From Zero to Stock Hero
Volume I, II & III
For everyone who joined recently, here’s the full three-part Zero to Stock Hero series in one place. (NO PAYWALL)
They’re still some of the most practical things I’ve written.
Part 1
In markets, you’re not rewarded for knowing what’s next - you’re rewarded for surviving what’s next.
Before we begin, here are the three simplest, yet most valuable tips I was ever given:
Hold a trade longer than you think you should.
Go with your gut.
Buy into strength.
Most fail because they do the opposite of them all. They cut winners early, or they overthink and override instinct. They second-guess themselves right out of good trades. The good trades don’t scream. They just start working and keep working, if you let them. Mastering these three won’t make you invincible, but they’ll keep you out of 90% of dumb mistakes.
Anyway… Shall we begin?
Stocks aren’t just symbols flickering on a screen. They’re belief systems, battlegrounds, and balance sheets all wrapped into one messy, beautiful yet infuriating package. If FX is the plumbing of the global financial system, then equities are its heartbeat - pumping with optimism, greed, fear, and raw human innovation in real time. Every earnings whisper, every CEO stumble, every Fed decision, it all flows through that endless digital tape, and somehow we’re supposed to make sense of it all.
This is your map. Not a get-rich-quick brochure promising $10k days from your kitchen table. Not another “hot stock picks” newsletter, though I do provide that. This is just a map for navigating the equity landscape with a trader’s eye and a macro lens, written by someone who’s paid the tuition fees for these lessons the hard way (and trust me, I have).
If you’ve ever stared at a screaming green candle and felt that familiar tug - “should I chase it?”, this one is for you. If you’ve watched Nvidia rip 8% and somehow your completely unrelated restaurant stock decided to join the party (or the selloff), and you had no idea why, this is for you. If you’re tired of the Twitter gurus and YouTube charlatans promising easy money while you’re still trying to figure out why your “sure thing” tech play is acting like a penny stock, and you get burned, this is for you.
Look, I’ve been that person. I’ve chased the momentum. I’ve misread the multiple expansion. I’ve held through many drawdowns. The market has a way of humbling you just when you think you’ve got it figured out. But somewhere between the losses and the lessons, patterns start to emerge. You begin to see the matrix behind the madness.
This post is designed to take you from confused spectator to informed participant , or if you’re already trading, from messy participant to structured stock operator. We’ll move through:
What stocks really are and why they actually move (spoiler: it’s not always fundamentals)
How macro and micro forces collide in ways that make no sense until they suddenly do
The hidden psychology and structure of indices that drive more moves than you think
Earnings season landmines
The Mag7 effect
Flow dynamics, ETFs, and how passive money creates active opportunities
Why retail and institutional money behave like completely different species
Tools that actually help instead of just selling you hope in a subscription package
Believe it or not, you don’t need to trade every day. Yep, the truth hurts, but you probably shouldn’t. But if you’re going to step onto this battlefield, you need to at least understand the terrain. There are few worse feelings than watching a position bleed while having no clue why the market suddenly decided your stock was guilty by association with something happening three sectors away.
The goal of this post isn’t to make you rich - that’s on you. My goal is to arm you with context so you can tell the difference between noise and narrative, narrative and actual signal. So when the next “surprise” earnings reaction happens, or when your safe dividend stock suddenly moves like a crypto coin, you’ll have a framework for understanding why.
The market will still surprise you. It surprises everyone. But at least you won’t be surprised by your own lack of understanding.
Let’s get into it.
Risk disclaimer: This post may cause increased caffeine consumption. Proceed with some enthusiasm (and a healthy dose of caution). It’s long.
What Is a Stock?
A stock is more than a ticker symbol – it’s a slice of a living, breathing business.
Let’s cut through the jargon and start with what matters: when you buy a stock, you’re literally buying a piece of a real company. Not a derivative, not a contract, not some abstract financial instrument, you’re getting actual ownership. Think of it like this: if Apple were a massive pizza (bear with me here), your single share would be one tiny slice of that pizza. If Apple grows and becomes more valuable, your slice grows with it. If Apple has a rough quarter, your slice shrinks accordingly.
But here’s where it gets interesting, and where most people miss the point. You’re not just buying a number that goes up and down. You’re buying into the dreams, mistakes, innovations, and occasional disasters of real people running real businesses. Every earnings call, every product launch, every CEO tweet, it all flows through to your position because you literally own a piece of the action.
The Beautiful Risk of Ownership
As a shareholder, you get some pretty cool rights. You can vote on major company decisions (though unless you own millions of shares, your voice is more like a whisper in a stadium). You might get dividends if the company decides to share its profits. But here’s the catch that keeps most people awake at night: you’re dead last in line if things go sideways.
If a company goes bankrupt, everyone gets paid before you - employees, suppliers, the government, bondholders, even the guy who delivered the office coffee. You get whatever’s left, which is often nothing. It’s the ultimate high-risk, high-reward setup. Bondholders get their steady interest payments and sleep soundly. Stock owners get the sleepless nights and the occasional life-changing windfall.
The Magic of Limited Liability
Here’s something that would blow the minds of merchants from centuries past: you can’t lose more than you put in. Buy $1,000 worth of stock in a company that goes spectacularly bust? You lose your $1,000, period. The company’s creditors can’t come after your house, your car, or your remaining savings.
This might seem obvious now, but it wasn’t always this way. Back in the day, business owners were personally liable for everything. The Dutch East India Company in the 1600s was revolutionary because it let regular people fund risky voyages without risking personal ruin. That simple concept, limited liability, is what made modern capitalism possible. It’s what lets you take a flyer on that promising biotech stock without worrying about losing your shirt if their drug trials fail.
Understanding What You’re Actually Buying
Not all stocks are created equal, and understanding the differences can save you from some painful surprises. Let me break down the menagerie:
Common vs. Preferred
Most of what you’ll trade is common stock, you get voting rights and a seat at the table (however small). Preferred stock is like being aristocracy: you don’t get to vote, but you get your dividends first and you’re ahead of common shareholders if the company goes under. Think of preferred as the stock market’s version of first-class passengers getting off the plane first.
Size Matters, fellas.
Market cap (total value of all shares) tells you what size company you’re dealing with:
Large-caps are the aircraft carriers of the stock world - Apple, Microsoft, companies worth hundreds of billions (a few are worth trillions). They’re stable, predictable, and about as exciting as watching paint dry (until they’re not). But when you need something reliable in your portfolio, these are your anchors.
Small-caps are the speedboats - nimble, fast-moving, and occasionally prone to capsizing in rough seas. They can double on good news or get cut in half on bad earnings.
Penny stocks are the jet skis of the stock world - fun to watch, dangerous to ride, and most people who get on them end up in the water. The graveyard of blown-up trading accounts is littered with penny stock casualties. Not my cup of tea.
Growth vs. Value: The Tortoise and the Hare
Growth stocks are the companies everyone’s talking about at dinner parties. They’re usually reinvesting every penny back into the business, promising exponential expansion. Nvidia, Tesla, Netflix in its heyday, any biotech with a promising pipeline - these are growth plays. They trade on dreams and potential, which means they can soar on good news and puke when reality doesn’t match expectations.
Value stocks are the wallflowers of the stock market, solid companies that nobody’s paying attention to. Maybe they’re in boring industries, maybe they had a rough patch, but they’re trading cheap relative to their fundamentals. The catch? Sometimes stocks are cheap for good reason, and sometimes they stay cheap longer than your patience lasts.
Cyclical vs. Defensive
Cyclical stocks are like your fair-weather friends. They’re great company when times are good, but disappear when things get tough. Airlines, car manufacturers, and luxury goods, these stocks live and die by the economic cycle. Buy them at the right time in the cycle and you’ll look like a genius. Buy them at the wrong time, and you’ll wonder why your recovery play keeps going down.
Defensive stocks are the reliable friends who show up with drugs and broth when you’re sick. Utilities, consumer staples, healthcare, tobacco - people need these regardless of whether the economy is booming or busting. They won’t make you rich overnight, but they’ll still be there when the market decides to have a meltdown.
In summary, stocks represent ownership and come in many varieties. Knowing what type of stock you’re dealing with (big or small, growth or value, cyclical or defensive, etc.) will help set expectations about its behaviour.
How Stock Prices Move: The Beautiful Chaos Behind the Numbers
If you’ve ever watched a chart for more than five minutes, you’ve probably had that moment of existential confusion: “Why the hell did it just do that?” One minute, your sure thing tech name is climbing steadily, the next it’s puked 5% on news that seems completely unrelated.
Here’s the thing nobody tells you upfront: stock prices move for dozens of reasons, and sometimes for no reason at all. But underneath the apparent chaos, there are patterns and forces you can learn to recognise. Think of it like weather, you can’t predict exactly when it’ll rain, but you can learn to read the clouds.
In the long run, and I’m talking years here, not days, stock prices tend to follow a company’s ability to make money. I still think Benjamin Graham said it best: “In the short run, the market is a voting machine, but in the long run, it’s a weighing machine.” Short-term prices are like a popularity contest run by caffeinated teenagers. Long-term? That’s when the adults finally show up to check the books. Or the other way round, who knows?
Earnings
At its core, a stock represents your slice of a company’s future profits. When a company consistently grows its earnings, the stock usually follows… (eventually). The keyword there is “eventually.” I’ve watched fantastic companies report blow-out quarters and seen their stocks drop 10% because the market was having a mood swing that day, and I have seen the same happen, smashing sell-side numbers but missing buy-side estimates.
Earnings per share (EPS) is the company’s net profit divided by the number of shares outstanding. If a company makes $100 million and has 50 million shares outstanding, that’s $2 per share. Simple math, but here’s where it gets interesting: the market’s reaction to that $2 can be anything from “meh” to “holy grail discovered.” Earnings reactions can be for the a multitude of reasons, including EPS or maybe the CEO (not mentioning any names) has mentioned AI 483 times on the earnings call.
The P/E Ratio: What Will People Pay for a Dollar of Profit
This is where things get psychological. The price-to-earnings ratio tells you how much investors are willing to pay for each dollar of a company’s annual profit. If a stock trades at $30 and earns $2 per share, that’s a P/E of 15x. Meaning people are paying $15 for every $1 of annual earnings.
A high P/E (say 30x or 50x) usually means one of two things: either investors expect explosive growth, or they’ve lost their collective minds. Tesla traded at ridiculous multiples for years because people believed it would be the future of transportation. Some said it was justified as Tesla is a tech stock. Some say it wasn’t, as Tesla is an auto name… Sometimes they were right, sometimes... well, sometimes reality is a harsh teacher.
A low P/E often signals a value opportunity, sometimes a value trap. Maybe it’s a solid company that Wall Street forgot about, or maybe it’s cheap because the business is slowly dying. The art is figuring out which one you’re looking at.
Sometimes, cheap is cheap for a reason. But saying that, I think the last time I bought a name and the P/E ratio was part of the thesis was here. Back when I bought META in the lows 90s at 8.5x trailing P/E. Believe it or not, META became a value name for a short period. (I still hold META till this day)
Other Valuation Metrics: The Extended Family
P/E ratios are just the beginning. Different industries worship different metrics, I am not going into each of them as I don’t want this post to end up being like a textbook:
PEG ratio tries to account for growth (because paying 30x earnings for 40% growth might make sense)
Price-to-sales matters for companies that aren’t profitable yet
Price-to-book is big in banking and real estate
EV/EBITDA (enterprise value to earnings before interest, taxes, depreciation, and amortisation), yes, it’s a mouthful, but it’s useful for comparing companies with different capital structures. Lots argue it’s more important than P/E.
Instrinsic Value What a stock is really worth based on fundamentals. One way to estimate this is via the DCF model (discounted cash flow).
Different metrics matter in different contexts. Trying to value Netflix using bank metrics is like judging a fish by its ability to climb a tree.
Supply and Demand
Sometimes stocks move simply because more people want to buy than sell, or vice versa. Sometimes they move when there’s less buyers than sellers just because the buyers are buying a larger size. This sounds obvious, but the reasons behind the buying and selling can be wonderfully absurd.
The Liquidity Game
Big, famous stocks like Apple can absorb massive trades without flinching. You could buy $10 million worth and barely see a blip. Try that with a small-cap biotech, and you might single-handedly move the stock 5%, maybe even more. It’s like the difference between throwing a pebble into the ocean versus a swimming pool.
I learned this lesson early on, watching a small-cap stock I owned gap up 15% on “no news.” Turns out someone was rebalancing and needed to buy exactly what I owned. Sometimes you’re skilled, sometimes you’re lucky, and sometimes you can’t tell the difference.
News
Stock prices move on news, they often move more on the perception of news than the news itself. I’ve seen companies report exactly what analysts expected and still get hammered because the market was hoping for a miracle.
Then there’s the classic “buy the rumour, sell the news” phenomenon. A stock runs up for weeks on whispers, then promptly drops when the news is actually announced. Why? Because everyone who wanted to own it based on the rumour had already bought. When the news hit, they took profits.
It’s like showing up to a party that everyone’s been talking about, only to find out the best conversations happened before you arrived.
Sentiment
Here’s where it gets really interesting (and frustrating). Stock prices are moved by humans (algos too, but those are made by humans, for now…), and humans are emotional creatures who occasionally make decisions based on logic. The classic line comes to mind - the market can stay irrational longer than you can stay solvent, and I’ve got some battle wounds to prove it.
Fear and Greed
When people are greedy, they’ll pay ridiculous prices for mediocre companies with good stories. When they’re fearful, they’ll sell fantastic companies at bargain prices because they can’t sleep at night. (Small tip, if you can’t sleep because a position is keeping you up - cut it - this should never happen).
The VIX is the fear gauge. When it spikes above 30, people are panicking. When it drops below 15, everyone’s feeling invincible as its smooth sailing. Both extremes tend to create opportunities, though timing them is like trying to catch a falling knife while riding a unicycle.
Momentum - You Can Buy Strength, You Know
Rising stocks attract buyers (FOMO is indeed a real thing), which pushes them higher, which attracts more buyers. It’s a beautiful feedback loop until it isn’t. I’ve watched stocks double on no fundamental change whatsoever, just because everyone wanted to be part of the party.
The flip side is equally brutal. When selling starts, it can cascade as stops trigger, which triggers more selling, which triggers margin calls, which triggers more selling. It’s like watching dominoes fall in slow motion, except each domino is a percentage point of your net worth.
Narratives
Sometimes, entire sectors move based on a compelling story that captures the market’s imagination. The dot-com boom had “the internet changes everything.” The 2020-2021 era had electric vehicles and clean energy. 2023 brought us the AI revolution.
These narratives can become self-fulfilling prophecies. If enough people believe AI will transform the world, they’ll bid up AI stocks, which validates the narrative, which attracts more buyers. Nvidia went from a gaming chip company to the poster child of the AI revolution, and its stock price followed accordingly.
But narratives eventually have expiration dates (not it applies to NVDA). When reality doesn’t match the hype, or when the next shiny narrative comes along, yesterday’s darlings become today’s casualties. You saw this play out with cannabis stocks a few years back.
The trick isn’t avoiding narratives, they’re incredibly powerful when they’re building. The trick is recognising when you’re riding a wave versus getting caught in a tsunami. I did do a write up on narratives which I have attached below.
The Uncomfortable Truth
Here’s what they don’t teach you in books: sometimes stocks move for no good reason at all. Algorithms trading against other algorithms, creating feedback loops that have nothing to do with the underlying business. A typo in an earnings release that gets corrected an hour later, but not before the damage is done.
Markets are the most efficient information-processing machine ever created and a chaotic mess of human emotions amplified by technology. Your job isn’t to make sense of every move, it’s to understand the forces at play well enough to position yourself intelligently. When you finally realise that it’s not your job to make sense of every move, you will succeed.
Sometimes you’ll buy a stock based on solid fundamentals and watch it go nowhere for months while some meme stock doubles for no reason. Sometimes you’ll nail a sentiment trade perfectly and feel like a genius, then get humbled the next week when you try to repeat it.
The market will humble you. The key is learning from the humbling instead of being destroyed by it.
That’s the game we’re all playing, trying to find signal in the noise.. Sometimes the fundamentals win, sometimes sentiment rules, and sometimes you just get pure lucky.
Sector Rotation + Fund Flows
Here’s something that’ll mess with your head: sometimes your individual name moves not because of anything the company did, but because a pension fund in Ohio decided to rotate from growth to value.
Believe it or not, big institutional investors, pension funds, sovereign wealth funds, massive hedge funds, move money around like you and I. When they decide it’s risk-on, money floods into tech and growth stocks. When they get spooked and it’s risk-off that same money rushes into more defensive names - utilities and consumer staples like people fleeing to the basement during a tornado.
Your stock can be caught in someone else’s portfolio rebalance, and there’s not a damn thing the company can do about it.
ETFs make this even more pronounced. When money flows into the “Technology Select Sector SPDR Fund,” that fund has to buy every tech stock in its index, regardless of whether those individual companies deserve it. Sometimes you’re riding the wave, sometimes you’re getting dragged along by it.
Technical Analysis
Now, I know some of you are rolling your eyes at the mention of technical analysis , drawing lines on charts and finding patterns in squiggly lines. But here’s the thing… I was that guy once, convinced it was all astrology for retail traders, but enough people believe in it as the years have gone on that it actually matters a LOT!
When a stock breaks below a widely-watched support level, a thousand algorithms and technical traders all hit sell at the same time. Their selling pushes the stock lower, which triggers more technical selling, which validates the original technical signal. I guess you could say it’s like a financial Ouija board that works because everyone’s pushing the planchette in the same direction. Likewise, a breakout above a resistance level might attract buying. Technical trading can create self-reinforcing moves in the short term.
Additionally, there are stop-loss orders clustered around certain prices – if those trigger, they can accelerate a move further.
We have all seen fundamentally solid companies get absolutely destroyed because they hit some technical level that the chart-watchers didn’t like. Is it rational? Not really. Does it move stock prices? Absolutely.
The algorithms make it even crazier. Some machines are scanning thousands of stocks every millisecond, looking for momentum shifts, technical breakouts, or patterns that worked in the past. Sometimes they create feedback loops that turn a small move into a big one, just because the machines are all following similar logic.
I guess the lesson for technical analysis is this… You don’t need to believe in it if what you’re doing is working, but you best respect it. Ignoring these levels can be like ignoring traffic lights.
A Real-World Example - When Everything Goes Wrong (And Right)
Let me paint you a picture with a hypothetical scenario that’ll feel painfully familiar:
Company XYZ is trading at $100, earning $2 per share (P/E of 50x, yeah, it’s pricey, but it’s a growth darling). Earnings day arrives. The company beats expectations with $2.10 per share and raises guidance. Fundamentally, this is good news.
But during the call, the CEO mentions “some uncertainty” in the next quarter’s pipeline. Meanwhile, the Fed just hinted at rate hikes, which makes those high P/E multiples look less attractive. And separately, a few funds decide this is a good time to take profits and reduce their positions.
Result? Despite beating earnings, XYZ drops 5% to $95 over the next few days.
Sound familiar? I’ve lived through this exact scenario more times than I care to count. You do all your homework, the company executes perfectly, and the stock still gets punished because the market was in a mood.
But here’s the rest of the story: a month later, the Fed softens its tone, market sentiment improves, and suddenly everyone remembers that XYZ is working on AI chips (or whatever the hot narrative is that week). Money flows back into tech, analysts start talking it up on CNBC, and boom XYZ not only sees $100 but shoots to $110.
Why the higher price? Maybe investors are now willing to pay 35x forward earnings instead of 33x because rates aren’t going up as fast. Maybe earnings estimates crept up to $3.20. Maybe it’s just that the market’s mood improved and people remember why they liked the stock in the first place.
This back-and-forth happens constantly. Short-term, anything can move a stock: a tweet, a sector rotation, a technical breakdown, or news that has nothing to do with the actual business. But if XYZ truly grows earnings from $2 to $5 over a few years, the stock will likely be much higher than $100, regardless of all the noise in between.
The art is learning to separate signal from noise. The signal is the fundamental trajectory - is this company getting stronger or weaker? The noise is everything else.
The Fed - The Ultimate Market Puppet Master
Before we wrap up, let’s talk about the 800-pound gorilla in every room: the Federal Reserve. When people say “Don’t fight the Fed,” they’re not being dramatic. It’s a tale as old as time! They’re acknowledging that the world’s most powerful central bank has more influence over stock prices than any single company’s earnings report.
When the Fed cuts rates or pumps money into the system through quantitative easing, some of that cash finds its way into stocks. The 2010s and especially 2020-2021 showed us what happens when the money printer goes brrrr, stocks float higher on a sea of liquidity, sometimes regardless of fundamentals.
There’s a concept called the Fed Put, the belief that if stocks drop too hard, the Fed will step in to save the day by cutting rates or providing more stimulus. It’s not an official policy, but investors have seen it play out enough times (1987, 1998, 2008, 2018, 2020) that they’ve started to count on it.
This creates a dangerous psychological dynamic where people “buy the dip” not because stocks are cheap, but because they expect the Fed to ride to the rescue. Basically, it works until it doesn’t.
2022 was a brutal reminder of what happens when the Fed takes away the punchbowl. As rates went up to fight inflation, all those high-flying growth stocks that were floating on cheap money suddenly found themselves without life jackets. Some were cut in half, some even more.
The lesson? Liquidity is like the tide, it lifts all boats when it comes in and exposes who’s swimming naked when it goes out. Your job is to make sure you’re not the one without shorts when the water recedes.
The Bottom Line
Stock price movement is equal parts science and art, logic and madness. You need to understand the fundamental climate patterns, earnings growth, valuation metrics, and industry trends. But you also need to read the daily weather and ride the waves of sentiment as they come.
Sometimes you’ll nail the fundamentals perfectly and still get crushed by a sentiment shift. Sometimes you’ll catch a momentum wave and feel like a genius, only to get humbled the next week when you try to repeat it.
Markets will teach you humility, patience, and the difference between being right and making money. As I said before, your job isn’t to predict every move; it’s to position yourself intelligently for the long-term direction while managing the short-term chaos.
Because at the end of the day, stocks are just pieces of businesses run by humans, traded by other humans, all trying to figure out what comes next. Sometimes it’s rational, sometimes it’s not, but it’s always human.
And I think that’s both the challenge and the opportunity.
Macro to Micro: When the Big Picture Crushes Your Perfect Stock Pick
Here’s a painful truth I learned the hard way: you can pick the perfect company with flawless execution, growing earnings, and a brilliant management team, and still watch your investment get destroyed because the Federal Reserve decided to hike interest rates.
Stocks don’t exist in a bubble. Even Apple can get crushed if the macro environment turns hostile.
Understanding macro isn’t just helpful, it’s survival. Because when the economic tide turns, it doesn’t ask if your company deserves to get swept away.
Interest Rates: The Invisible Hand
Think of interest rates as gravity for the financial universe. When rates are low, everything floats higher. When they rise, gravity gets stronger, and things start falling back to earth.
Here’s why this matters to your stock portfolio: interest rates represent the “risk-free” return you can get. If you can earn 5% in a Treasury bond with zero risk, suddenly that growth stock trading at 30x earnings needs to work a lot harder to justify its existence.
The 2020-2022 Whiplash: A Masterclass in Rate Impact
Let me paint you a picture of what this looks like in real life. In 2020, the Fed slashed rates to basically zero and fired up the money printer. Suddenly, your savings account was paying 0.1%, and a 10-year Treasury was yielding maybe 1%.
Investors looked around and said, “Well, there is no alternative” (they literally called it TINA). Growth stocks trading at 40x earnings didn’t seem so crazy when the alternative was earning essentially nothing in bonds. Tesla could trade at ridiculous valuations because when you discount future profits at near-zero rates, those far-off earnings look pretty valuable today.
People quit their jobs to day-trade because “stocks only go up.” Every dip got bought. Every growth story got bid to the moon. It felt like financial gravity had been suspended.
Then 2022 happened.
Inflation spiked to levels we hadn’t seen since the 1980s, and the Fed performed the great hiking crusade where rates went from zero to five per cent in what felt like a weekend. Suddenly, that same Treasury bond was yielding 5%, real money, with no risk.
The growth stocks that looked reasonable at 0% rates suddenly looked insane at 5% rates. Why own a speculative biotech when you could get 5%? The gravity came back with a vengeance. Some growth stocks fell 70-80%. Companies with no profits got obliterated. Even profitable companies saw their valuations compress as investors rotated into value stocks and bonds.
The macro tide had turned, and it didn’t care about your fundamental analysis.
Different Sectors, Different Reactions
Interest rates don’t affect all stocks equally, which is where it gets interesting:
Banks generally like moderate rate increases because they can charge more for loans. But if rates go too high too fast, loan defaults can spike and banks get hurt anyway. It’s a Goldilocks situation; they want rates not too hot, not too cold.
Real estate companies and REITs hate rising rates because their business models depend on cheap financing. When mortgage rates jump from 3% to 7%, suddenly fewer people can afford houses, and real estate stocks get crushed.
Utilities are the weird ones. They’re often bought for their dividends, so when Treasury yields shoot up, investors think “why own a utility paying 4% when I can get 5% risk-free?” But in a recession, they’re also seen as safe havens. It’s complicated.
The Yield Curve
Here’s a nerdy concept that actually matters (sometimes): the yield curve. Normally, long-term bonds pay higher rates than short-term ones (because you’re tying up your money longer). When this flips, when short-term rates are higher than long-term rates, it’s called an inversion.
Inverted yield curves have predicted almost every recession since World War II. It’s like the bond market saying, “Things are so bad right now that we think rates will have to come down in the future.” And when recessions hit, corporate profits usually fall, which means stock prices fall.
In 2022-2023, the yield curve inverted deeply. Short-term rates hit 5%+ while 10-year bonds stayed around 4%. The bond market was essentially screaming “recession incoming,” and many were watching nervously for it to materialise. Still to this day, it remains the most speculated recession ever - it still hasn’t happened.
Inflation
Inflation might be the most misunderstood force in markets. Everyone talks about it, but most people don’t really grasp how it ripples through to stock prices.
Here’s the simple version, inflation is when stuff gets more expensive. But the devil’s in the details.
The 2022 Inflation Shock: When Everything Went Wrong
We lived through the inflation spike of 2022, and it was educational in the worst possible way. CPI hit levels we hadn’t seen since the early 1980s, over 9% at the peak. Oil prices went crazy (this was also partly due to Russia Ukraine) and groceries became a luxury.
Consumers started cutting a little on everything that wasn’t essential. Companies began reporting that customers were trading down to cheaper options or simply buying less. Walmart and Target both mentioned customers skipping purchases. Even Apple warned about currency headwinds and economic uncertainty. This situation was slightly different to the 80s as the consumer remained surprisingly strong despite inflation and they still remain strong till this day.
But here’s what really mattered for stocks: inflation forced the Fed’s hand. They had to raise rates aggressively to fight it, which brought us back to the interest rate problem I just discussed.
The Good, the Bad, and the Ugly of Inflation
Not all inflation affects all companies equally:
The Winners: Companies with pricing power did fine. If you’re Coca-Cola and everyone’s costs are going up, you just raise the price of Coke and consumers grumble but still buy it. Energy companies did really well in 2022 because oil and gas prices soared.
The Losers: Companies with long-term contracts or those in hyper-competitive industries got squeezed. If you’re locked into selling your product at 2021 prices but your costs have doubled, you’re in a bit of trouble.
The Complicated: Some companies could pass on costs but with a lag, so their margins got squeezed temporarily. Others found that while they could raise prices, volumes fell enough to hurt profits.
Moderate Inflation vs. the Scary Kind
Here’s something that surprises people: a little inflation (2-3%) is healthy. It usually means the economy is growing, and companies can gradually raise prices. The Fed targets 2% inflation for a reason.
The scary inflation is the unexpected kind. If it suddenly jumps to 6%, that’s when markets panic. Not because 6% inflation is necessarily catastrophic, but because it means all the assumptions about Fed policy, corporate costs, and (normally) consumer behaviour just went out the window.
Deflation: The Opposite Problem
While high inflation is bad, deflation (falling prices) can be worse. Japan spent decades dealing with deflation, and its stock market went nowhere for ages. When prices are falling, simply put, consumers delay purchases (”why buy now when it’ll be cheaper next month?”), which creates a vicious cycle of falling demand.
Why This All Matters
Macro doesn’t just influence your stocks; it often overwhelms everything else. I’ve seen companies beat earnings estimates by 20% and still fall because the macro environment was hostile at that point. I’ve also seen mediocre companies get lifted by macro tailwinds they did nothing to deserve.
Your job as an investor isn’t to predict macro (good luck with that), but to understand how different macro environments affect different types of stocks:
Rising rate environment? Favour value over growth, banks over REITs, profitable companies over the stories.
High inflation? Look for companies with pricing power, avoid those with fixed contracts, consider energy and materials.
Recession fears? Defensive stocks, consumer staples, companies with strong balance sheets.
The best companies can navigate any macro environment, but even they’ll see their stock prices reflect the broader tide. Understanding that the tide doesn’t guarantee success, but ignoring it almost guarantees failure.
Remember, you might be right about the company and still lose money because you were wrong about the context. The macro environment is the stage on which your individual stock picks perform, and sometimes the stage itself becomes the story.
The Market’s Scoreboards
An index is like checking the scoreboard during a football match. But if you don’t know who scored, how, and when, you’re not actually watching the game.
When someone asks, “How’s the market today?” what they usually mean is: “What’s the S&P doing?” Or the Nasdaq. Or the Dow. They’re not asking about your meme stock or the regional banks you’re nervously bag-holding. They’re asking about indices, the broad, often oversimplified scoreboards that compress hundreds of stories into a single number.
Indices matter. But if you don’t know how they’re built, you’ll misread the story they’re telling. So let’s humanise these benchmarks, strip away the mythology and get real about how they work, how they skew, and why the index print doesn’t always match what’s happening in your portfolio.
S&P 500
The S&P 500 is the index. The heavyweight. The benchmark fund managers are judged against, and the one everyone refers to at the pub when they say “the market’s up.” It tracks 500 of the largest public companies in the U.S. across all major sectors. but don’t let the round number fool you. It’s not “equal slices of 500 stocks.”
The S&P is market-cap weighted, meaning the bigger the company, the more influence it has. Apple isn’t just in the S&P, it is the S&P on some days. In recent years, Apple and Microsoft alone have accounted for over 10% of the index. The top 10 names? Over 30%.
So when the S&P rallies, it doesn’t necessarily mean the whole market is healthy. Sometimes, it’s just the big boys, aka the Magnificent 7/MAG7 (Microsoft, Apple, Amazon, Google, Nvidia, Tesla & Meta) pulling the sled while the rest of the team is face down in the snow.
Here’s where it gets tricky: in 2023, the S&P looked strong on paper. But under the hood, most stocks weren’t keeping up. The index’s gains were driven overwhelmingly by the Magnificent 7. Three-quarters of the performance came from less than 2% of the names. So if you were diversified, ironically, if you were doing it right, you might’ve been losing money while “the market” looked like it was ripping.
And that disconnect? That’s the cost of not understanding index construction. It’s also why traders started tracking equal-weight versions of the index more closely then, we’ll get to that shortly.
Nasdaq 100
The Nasdaq 100 is basically the growth-stock index. It’s 100 of the biggest non-financial companies listed on the Nasdaq exchange, but in practice, it’s just tech and tech-adjacent juggernauts with a couple of outliers for flavour.
This is the index you trade if you believe in software margins, AI narratives, or cult CEOs with rockets and flame-throwers. Apple, Microsoft, Google, Amazon, Meta, Nvidia, Tesla - the usual suspects. When tech leads, Nasdaq outperforms. When tech gets punched in the mouth, Nasdaq bleeds more than the others.
It’s also cap-weighted, so the same story applies: a handful of names do most of the work. In 2023, it got so concentrated that the Nasdaq committee did a one-off rebalance to stop the top 7 from exceeding 50% of the index. That’s how top-heavy it had become.
If you trade QQQ (the ETF that tracks this index), just know: you’re not trading a balanced tech basket. You’re buying a leveraged opinion on whether the Mag7 keeps winning.
Dow Jones - Grandpa’s Gauge
The Dow is the most iconic index and arguably the least useful. It tracks just 30 stocks. Not the biggest 30, not the fastest growing 30, just 30 blue-chip names across different sectors.
Worse, it’s price-weighted, which means it gives more weight to higher share prices, not larger market caps. A $300 stock moves the Dow 10 times more than a $30 stock, regardless of the companies’ actual value. In 2024, a single down day in Goldman Sachs could drag the Dow more than the entire utilities sector imploding.
That said, the Dow still moves headlines. If it drops 500 points, CNBC will flash red banners “markets in turmoil” and your dad will text you asking if he should sell everything. As a trader, it’s background noise, but as a sentiment gauge for the public, it still matters.
Russell 2000 - The Crap
The Russell 2000 tracks 2000 smaller U.S. companies. It’s market-cap weighted too, but the weights are much flatter, and the companies are more domestically focused and economically sensitive.
When the Russell is outperforming, it usually signals a risk-on environment: people are willing to own scrappier, more volatile stocks. When it lags, it often reflects caution - higher rates, tighter liquidity, a flight to safety.
In 2024, while the S&P and Nasdaq soared, the Russell lagged badly. Why? The Magnificent 7 don’t live here. Smaller companies couldn’t access cheap capital. Many had weaker balance sheets. So while big tech rode the AI wave, the little guys were paddling upstream. That divergence tells you a lot about where the liquidity is flowing and who it’s skipping.
Equal Weight vs Cap Weight: The Breadth Truth Serum
Want to know how healthy the market really is? Compare the cap-weighted S&P 500 to its equal-weight sibling. In the equal-weight version, each of the 500 stocks gets the same allocation. So Apple and AutoZone have the same impact.
In 2023, the cap-weighted S&P did +21%. Equal weight? Around +14%. That gap is your warning light. It tells you the rally isn’t broad, it’s being dragged higher by a few monster names. That doesn’t invalidate the rally, but it changes how you position. If you’re long “the market” but underweight the monsters, you’ll underperform. If you’re long equal-weight and thinking you’re tracking the index, you’re not.
Why Index Construction Actually Matters
Index construction affects:
Your ETF performance
How passive flows distort price action
Which companies benefit from forced buying
What happens on rebalancing dates
If you don’t understand this, you’ll misread macro moves, get chopped up in rotations, or wonder why your portfolio’s flat while the S&P’s at all-time highs.
Tesla’s inclusion in the S&P 500 in December 2020 caused a buying frenzy. Why? Passive funds needed to own it. That’s not narrative or valuation, that’s mechanical flow. The same goes for removals, sector reclassifications, and special rebalances.
This game is about knowing what’s really moving, and why. Not just reading the scoreboard.
The Mechanics of Earnings Season
Earnings season is where your thesis meets the truth.
Every quarter, the curtain lifts. Companies reveal what’s really been going on behind the scenes - the revenue, the profits, the guidance, the tone. And the market? It reacts instantly, brutally or euphorically. That’s a lie, sometimes flat.
This is earnings season. It comes four times a year - like a quarterly report card for Wall Street. And just like in school, some names pass the test with flying colours, some scrape by, and some fail spectacularly.
When It All Kicks Off
Earnings season usually begins a few weeks after the quarter ends. Think: mid-Jan, mid-April, mid-July, mid-October. Traditionally, it kicked off with Alcoa, the aluminium giant. These days, it’s more often JPMorgan, Goldman, and the rest of the financials setting the tone. Then come the tech titans. Retail and stragglers show up last (some of them run funky fiscal calendars).
What to Look For in a Report
Here’s what actually moves stocks:
EPS (Earnings Per Share): The bottom line. Net profit divided by the number of shares. If the number beats expectations, the market cheers. If it misses? Expect a slap.
Revenue: For high-growth companies, especially, this can matter more than EPS. If your story is “we’re taking over the world,” but your top line is flat, investors start to question the plot.
Guidance: This is the big one. The company can beat last quarter but guide lower, and the stock tanks. Why? Because forward expectations reset the narrative. One cautious comment from a CFO can knock 15% off a stock.
Margins: Improving margins means pricing power or efficiency. Falling margins might signal inflation, cost issues, or competitive pressure. Don’t ignore them.
Key Metrics: Every industry has its own pulse. For a social platform, it might be daily active users (DAUs). For a retailer, same-store sales. For a SaaS firm, the net retention rate. Read between the lines and see what management’s highlighting, and what they’re quietly burying.
The Call: Where the Real Drama Happens
Earnings press releases are scripted. But the conference call? That’s where the gloves come off. Analysts get to question management. Executives try to spin the quarter. Sometimes they do a great job. Other times, they slip, and that’s when the stock can swing wildly.
A good call can turn a neutral report into a +6% move. A bad one can turn a beat into a -10% puke. Traders listen for tone, confidence, or any sign that management is rattled.
The Whiplash: After-Hours vs The Next Day
Often, the report drops after the market closes. Stocks will shoot up or down instantly. But the real move sometimes comes the next morning, once the call is digested, the analyst notes are out, and liquidity returns.
You might see:
+5% on the headline beat
Then, 7% during the call
Then flat the next morning
It’s messy. Which is why many traders avoid holding positions into earnings or hedge unless they have conviction, or an edge (questionable to have an edge with earnings though really…).
Why It Sets the Tone
One company’s report can influence an entire sector. If Delta says travel demand is surging, airline stocks across the board might rally. If FedEx misses and blames soft shipping volumes, retail and logistics names might get dragged.
Sometimes the first few reporters of the season set the tone for sentiment. Strong numbers early? People extrapolate strength. Early weakness? Caution spreads.
Post-Earnings Drift
There’s a weird phenomenon: when a company delivers a big surprise, up or down, the stock often keeps drifting in that direction for days or weeks after. This is called post-earnings announcement drift (PEAD). It’s like the market slowly recalibrates. Some funds take time to reposition. Others want confirmation. Either way, if you miss the initial pop, the move isn’t always over.
The Opportunity (and the risks)
Earnings season brings volatility. Implied volatility rises. And for some, this is prime hunting ground, trading around reactions, momentum, or the overreactions that inevitably come.
But it cuts both ways. If you’re wrong, you can be really wrong. Some traders only play post-earnings, after the dust settles, when sentiment extremes are clearer.
For long-term holders, this is when you recheck your thesis. Did the company do what you expected? Did anything change that warrants exiting or sizing up?
A Simple Anatomy of a Print
Let’s say Fed Inc reports:
EPS = $3.00 (vs $2.50 expected)
Revenue = $10B (vs $9.5B expected)
Raises full-year guidance by 5%
Stock jumps +8% in after-hours. On the call, the CFO mentions margin headwinds next quarter due to raw material costs. Stock trims gains to +5%. The next day it opens +6%, holds most of it. Over the next two weeks, it drifts up another +4% as analysts upgrade and institutions rotate in. Textbook strength.
Now imagine the opposite: they miss on both top and bottom lines, and guidance is cautious. The stock drops -12% after hours. On the call, tone is defensive. Next morning, it gaps down -15% and closes down -18%. Volume triples. Analysts start downgrading. Catching that bounce? Might be weeks away. The “value” buyers step in later… if it holds.
Watch for Buybacks and Dividends
Sometimes companies sweeten the pot with buyback announcements. “We’re authorising $10B in share repurchases.” That can lift a stock even if the quarter was just okay; it’s a signal of confidence. Buybacks are management’s way of saying: ‘We like this price more than your next idea.’ Sometimes they mean it. Sometimes they’re just out of ideas.
The same goes for dividend hikes. If a company increases its payout, it often signals stability and strength. Conversely, cutting a dividend is a red flag; market usually punishes that fast.
Why It Matters
During earnings, stocks trade more on their own stories and less on macro. Correlations drop. It’s a stock picker’s market during earnings season. If you’re good at reading individual setups, this is your time. If you’re not, sit back and learn.
The rest of the year, narratives and sectors tend to trade together. But earnings season? That’s where you see what’s real. And what was just a chart with hope baked in.
The Magnificent 7
The Mag7 don’t just move the market. Some days, they are the market.
In the last few years, a strange gravity has taken hold of U.S. equities. A handful of tech giants, seven, to be exact, have grown so large, so dominant, that they’ve become more than just companies. They’ve become the market’s pulse.
We call them Mag7 as I mentioned earlier: Apple, Microsoft, Amazon, Alphabet (Google), Meta (Facebook), Tesla, and Nvidia. They’ve each built empires in their own lane, phones, cloud, e-commerce, search, social, EVs, semis, but together, they’ve reshaped indices, flows, and the entire equity narrative.
The Stats That Make You Blink
By 2025, these seven alone made up more than 30% of the S&P 500. That means one out of every three dollars in the index is riding on a handful of names. In some months, over 70% of the index’s gains were attributable to this crew. Most would argue that’s not a market. That’s a monarchy.
And it’s not just size, it’s performance. From 2023 through 2024, while most of the S&P 500 was grinding sideways, the Mag7 were putting up double and triple digit gains. Nvidia’s AI rally alone looked like something out of the dot-com era. Microsoft and Apple were printing cash. Meta staged a huge massive comeback (thank you Zuck). Amazon kept pushing margins in AWS. Alphabet weathered the search wars. Even Tesla, for all its drama, kept finding narrative lifelines.
Why They’re So Powerful,
There are a few core drivers:
They’re still growing. These aren’t old blue chips with 2% topline growth. Many are still putting up 15-30% revenue growth, depending on the segment.
They have moats. Apple’s ecosystem. Microsoft’s enterprise lock-in. Nvidia’s chip dominance. Meta’s social reach. These are not easily disrupted.
They’re cash machines. These companies throw off billions in free cash flow. That fuels buybacks, (now for some) dividends, M&A, and moonshot R&D, which keeps the flywheel spinning.
They’re narrative stocks. AI, AR, clean energy, cloud, ads. They’re plugged into every popular secular growth theme on the board.
They’re liquidity vacuums. Because they’re so heavily weighted in indices, when passive money flows in, it flows into them. When retail wants exposure to tech, it’s often via QQQ or SPY, which means more of the same.
When They Go Up, Everything Usually Follows
When Nvidia has a monster earnings beat, you often see semis rip across the board. If Apple or Amazon rallies post-earnings, it lifts sentiment for consumer and tech broadly (with the AI theme - higher capex from Mag-7 ex NVDA = NVDA higher). They’re not just leaders, they’re bellwethers. If they’re green, the market breathes a little easier. If they’re red, the defensives even start sweating.
But this much concentration does come with risk.
Markets love leaders, until they don’t. And when the top becomes too narrow, it starts to wobble. If Apple disappoints, it doesn’t just drag Apple, it drags the S&P. When the Mag7 underperform, the whole “market” can look broken.
And the flip side of size is expectation. When you trade at 28x forward earnings, the bar is high. A small miss or soft guide can shave $100 billion off a market cap in a session. These names aren’t invincible, just really, really good at managing expectations (most of the time).
Not All 7 Are Created Equal
They’re not a monolith. Consider:
Apple and Microsoft: The grown-ups. Consistent cash flow, dividends, huge buybacks. Viewed as the safest of the bunch.
Nvidia and Tesla: The wildcards. Higher beta, high multiples, high narrative. Prone to monster rallies,and fast drawdowns.
Amazon and Alphabet: Execution-sensitive. Cloud and ad revenue can be lumpy. Margins and cost control matter here.
Meta: The comeback kid. Written off in 2022, rebounded hard by focusing on efficiency and riding the AI coattails.
So while they trade together in the eyes of passive flows, their individual drivers vary. One can stumble while another soars.
Trading Around the Mag7
Here’s the playbook:
Earnings = Events. These aren’t earnings calls, they’re market-moving catalysts. One print from Microsoft or Nvidia can set the tone for the week.
Gamma is relevant. Tesla, Meta and Nvidia are option-flow battlegrounds.
Sentiment gets crowded. When everyone is overweight the same 7 names, the risk isn’t just drawdown, it’s underperformance if the rest of the market finally rotates.
Breadth check: If these names are green but everything else is red, that’s not strength.. Watch equal-weight indices and breath metrics. Narrow leadership rallies don’t last forever.
Are They Too Big to Fail?
They dominate sectors and indices. They dominate mindshare. But that also makes them political targets. Regulators are always sniffing and antitrust cases are building. Eventually, someone might try to clip their wings.
In the meantime, they are the engine and the potential ice on the road.
As a trader or investor, you don’t have to love them. But you have to watch them. They set the tone. They swing the flows. And for now, they are the market.
Institutional vs Retail: Who’s Actually Moving the Market?
Retail traders bring passion and memes; institutions bring billions and risk models and both shape the tape.
If the market is a battleground, institutions are the tanks, and retail is the infantry. One has firepower and structure; the other has speed, unpredictability, and sometimes a flamethrower disguised as a meme.
Understanding who’s on the other side of your trade, and how they think, is a cheat code most ignore. So let’s break it down.
Institutions
These are your pension funds, hedge funds, mutual funds, insurance companies, and sovereign wealth funds. Some of them are running billions. Others are trading faster than your screen can update. Either way, they’re the ones with the flow that moves markets, especially in large-cap names.
They move size. A $100 million position isn’t placed with a market order. They use algos, dark pools, and sometimes take days to fill it without causing slippage.
They have tools. Bloomberg terminals. Endless research. Satellite data. Management access. When they say “we met with the CFO last week,” they have.
They have constraints. Mandates, compliance, benchmark pressure, risk teams. If a position gets too big, they’re often forced to trim even if they love it.
They influence the narrative. When the “smart money” rotates from growth to value, or when prime brokerage desks leak positioning data, the rest of the market often follows.
But they also crowd trades. When everyone is long the same names and the tide turns, it turns fast. And because they’re managing outside money, underperformance can get them fired. That means they often can’t be patient.
Retail
Retail is everyone else, from the guy buying 5 shares of Apple on Robinhood to the woman trading biotech breakouts from her kitchen table. One trade is small. But the collective weight? It can move mountains in the right names.
Where They Clash
Retail gets mocked for being “dumb money.” But they were early on the 2020 rebound while many pros were still in fetal position. Meme stocks? Wild, yes, but GameStop’s short interest was insane. The crowd saw it first. So far this year, retail have been the smart money - institutions remain underweight tech!
Institutions have more structure, but also more baggage. Risk models, redemptions, career risk. Sometimes the pro move is not making the obvious trade, because it would look bad on a slide deck.
Sentiment Matters
Retail sentiment is often visible on social media, YouTube, Reddit, or in options flow. Institutional sentiment is more subtle. you watch futures positioning, fund flows, prime brokerage data (options too).
But both swing. Retail flips from euphoria to despair like clockwork. Institutions do too, just with more jargon and longer meetings.
Your Edge as Retail
You’re nimble. You can exit or enter with zero slippage.
You’re patient. No quarterly review means you can ride conviction for years, if you’re right. But hey, you probably should do a quarterly review.
You don’t have to impress anyone. That’s a superpower. But it also means no risk manager gives you a tap on the shoulder to stop you from doing something dumb.
If you combine common sense with a clear process, you can exploit inefficiencies institutions have to ignore. Especially in small- and mid-cap names, or during narrative overreactions.
The Rise of Passive Investing
Over the last couple of decades, and especially since the 2010s, there’s been a massive shift from active stock-picking funds to passive index funds. Instead of paying a manager to select stocks (active mutual fund or hedge fund), many investors opt to just buy an index fund that tracks something like the S&P 500 or Nasdaq. The logic: many active managers underperform their benchmarks over time (after fees), so why not just get the benchmark return cheaply?
This led to huge inflows into index mutual funds and ETFs like Vanguard index funds, BlackRock iShares, State Street SPDRs (like SPY), etc. For instance, the SPDR S&P 500 ETF (SPY) is one of the largest ETFs and trades heavily every day. When you buy SPY, you’re effectively buying tiny pieces of all 500 S&P stocks in one go.
The effect: Passive buying lifts all stocks in the index, regardless of individual merit. Similarly, passive selling (when people redeem or sell index funds) hurts all constituents. This is why sometimes you see stocks moving together in a way that might seem unjustified by their individual news – it might be because of fund flows.
There’s a term “the ETF-isation of the market” – meaning so much money is tied up in ETFs now that often sectors or baskets of stocks move in unison as those ETFs trade. For example, if a lot of people buy a tech sector ETF, the fund has to go buy all the tech stocks in its basket, boosting them all a bit.
Passive vs Active ownership: In the U.S., passive funds now own a significant chunk of total stock market capitalisation. Passive doesn’t mean “no action”, it means following a rule (like track the index). But passive funds do trade, especially when indices rebalance or when money flows in/out.
Final Word
You don’t have to choose sides. Watch both. Institutions set the tone. Retail adds noise, and sometimes reveals early truths. Price reacts to both - retail become increasingly more important each year.
A good trader listens to the crowd, respects the elephants, and knows when to fade them both.
Common Downfalls in Equity Trading
In markets, pain is inevitable, but stupidity is optional.
Every blown-up account has a story. And if you trade long enough, you might have a few of your own. But there’s a difference between lessons and landmines; the former teach, the latter wipe you out.
This is the section that could save you more money than any stock tip ever will.
1. Buying Stories Instead of Businesses
You heard it’s “the next Tesla.” It’s got AI in the name. It’s up 40% this week. You’re in.
Narratives are so seductive and outright dangerous when unchallenged.
A stock with a great story can still be a terrible investment. Always zoom out: is this hype, or is this real? Has this business actually proven anything? Does the valuation reflect perfection in a market that rarely gives it?
Ask: What has to go right for this to make sense? And if your answer is “everything,” it’s probably not the one for you.
2. Chasing Green Candles
You watch a stock fly 20% in two days. You hesitate. It keeps going. FOMO kicks in. You buy the top. It retraces 10%, and you panic-sell.
Buying strength is not the same as chasing momentum blindly. One is tactical. The other is emotional. If a stock has run 80% in two weeks and you’re just now getting interested, stop and ask why. You’re most likely late.
The market punishes those who act out of envy. Let the move go. Wait for the next.
3. Turning Trades Into Investments
You wanted it for a few days, buut it dipped. You didn’t cut. Now you’re down 30% and telling yourself you’ve got long-term conviction.
Discipline is knowing what type of trade you’re in before you enter. If your thesis was invalidated and you’re still holding, you’re not being patient, you’re being stubborn.
Having an exit plan is vital.
4. Revenge Trading
You took a hit. You’re angry. You double your next position trying to make it back. You lose again. Now you’re on tilt.
Markets don’t care about your need to be even. Revenge trading is how small losses become career-threatening ones. Step away. Reset. Trade when you’re calm, not when you’re bleeding ego.
I wrote two educational posts on psychology this year that I have attached below.
5. Ignoring Position Sizing
“I really believed in it.” Great. But why was it 25% of your portfolio?
Sizing isn’t just risk management it’s emotional management. When a trade is too big, you just can’t think straight. You check the chart every five minutes. You struggle to sleep. That’s not edge, that’s fragility.
If you can’t sleep, you’re too big. If you size small and it works, you can always add. But if you’re oversized and wrong, you can’t think.
6. Misunderstanding Valuation
Just because it’s down 70% doesn’t mean it’s cheap. And just because it trades at 50x earnings doesn’t mean it’s expensive.
Context matters. Growth. Margin profile. Market conditions. Interest rates. Compare apples to apples, and don’t forget that the market often pays up for the future, not the now.
Valuation isn’t about numbers. it’s about expectations. Price is what you pay. Narrative is what you get.
7. Overtrading and Burnout
You’re in five trades within an hour of the trading day. You’ve checked your P&L 47 times. You’re not trading, you’re gambling. Sorry not sorry.
You don’t need to trade every day. Most gains come from waiting. The rest is noise. Save your energy for when it matters.
Boredom is not a valid reason to trade. I repeat, boredom is not a valid reason to trade.
8. Holding Losers, Selling Winners
It’s a classic: You cut your winner to lock in a gain and let the loser hang around because it’ll bounce.
You’ll be rewarded for patience on winners and discipline on losers. Flip your script. And as I said at the start of the post, let your winners run. Cut the ones that no longer justify your capital.
9. Listening to the Wrong People
Everyone’s an expert on social media. Most of them haven’t seen a full cycle or managed real risk. That influencer in Bali with 12 monitors? He’s probably broke.
Filter your inputs. Ask: Does this person have skin in the game? Do they talk risk as much as reward?
Use advice as data, not gospel. Then do your own work.
10. Forgetting This Is a Game of Probabilities
You followed your process. You managed risk. And you still lost. Welcome to trading.
A good process can have bad outcomes. But a bad process with a lucky outcome? That’s a trap, not a win.
Zoom out. Take notes. Review your trades like a pro athlete watching themselves back on a screen. The market will always humble you; the key is to let it refine you instead of wreck you.
No one avoids every mistake. You will chase, baghold and misread. But you don’t have to repeat them.
Mistakes are tuition and stupidity is taking the same class twice.
If you learn, adapt, and survive, you’ll be around long enough to win.
Tools & Resources
1. Charting & Price Action
TradingView (better charts than the terminal) Web-based, sleek, and ridiculously flexible. You can chart anything, from SPX to your favourite small-cap biotech, and overlay indicators like RSI, moving averages, VWAP, or custom scripts.
2. Fundamental Data & Valuation
Bloomberg - if you can afford it.
Koyfin -Think of it as a poor man’s Bloomberg. Clean visuals, macro overlays, valuation charts, earnings history, sector dashboards, all in one place.
Finviz - Use the screener to filter by fundamentals or technicals. Also handy for heatmaps.
3. Options & Flow Intelligence
SpotGamma - If you trade names with active options markets (think: Nvidia, Tesla, SPX), understanding gamma exposure is essential. SpotGamma breaks down how dealer hedging might affect intraday movement, especially around key expiry dates. It’s not gospel, but it helps explain why price sticks to a certain level.
TradeAlert - Non-stop option flow. Great for sniffing out unusual activity.
5. News & Sentiment
Twitter/X - Still a goldmine to fade + follow. Follow people who talk risk, not just reward. FinTwit has some brilliant minds. and some absolute grifters. Learn to tell the difference.
Bloomberg Terminal (if you have access/can afford it), king for global news flow, macro data, and so on. Overkill for most, but game-changing if you’re serious and can get on a desk with one.
6. Execution & Broker Platforms
Take the IBKR pill.
7. Books
I will do a post on this at some point. Happy to give book recs here and there via DM.
8. Education Resources
The tools don’t do the work for you, but they make it possible to do the work better.
Simplicity is underrated and precision is earned.
You don’t need 20 indicators, 5 news feeds, and 8 watchlists. Nor do you need to pick X broker because it has neater UI than Y.
Cheats, Shortcuts & Shit That Actually Helps
When options go nuts, stocks usually follow
Gap Up + No Fade = Buy Strength
Macro matters less... Until it doesn’t
Try not to open new positions a day before FOMC
The best trades work instantly
Build a Do Not Touch list
Your edge fades the moment you trade for dopamine instead of outcome
If you made it this far, thank you and well done.
There’s no shortage of trading content out there these days, and 90% of it is either sanitised for mass appeal or dressed up to sell you something. That wasn’t the goal here.
This series is written for the person sitting at their screen after getting stopped out for the third time this week… for the person wondering why when the market’s up 2% their portfolio isn’t… for the one who’s read the threads and books, bought the courses, taken the trades, and still feels like they’re missing something.
I’m not here to tell you this game is easy. It’s not. But it is learnable, if you’re willing to stay in the fight long enough, and honest enough, to keep refining. You don’t need to catch every move. You don’t need to win every trade. You just need to survive long enough for your process to do its job.
That’s the work. That’s the edge.
This is just Part 1. Zero to Stock Hero: Part 2 will drop soon. It’ll go deeper into setups, systems, positioning, more in-depth into different participants and the unteachable stuff most traders only learn through pain. If this first post helped at all, I promise the next one will go even further.
Now, go do less dumb stuff than you did last month.
Chat soon,
Fed
Part II
Anyone can have a good idea. Very few know how to survive it.
If you made it through Part 1, you should kind of get it now. You understand what actually moves stocks, not what should move them, but what does. You’ve seen how sentiment can make a 15 PE stock trade like it’s about to cure cancer, how pension fund rebalancing can trash perfectly good companies, and how the same ticker can ping-pong between meme stock, a macro hedge, and margin call fodder faster than you can check your P&L.
But that was the map, and this is the manual.
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There’s a world of difference between understanding how the market works and knowing how to operate inside it. A solid thesis isn’t the edge, execution is. The edge, if such a thing exists, lives somewhere between structure and restraint. That’s what this post is about.
I’ve seen great ideas lose money and mediocre ideas pay traders for years. The difference wasn’t the chart or the story. It was the sizing, the exit, the timing, the conviction. And, the person.
You want a higher Sharpe ratio? Learn to hold size when you’re right and take size down when you’re unsure. You want to stop sabotaging your own setups? Start by knowing what kind of setup it actually is. You want to survive long enough to get good? Then build the kind of strategy that lets you function after your worst losing streak.
This isn’t about indicators or some perfect strategy. It’s about adapting your execution to context. About knowing how to:
Identify asymmetric setups that make sense in your timeframe
Size and scale positions without losing your nerve
Exit cleanly when you’re right, wrong, or just tired
Use options like a professional… to define risk, enhance reward, or express a thesis
Protect capital without hedging yourself into oblivion
Manage psychology through systems
This post is long. And I guess it’s written for people who are sick of spinning in circles, for people who already know “buy low, sell high” but can’t seem to do it when it matters. For people who want to stop guessing and finally start operating.
You don’t need a terminal to become dangerous. You don’t need a $100m book to trade like a professional. But you do need discipline, clarity, and the humility to keep refining. The guys with a Sharpe above 2? They’re not geniuses, they’re systematic killers of bad habits. And I hope this post helps you get closer to becoming one.
Let’s begin.
Setups That Work
The best setups don’t scream. They whisper, and work.
Everyone wants the perfect setup. But let me ruin the illusion early: there is no such thing.
There are only high-probability conditions, matched with your timeframe, executed with consistency. That’s it. No indicator combo will save you. No secret pattern, no magic candle. Just structure, repetition, and edge. Let’s be blunt: most of what retail is taught about technical setups is noise. Pattern-matching without context. Buying breakouts with no understanding of what’s being unwound. Drawing lines on charts without grasping what’s underneath them.
That said, there are setups that repeat, not because the lines are magic, but because market participants are predictable in how they behave around pressure and imbalance.
I bucket the setups that work into three categories:
Narrative Setups
These are trades that align with a strong macro or thematic backdrop and a clean technical entry. They’re not just stories - they’re stories with teeth.
You’re not trading “the AI bubble.” You’re trading a strong name in a strong group, with flows, earnings, or secular tailwinds behind it, and a chart that just pulled back 12% into the 100-day and caught a bid. That’s a setup. That’s narrative with structure.
Example setup:
Sector narrative/theme accelerating (AI, semis, clean energy, defence)
Pessimistic positioning, earnings beat or strong institutional flows within last 1–2 weeks
Name reclaims a key level (50/100/200d MA) with volume
Narratives without structure = traps. Structure without narrative = no juice. You want both.
Event-Driven Setups (Catalyst Windows)
This is where the real edge lives for some/
You don’t need to predict earnings. You need to understand
The market is obsessed with expectations. That’s why sometimes a beat sells off, because the buy-side bar was already too high.
Great post-event setups usually include:
A clear earnings reaction (gap-and-hold / gap-and-fade)
Clean response to guidance
Volume surge with tight intraday movement
Follow-through on day 2 or 3 (post-earnings drift)
These are some of the best multi-day momentum trades out there, but most retail traders exit too early, or can’t size because the move’s already started. That’s the difference between “caught it” and compounding it.
Other catalysts worth watching:
FDA approvals (biotech gold mine)
M&A rumours/deal announcements
Product launches/investor days
Guidance raises from sector peers
Technical / Momentum Setups
This is where price action becomes process, not art or retail mythology.
Technical setups matter. But not because you drew a flag on a chart and called it conviction.
I use trendlines. But not in isolation. I care when a trendline coincides with:
Anchored VWAPs from prior catalysts (earnings, guidance, gap days)
Volume areas that absorbed selling during prior stress
Key Moving Averages
Dealer hedging zones / known gamma pivots
Where price has respected it multiple times on volume
In context, a trendline isn’t necessarily a signal. It’s a potential decision zone, where flow either confirms or rejects. It prompts the question: are sellers still in control, or has the tape shifted? Are passive bids starting to take the lead?
Here’s how I classify high-probability technical setups:
Risk Ignition: Multi-day coiling range after a directional impulse → sharp unwind of weak positioning = asymmetry.
Reclaims: Name undercuts prior low, flushes weak hands, then reclaims the level on volume. Your signal isn’t the low, it’s the acceptance above it.
Range expansion: Tight tape, then expansion into space, especially if supported by flows or macro backdrop.
Trend retest holds: Multi-week trendlines respected on a low-vol pullback into macro risk (CPI/FOMC/NFP), followed by a reclaim = risk-on signal.
What matters most is how the price trades at those levels. Not that it gets there, but what happens when it does.
I guess what I am trying to say is that strong hands buy structure and weak hands chase. Your job is to lean into those control zones, where you can define risk, size with intent, and scale into conviction when the market confirms.
Entry, Sizing & Scaling (More about this to come in my risk management post)
You don’t get paid for your ideas. You get paid for how you size them.
The market doesn’t care how compelling your thesis is if your sizing’s wrong. And it definitely doesn’t care if your entry’s random. In professional money management, edge isn’t just about being right, it’s about how you express the trade.
This section is about three intertwined pillars:
Entry: Where and why you initiate risk
Sizing: How much capital you allocate
Scaling: When you press and when you pare
Let’s break them down.
I. Entry Isn’t a Price, It’s a Process
The best entries are usually boring. Not the breakout, not the FOMO spike, nor the candle that made you gasp.
Professionals enter on acceptance and asymmetry:
Acceptance: Price finds footing. The bid holds. The market digests information and stays elevated. That’s your tell.
Asymmetry: The downside is defined. The upside is open. Your risk is mechanical, not emotional.
Checklist before pulling the trigger:
Can you define your invalidation? (Not just price but behaviour)
Is there liquidity at this level?
Catalyst proximity - Is there binary risk (earnings, macro print) in 24 hours?
Setup maturity - Are you early, in the meat, or late?
Conviction? I score 0-5
You’re not trying to snipe the exact bottom. You’re trying to enter where price confirms your thesis, and you can control risk as entry without a risk plan is just a bet with better font.
II. Sizing: Where 90% of Participants Blow Up
Let’s kill a myth: there is no such thing as a “conviction size” trade unless you’ve already proven the trade is working.
Institutional sizing is systematic, probabilistic, and adaptive:
Starter size = uncertainty premium
Add on confirmation = conviction earned
Let’s say your max size on a name is 5% of NAV:
Starter = 1% on range reclaim
Add = another 1-2% on volume expansion
Final 2% = only if macro/theme lines up and the tape accelerates
You scale into information, not hope.
III. Scaling
Professionals aren’t hoping their position works, they’re building into it.
You don’t need to go full size on Day 1 - that can depend on the vol regime:
You scale when volatility contracts
You press when volatility expands
Think like this:
Flat → Small → Working → Add
Full → Extended → Trim
Unclear → Don’t touch it
Most traders blow up because they scale into price instead of into information.
This game is about stacking edge. Entry gets you in the game. Sizing keeps you playing and scaling is how you get paid.
Every portfolio manager I respect has different setups. But they all size with respect. They all add based on confirmation. And none of them double down just because a red candle appeared.
Let’s get more tactical now. Next section, I’ll talk about execution: entries in illiquid names, how to use options as expression tools, and how to size volatility instead of price.
Execution and Expression
Because a good idea poorly expressed is just a future regret.
Execution is where most traders unconsciously leak edge. It’s not just about whether you’re right, it’s about how you get into the trade, how you size it, and how you express it, given the structure of the name and the environment around it.
I. Execution in Illiquid or Thin Names
In real-world trading, liquidity isn’t a detail - it’s a constraint. Especially for PMs running size.
You don’t just fire a 3% position into a low-ADV name. You work it.
Rules some would follow internally:
Liquidity filter: No more than 20–30% of a name’s 20-day ADV per day, and even that’s aggressive unless it’s a clean event-driven play
Time of day matters: Open and close = worst slippage. Midday is dead but useful for quiet adds
Use conditional orders: Don’t just sit on the bid. Step into momentum when the market confirms, especially after reclaim levels
Work the book: If you’re running size, stagger orders across levels or at VWAP not all-in at one price. Don’t be the liquidity…
If you’re running a small book, this might sound overkill. But the point remains: treat your execution like you’re managing a real book, even if it’s five figures. That habit will pay dividends later.
II. Use Options to Express Asymmetry - Not Lottery Tickets! (Though the odd Friday SPX 0DTE is ok)
Options aren’t magic. But they’re often the cleanest way to:
Express directional views around catalysts
Define risk in binary environments
Play volatility instead of price
If you’re trading around earnings, macro events, or headline risk, the question isn’t “should I buy the stock?” but “is long vol or short vol the better expression?”
Examples:
You want upside, but hate the tape? Call spreads give you defined exposure with limited capital bleed
Expect a sharp move, but unclear direction? Straddles or strangles (if priced reasonably) offer vol plays
Stock is extended but crowded? Look to sell premium (via spreads or calls) if you’re positioned for mean reversion
You’re not buying options because the chart looks spicy. You’re using them to control exposure, capital at risk, and payoff shape.
My personal filters for using options over equity:
Illiquid underlyings with clean option chains (and relatively tight spreads)
Macro or earnings risk within 3–5 days
Crowd positioning is clear, and I want to fade it without unlimited downside
I need more time for a narrative to work than I’m willing to bleed on stock
If you don’t know what your max loss is before entering the trade, you’re not trading options, you’re gambling with better marketing.
III. Size Volatility, Not Price Targets
Most retail sizing decisions look like this: “It’s a $50 stock. I’ll buy 100 shares. That’s $5,000. Sounds about right.”
That’s not sizing
You need to size relative to expected volatility, not nominal price. I size trades based on what the expected move is, and how much of that move we want to capture without being blown out on noise. (Sure, conviction too)
Simple rule of thumb: Your dollar risk = volatility-adjusted stop distance × position size.
If you’re risking 2% on a trade, and your stop is 5 ATRs wide (which is reasonable in high-vol names), you better size down accordingly.
Trading Nvidia on CPI day and trading Procter & Gamble in August are not the same sport. One moves 8% on headlines. The other barely flinches.
Practical tools:
Use implied moves from short-dated straddles into events
Build your stop zones around where structure breaks, not just a fixed percentage
Bottom line: Execution isn’t about getting in fast. It’s about getting in well - with clarity on risk, intent behind sizing, and a vehicle that matches the conditions you’re playing in.,
Managing the Trade (Stops, Profit-Taking, and Letting It Run)
I. Stops: Where the Thesis Fails, Not Where You Get Uncomfortable
A proper stop isn’t just a percentage or a moving average. It’s where your idea stops making sense.
You’re not placing stops to protect your ego. You’re placing them to control path risk, the risk that your trade plays out, but takes you out first.
Ask yourself before entering:
“Where would this trade be structurally invalid?”
“What would the best participants not let happen here?”
“If this fails, where does liquidity likely vacuum?”
Examples:
A breakout that can’t hold above a key prior high = structural fail
A reclaim that gets reversed on volume = no longer your trade
A low-volume drift down turns into high-volume rejection = time to go
And remember: If the stop feels too wide to size properly, cut size, not the stop.
II. Profit-Taking: Systematic, Not Emotional
Most people either:
Cut too early because they’re afraid to lose paper gains
Never sell because they need the market to validate them
Both kill compounding.
There’s no one-size-fits-all here, but here’s a framework:
Trim into strength when the trade becomes consensus or parabolic
Hold the core if the structure is still intact
Exit entirely if the reason for being in the trade is gone
Try thinking in decision zones, not targets. When your trade hits 1.5x–2x your initial risk, start managing, not exiting.
This is key - the goal isn’t to top-tick. The goal is to extract value while staying exposed to upside.
III. Letting It Run - Something I Mastered A Long Time Ago
This is what separates high sharpe traders from the ones grinding out mediocrity.
Letting a trade run is hard because:
You want to “book the win”
You fear the reversal
You didn’t size it properly to allow breathing room
Here’s what helps:
Trail structure, not price
Let volatility contract
Tune out the P&L
The best trades rarely feel euphoric. They feel more obvious after they’ve paid you.
Bottom line:
Stops should be mechanical, not emotional
Profit-taking should reduce exposure, not conviction
Letting winners run is where you actually get paid
Portfolio Construction and Cross-Position Flows
Most traders think in trades. Professionals think in books.
It’s not about your best idea. It’s about how that idea interacts with the other 10–20 positions you’re holding, the factor exposures it introduces, and what your book becomes under stress.
This section is about managing that higher layer: The structure of your risk, and the flows that connect it.
I. Net Exposure vs. Gross Exposure: Know Your True Risk
You have seen me recently talk how gross has come down but nets have barely budged higher… I get asked so much what it means so here.
Gross is total capital deployed - long + short. Net is directional exposure - long minus short.
Why does this matter?
Because in a low-vol regime, you can run 150% gross and feel nothing. But when the VIX spikes from 13 to 23 in 24 hours, gross suddenly becomes pain.
Example:
Long 80%
Short 30%
Net = +50%
Gross = 110%
You might think you’re “balanced.” But if those longs are all beta > 1.5 and the shorts are slow banks, your book is lying to you.
Net exposure tells you where your P&L will move. Gross exposure tells you how fast it can move.
II. Correlation Is the Real Risk
You’re not diversified if everything reacts to the same driver.
Most traders have portfolios that are 8 tech stocks with different tickers. Or 5 short names that are all high beta, high short interest, and get squeezed together on CPI day.
What looks like diversification becomes concentration under stress.
Ask yourself:
If a macro shock hits, how many of my names will move the same way?
How many trades are really just expressions of “tech up” or “rates down”?
Is my short book actually a hedge, or just another beta tail?
Sometimes the best hedge isn’t another short, it’s cash.
III. Sector Buckets and Flow Spillover
Flows rarely stop at one ticker.
If money floods into NVDA, it usually pulls AMD, AVGO, SMCI, and even TSM with it. If META breaks, the whole ad complex starts to wobble - think SNAP, PINS, even GOOG.
Build awareness of sector flow clusters - don’t overweight the same theme without intention.
It’s okay to cluster, if it’s your edge. But don’t do it by accident.
And remember this flows cascade. The leader moves first. The beta catches up later. That applies on the way up… and… on the way down.
IV. Conviction vs. Optionality vs. Risk Off
Every position in your book should serve a role:
Conviction Core: Highest weighting, full process alignment. You’ve done the work. You size it.
Tactical Trades: Lower weight, short horizon, structure-dependent.
Exploratory Probes: Tests, toe-dips, early-stage ideas.
Risk Off Hedges: Sometimes names, sometimes cash, sometimes puts. The only rule: they should actually help if things break.
If everything in your book is a 2–3% weight… You don’t have a strategy. You have a smoothie.
V. The Book Under Stress: Can You Function?
When the market turns, everything compresses. Liquidity, spreads, and brain function.
Ask yourself now, before that inevitable day comes:
What names have to go if the tape flips?
What positions earn the right to stay on?
Where am I secretly long the same factor across 4 tickers?
Portfolio construction is a dynamic exercise, not a spreadsheet exercise.
The best PMs don’t just manage ideas. They manage interaction. They know how their book breathes, in calm and in chaos.
Mistakes I Still See Professionals Make
Edge isn’t about avoiding mistakes. It’s about eliminating the repeatable ones.
You’d think that after running capital for years, the big errors would fade. They don’t. They just get more expensive.
Here’s what I still see, in PMs, traders, even desks with $100mm+ books.
I. Overconfidence in Thesis, Underconfidence in Price
They did the work, built the model, yet when price disagrees, they freeze.
But here’s the rule: the market doesn’t care what you think.
Price leads. The thesis confirms or it gets revised. If a trade isn’t acting the way it should, that is information. And you either respect it, or just become a bagholder with a better vocabulary.
II. Scaling When It Hurts, Trimming When It Works
The most common professional version of FOMO is this:
“I can’t believe I didn’t have enough size. It’s working. I’ll add more.”
But they add too late, just before the move stalls.
And then they trim when it finally starts paying… because the P&L feels big.
Scaling should reflect confirmation, not regret. Exiting should reflect conditions, not comfort.
III. Ignoring Liquidity on the Way Out
Anyone can build a position. Not everyone can unwind one cleanly.
I’ve seen seasoned PMs average into illiquid longs, only to discover they are the float. Then earnings disappoint, vol spikes, and their exit triggers a 5% air pocket.
Always model liquidity into your exit. Not just “what I want to do” but “what the market can absorb.”
IV. Overhedging Until They’re Just Paying Vega
The temptation to hedge everything is strong, especially in high-vol regimes.
But here’s the truth: most hedges are just long vol donations.
Buying SPX puts on a 3% net long book
Hedging tech with utilities that have 0.1 beta
Carrying 5% of capital in puts that decay 20% per month
Hedges are tools. Not pacifiers.
The best hedge is usually one of these (or a few):
Size down
Get flatter
Cut correlation
Add optionality when vol is mispriced, not because you’re nervous
V. Forgetting the Calendar
Pros still mismanage the obvious.
Holding crowded longs into CPI prints. Leaving size on into quad witching. Swinging for earnings while managing other people’s money.
“I didn’t realize NFP was tomorrow.” Guilty as charged.
Don’t let macro events surprise you. You don’t need to predict them. You just need to not be caught leaning the wrong way.
VI. Not Having a Process for Exits
Even good traders still do this:
Have a beautiful entry
Manage the position well
Then puke it out the moment vol spikes
They had a plan for risk, but none for reward.
If you don’t define exit zones, you will sell at the worst moments. Not because you’re dumb, but because your brain’s built for survival, not discipline.
VII. Taking Breaks Too Late
The best PMs know when to pull themselves off the field.
After 3–4 red trades in a row? Reduce risk, trade lighter or even just step back and watch.
But so many professionals wait until the drawdown is painful. Until their confidence is low, and decision-making is reactive.
Reset before the damage compounds and not after.
Bottom line:
Being a pro doesn’t mean perfection. It means building a system that keeps you from compounding small mistakes into catastrophic ones.
When your process has fewer leaks than theirs, you don’t need better ideas. You just need to survive longer and let the numbers do the rest.
The Mental Game
At some point, everyone involved with markets figures out the truth which is that your biggest risk isn’t the market. It’s you on a bad day, with size on.
Edge can be destroyed in an hour of ego. Confidence can be shattered in a week of poor execution. And no backtest survives the psychological war that begins the moment you’re in a drawdown.
I have already written a post on Drawdown Psychology.
I. Tilt Doesn’t Start With Rage - It Starts With Subtle Slippage
Tilt isn’t always dramatic.
It often starts small:
You skip a mental checklist
You add size on a whim
You trade something “just to stay active”
These are not execution errors, they’re emotional leakage.
The pros that last are the ones who catch themselves early. They see the change in tone, the impulse to “make something happen,” and they know that’s not flow… that’s ego.
II. The Slippery Slope of One Good Trade Gone Wrong
Everyone has had it… You get a good setup. It starts to work. You add.
Then a headline hits or your read just isn’t right.
You give it room. Then you give it more. Then suddenly, your “best trade of the month” is your worst drawdown of the quarter.
This isn’t about stops, it’s about identity drift.
Good traders lose money. But they don’t lose their process.
III. Anchoring to P&L is the Death Spiral
Your process doesn’t get better when your P&L is up. And it doesn’t stop working just because your screen is red.
But if you anchor your decision-making to your daily mark, you start defending past choices instead of adapting to what’s in front of you.
The tape owes you nothing. And it doesn’t care how well you traded yesterday.
Detach and review at the end of the day. But don’t trade to repair a number. Trade to execute your strategy.
IV. Identity: You Are Not Your P&L
This is the one most professionals learn too late:
If your self-worth is tied to your performance, your process will suffer every time your P&L does.
The best traders I know are detached. Not cold, just centred. They love the game. But they don’t need the market to validate them.
Your job is not to win today. Your job is to be sharp enough to win over time.
V. Resets Are a Skill
Know your red flags:
You’re trading bigger after a loss
You’re justifying size with “it’ll bounce”
You’re changing your stop because you “believe”
When that happens, reset:
Cut size
Cut gross
Take 24 hours
Review without judgment
If you wait until you’re in a tailspin, it’s already too late.
VI. No System Survives Without Psychological Maintenance
Backtests don’t account for:
Being tired
Fighting with your partner
Being down 8% YTD
Watching peers talk about monster trades
Feeling like you’re missing everything
All of that is real. And none of it shows up in a Sharpe ratio.
The pros who last aren’t always smarter. They’re just more consistent under stress. They have rules for themselves, not just their trades.
Final thought:
Markets will test your process. But more than that, they’ll test who you are as a person. If you don’t have a psychological risk framework, you don’t have a complete strategy.
Keep your edge sharp and your mind sharper.
Volatility Environment Playbook
Volatility isn’t noise, it’s the regime, and your strategy should flex to meet it.
Most retail traders treat a low-vol melt-up the same as a high-vol flush. Churn.
Low Volatility Environments (VIX < 15)
Setups take longer to develop
Breakouts grind
False moves are more common, and range-bound price action frustrates trend followers.
Position sizing can increase slightly due to narrower expected ranges.
Options premium is cheaper, so long vol can make sense if you expect regime change.
Best tactics:
Trade less
Hold longer
Use wider stops in percentage, but tighter in volatility-adjusted terms.
Be patient with scaling, there’s no rush, trends develop slowly.
Moderate Volatility (VIX 15–22)
This is where most of the best risk-reward lives.
Price respects structure
Catalysts matter, but don’t fully dominate.
Liquidity is sufficient, and spreads are manageable.
Best tactics:
This is business as usual for most discretionary traders.
Focus on clean setups with structure and narrative.
Sizing should align with your base framework.
High Volatility (VIX > 23+)
Now it’s a different game.
Liquidity thins out, spreads widen and slippage spikes.
Correlations go to 1, diversification vanishes.
Strong names sell off anyway and everything is beta.
Best tactics:
Cut gross, cut net
Trade smaller.
Intraday trading edges > swing.
If you must hold overnight, consider hedging with index puts or vol products.
Volatility isn’t to be feared, it’s to be respected. Some of the best trades come out of chaos.
Building Your Playbook
If you want to get serious then trade like you’re running a real book.
Your edge isn’t just in the setup, it’s in the process around it.
Here’s how to systematise your discretionary trading into something scalable:
I. Categorise Your Setups
You don’t need 20. You need 3-5 that you understand inside out.
Narrative-driven trend
Event-driven volatility
Mean reversion
Positioning setups
Give each one a name, a checklist, and sizing rules.
II. Assign Playbooks by Volatility Regime
Low vol = longer holds, tighter risk. High vol = shorter duration, faster exits.
Each setup should have notes on:
Entry criteria
Risk model
Vol-adjusted sizing
Conditions where it fails
III. Track With Intent
Start a basic trade journal that tracks:
Setup type
Conviction score
Entry reason
Outcome vs. expectation
Patterns will emerge. You’ll see what you’re actually good at.
IV. Run a Real Book, Even With Small Capital
Start thinking like a PM:
Know your gross and net exposure
Monitor sector exposure
Log rolling beta
Track cash percentage
Scenario Analysis
If you treat your $25k book like it’s $25m, you’ll build the habits now that scale later.
V. Keep Refining
Your playbook isn’t static. Prune the dead setups and double down on what works.
This is how you build edge: Discover what pays you, size it appropriately and cut what bleeds you. A proven playbook turns market noise into actionable intelligence. It’s what makes you dangerous instead of desperate.
You’ll never be done building; your edge will always be in refinement. Do less dumb stuff, more consistently.
Fed
PS - If you found value here, smash the like and restack. It helps others find this stuff instead of the usual online guru nonsense.
Part III
If you made it through Parts 1 and 2, you’ve built the foundation. You understand what moves markets and how to express your ideas through proper execution. You know that sentiment drives short-term price action, that flows matter more than fundamentals most days, and that your edge lies somewhere between structure and discipline. But knowing what to do and consistently doing it are different games entirely.
Part 3 is about the gap between theory and practice. It’s about what happens after you’ve learned the basics, built a process, and started making money. It’s about the plateau that catches every trader, the psychological traps that destroy careers, and the advanced techniques that separate professionals from permanent amateurs.
This isn’t about finding better setups or secret indicators. It’s about evolution. About taking everything you’ve learned and making it antifragile. This manual is about building a trading approach that gets stronger during market chaos instead of falling apart.
I’ve watched too much talent plateau at mediocrity because they confused activity with progress. They had all the right concepts, but just couldn’t scale them. They knew how to find good trades but couldn’t squeeze maximum value from their best ideas. They understood risk management in theory but couldn’t adapt it to changing regimes.
The difference between a trader who makes steady money and one who compounds wealth over decades isn’t intelligence. It’s systems. It’s the ability to recognise when your edge is decaying and adapt before it kills you. It’s knowing when to press your winners and when gross exposure becomes toxic.
This write-up covers the advanced concepts that most retail traders never encounter
How to break through performance plateaus that trap most traders
The conviction scoring systems professionals use to size their best ideas
Risk management techniques that adapt to regime changes
How to spot when your edge is decaying and what to do about it
Portfolio construction that thrives in chaos
The mechanics of how systematic funds move markets
What it really takes to survive and compound over decades
You don’t need a Bloomberg terminal or a hundred-million-dollar portfolio to implement these concepts. But you do need the humility to admit that everything you think you know might need upgrading. The traders who survive and thrive are the ones who never stop evolving.
If you’re ready to move beyond the basics and start thinking like a professional, this is where we begin.
Why Most Traders Plateau
Every trader knows the story, you grind to achieve consistent profits, then suddenly hit a wall. The equity curve flatlines or even dips despite continued effort. This glass ceiling often appears after your first stretch of success. Signs your process is stagnating include a lack of new highs in account equity, repeating the same mistakes, or generally just feeling bored by a strategy that once excited you. Often, traders plateau due to feedback blindness and habit ruts, tweaking nothing or everything without structured feedback. Emotional decision-making and sticking to the same tactics while expecting different results are common culprits. One temptation at this stage is to simply trade more, but more trades does not equal more growth. In fact, overtrading usually hurts performance. A famous study of individual investors found that the most active traders significantly underperformed the least active by 5% to 10% per year after costs. The hyperactive households earned sharpe ratios half that of low turnover peers. Why? Frequent trading incurs fees, spreads, and overconfidence errors, all of which erode returns. As Investopedia bluntly puts it, “overtrading can occur for many reasons, but they all have the same outcome: poor performance”. In short, doing more of the same is not the answer when growth stalls.
Breaking through a plateau means changing something fundamental. You need honest feedback from someone who knows what they’re doing. Find a mentor, join some kind of trading community, get your trades reviewed by people who’ve been there. More importantly, stop obsessing over daily P&L and start grading yourself on execution. Did you follow your rules? Did you size properly? Did you exit where you planned? The plateau is usually in your head anyway - you’re scared to size up, scared to try something new, or you’ve gotten too comfortable with mediocrity. Pushing beyond it might involve deliberately trading outside your comfort zone in practice sessions, experimenting with new tactics in simulation to expand your skills, or taking time off to reset perspective. It’s critical to distinguish whether stagnation is caused by you or the market. If your once profitable setup is now failing across the board, the market regime may have shifted and your edge could be decaying (more on that later). Conversely, if others trading a similar strategy still succeed, the issue might lie in your execution (e.g. hesitating on entries, exiting winners too early, etc). In practice, it’s often a mix of both. The key is to diagnose honestly, review a large sample of recent trades to see if setups still have positive expectancy and if you’re following them faithfully. If the edge is intact but your discipline is wavering, focus on repairing your process (simplify rules, automate exits, etc). If the edge itself seems gone, it’s time to innovate. Above all, avoid the trap of plateau frustration: churning out more trades in the hope of breaking the slump. As the saying goes, “there are old traders and bold traders, but no old bold traders”. Surviving and advancing in markets means adapting, not putting your foot on the gas. The next sections will dive deeper into specific ways to evolve your strategy and operations once you recognise that you’ve hit a glass ceiling.
Squeezing More from Your Best Ideas
When you’ve identified a high conviction trade idea, how you manage it often determines whether you achieve ordinary or exceptional returns. Top traders learn to press their winners at the right moments and harvest profits when the odds shift. Knowing when to press vs when to harvest is as much art as science. Most traders sell their winners way too early because they’re terrified of giving back gains. You end up with a string of 10-20% wins while missing the moves that could actually change your portfolio size. But holding blindly is just as stupid and turns winners into losers. The skill is knowing when to press and when to take money off the table. Press when everything is confirming your thesis. Harvest when the signals start flashing warning signs or you’ve hit your target.
One approach is implementing a conviction scoring system for ideas, like I do. For example, you might score trade setups on a 0 to 5 scale based on factors like technical pattern quality, catalyst strength, and confidence in the narrative. Such scores can be tied to position sizing - higher conviction, larger stake. The key is to incorporate probabilistic thinking. A score of 5 might imply you believe the trade has, say, an 80% chance of success, whereas a 2 might be around 60%. Some professional investors do this by scoring multiple dimensions (e.g. Moat=3, Management=2, Trend=2 for a stock) to arrive at an average conviction. They then only invest if the average clears a threshold (say 2+ out of 3) and size positions proportionally to that score. Converting qualitative judgements into quantitative conviction scores helps remove bias and ensures your big bets are reserved for your best ideas. For a trader, a 5/5 setup might be one where multiple independent signals align (narrative, price action, positioning, fundamentals, etc). In those cases, you allocate more capital or take an aggressive position, whereas a mediocre setup gets a smaller size or a pass.
Crucially, scale with confirmation, not hope. This means you add to a position only after the market proves you right, not when it’s going against you. The world’s best money managers live by this rule. Many of you will know the saying - “Losers average losers.” When a position is losing, the market is telling you that your thesis timing (or premise) is wrong. Adding more out of hope is throwing good money after bad. Instead, cut losers quickly. Save that capital for when things do go right because that’s when you pyramid up. For example, say you buy a stock on an initial breakout; it then consolidates and breaks to new highs. That’s an opportunity to press and increase the position since your idea is proving itself. By contrast, if it breaks down, you stop out rather than double down. Pressing winners means you increase exposure to a proven correct position without increasing risk to original capital, often by using open profits as a buffer. This strategy demands planning and discipline (e.g. adding only at specified technical levels or after certain fundamental news).
To visualise the anatomy of a 3x+ trade, consider an example. A stock at $50 is breaking out of a multi-year base on a game-changing development (say, an FDA drug approval). Your analysis indicates a potential for it to triple (to $150+) over the next year if the drug succeeds commercially. Rather than go “all in” at $50, you might take an initial position. As the stock moves to $60 on strong earnings and further institutional buying (evidence of follow-through), you add. It runs to $75, has a healthy pullback to around $65 (higher low), then breaks $75… you add again, now with even more conviction. By the time it reaches $100+, you have a sizable position largely built on house money (profits from earlier entries). Throughout, you trail stop losses to protect against a reversal. This way, if the trend indeed produces a 3x gain (as, for instance, Nvidia’s stock did, rising ~240% in 2023 amid the AI boom), you fully capitalise. I see this with my subscribers, they catch a great idea at $50 and sell at $60 or $70 for a quick +20%, only to watch it go to $150 without them.
The difference in a multi-bagger trade is conviction and trade management, you let profits run and even press the trade as it works, while managing downside with stops and scaling out gradually as the price approaches your valuation estimate or shows exhaustion. To decide when to harvest profits, have clear criteria. It could be a trailing stop (eg exit if the price closes below the 50-day MA, which often can indicate a trend break). It could be valuation-based (if your thesis had a price target and it’s reached, take some off). Or it could be event based (exit after a catalyst event passes, like earnings or product launch). Some traders peel off portions into strength… for example - sell one third after a 100% gain, another third at 200%, etc, to lock in gains while letting the remainder run. The goal is to avoid round tripping a big winner into a loser. The trend is your friend… until it’s not. Pay attention to late-stage signals: climactic volume spikes, parabolic price acceleration, or news euphoria can hint that a trend is peaking. That’s when harvesting makes sense.
The bottom line: get more from your best trades by sizing them properly and managing them like a professional. Build a system where your position size reflects how confident you actually are in the trade. When you’re in, add to winners that are proving you right and cut losers that are proving you wrong. Most traders do the opposite and wonder why they can’t make money. This asymmetric approach (pushing the pedal on high probability/high reward situations and easing off when risk increases) is what turns a few good trades into career-making returns. Believe it or not, you only need one good trade to make a year (in some cases, a career).
Gross Exposure: The Double Edged Sword
Most traders think of each trade in isolation, but professionals manage portfolio risk holistically. Managing risk like you mean it entails treating risk management as a core system, not an afterthought. The first element is volatility targeting at the portfolio level. Instead of letting your overall account volatility drift up and down with the market’s mood, you adjust positions to keep total risk in a steady range. For example, a trader might target around 0.5% daily volatility on their portfolio. In quiet markets, this might mean using leverage or larger positions (because each position is less volatile). In volatile regimes, it means holding more cash or smaller positions to avoid outsized swings. By dynamically scaling exposure, volatility targeting aims to stabilise returns and prevent nasty surprises. It’s a common practice among funds and CTAs: if market vol spikes, they de-risk to bring portfolio vol back to target; if vol is very low, they might lever up slightly to reach the target. This discipline enforces buying low-risk environments, selling high-risk environments, which tends to reduce drawdowns. It is a well known fact that volatility managed portfolios often realise better risk-adjusted returns than static ones. The 2020 pandemic crash dramatically illustrated this, funds that cut exposure as the VIX spiked fared far better than those that rode their full exposure down.
Hand in hand with vol targeting is managing your gross vs net exposure.
Gross exposure is the sum of all your long and short positions (absolute exposure), while net exposure is longs minus shorts.
A portfolio can be 200% gross (leveraged) but market neutral (0% net), or 50% gross but fully directional (50% net long if no shorts). Adjusting these based on the market regime is key. In stable, trending periods with good liquidity, a higher gross exposure can be used to capitalise on many opportunities. Many hedge funds will run, say, 200% gross exposure in benign markets like now, meaning lots of positions (long and short) to capture idiosyncratic alpha, and perhaps a moderate net long bias to ride an uptrend. But when volatility spikes and correlations converge, high gross can become napalm. In stressed markets, every position starts moving together (longs and shorts both fall if there’s a liquidity crunch), and leverage can implode a portfolio. That’s why in high vol regimes, seasoned players will slash gross exposure (fewer positions, lower leverage) and often cut net exposure to reduce directional risk. For instance, if a fund was 120% long / 20% short (net 100% long) in a bull market, they might dial back to 50% long / 20% short (net 30%) when the market environment turns uncertain. Reducing gross limits the impact of violent swings, and trimming net (especially long bias) avoids large directional drawdowns.
A vivid example of gross exposure turning toxic was the Long Term Capital Management (LTCM) crisis. LTCM ran enormous gross leverage (~25x equity) by arbitraging bonds globally. In calm times, this yielded steady profits. But in 1998, volatility spiked and liquidity vanished: their highly leveraged bets all went south together. With around $5B capital, LTCM controlled over $100B in assets (and $1+ trillion in derivatives). When Russia defaulted and markets convulsed, LTCM’s positions lost so much so fast that they couldn’t cut them (no buyers) and faced total collapse. The fund lost $4.6B in months and had to be bailed out to prevent wider contagion. The lesson from this: liquidity fades + vol spikes = death spiral for high gross books. What worked in stable times became lethal in turmoil. Nowadays, funds try to prevent this by routine stress tests and gross reductions before a full-blown crisis.
Remember: gross is oxygen in low vol, napalm in high vol. We saw this again during Volmageddon in February 2018 when inverse volatility products imploded. Those products had massive hidden gross exposure to short volatility. It worked beautifully until VIX futures spiked around 100% in a single day. XIV collapsed 96% overnight and went bust, vaporising $2 billion in assets. What was steady income became an extinction event.
For instance, many risk managers will ask: “What happens if volatility doubles overnight? If all my positions fall 10% together?” If the answer is “I lose 50%+ of my capital,” the portfolio is overleveraged for a worst-case scenario. Stress test your exposure before the market does it for you. Run scenarios of sharp moves: if S&P futures lock down 5% overnight, or if your top 5 positions all gap against you, where do you stand? If the outcome is unacceptable, cut risk proactively. Good risk managers often carry hedges or keep dry powder for such scenarios.
Another advanced tool is monitoring rolling correlations to spot hidden exposure. It’s easy to think you’re diversified because you have 10 different trades on, but if those positions are actually highly correlated (say, all tech/growth bets in disguise), your true risk is one big bet. Calculating rolling 30-day or 90-day correlations between your positions (or between each position and the overall market) will reveal if you’re secretly concentrated. For example, you might be long semiconductors, long Nasdaq, and short VIX: on the surface, three different trades, but all three will tank if a growth/tech selloff hits (and likely at the same time). High correlation equals amplified risk. Aim for a portfolio where not everything moves together. If you find that many of your trades are in the same sector, theme, or factor, you either need to hedge that common exposure or diversify into uncorrelated strategies. Hidden correlations are a risk that undermines diversification. Tools like correlation matrices or factor exposure analysis can help. Many professionals use a risk factor view - instead of seeing 10 positions, they see, for example, “we have a big China exposure across these 4 trades, or a big long duration exposure across these 3 trades,” etc. That lets them size or hedge accordingly (e.g. if you’re inadvertently overweight one theme, lighten up or take an offsetting position).
In practice, institutional portfolio managers think in terms of “books” of risk, not individual trades. They might allocate risk to a book (e.g. a tech book, a macro book, an arbitrage book), each with multiple positions, and ensure no single book or factor can sink the whole ship. They constantly ask themselves - where are we concentrated? What scenarios hurt us most? Then they manage gross and net exposures of those books. They view losses and gains at the portfolio level, sometimes cutting a perfectly good individual trade because it adds correlation risk or gross exposure that the portfolio can’t afford at that time. This is a big picture risk mindset. Adopting this approach as an individual trader means regularly aggregating your total exposures and imagining the worst-case day. If that scenario is beyond your risk tolerance, you must dial things down. By targeting volatility, adjusting gross/net by regime, and avoiding secret correlations, you effectively bulletproof your process. No one can predict when the next crisis or spike will come. But if you run your risk deliberately (as if you’re your own head of risk), you won’t be caught overextended. When conditions are favourable, you can lean in (higher gross, with a net long tilt); when storms gather, you’ll already be trimmed down to survive. This dynamic approach to risk is what separates institutional-level trading from mere pyjama speculation.
There’s also a psychological component; gross exposure hurts your sleep in high vol environments. Even if you technically survive, being overexposed in wild markets rattles you enough to make terrible decisions. Trading at a size that allows you to stay rational is crucial.
The best defence is not to be over grossed by the time crisis hits. Prudent traders de gross early at signs of trouble. If you wait until the VIX is at 80 and credit spreads are blowing out, it’s too late, you’re selling into a vacuum.
Have leading indicators for when to trim exposure - volatility indices, liquidity metrics (like the MOVE index for bonds), or simple rules like “if my portfolio drops >5% from a peak, reduce all positions by half.”
Many quant funds have automatic triggers - if daily portfolio volatility goes beyond X, they scale down positions across the board. This discipline enforces buying low-risk environments, selling high-risk environments, which tends to reduce drawdowns.
Run scenarios before the market does it for you. Overlay the 2008 crisis or 2020 crash onto your current positions, assume each asset moves as it did then, how much would you lose? If the answer is “I lose 50%+ of my capital,” the portfolio is overleveraged for a worst-case scenario.
Sometimes stress tests reveal surprising concentrations. Maybe you’d survive everything except if one particular spread trade blew out. That’s valuable insight to hedge or lighten that specific risk..
If you cut gross and risk pre-emptively, you’ll navigate turmoil more calmly and even be in a position to capitalise on opportunities instead of being carried out.
Gross exposure is a double-edged sword. Use it when appropriate, but know when to sheath it. When volatility is low and stable, higher gross can enhance returns - it’s like adding sail in gentle winds. But when the storm comes, you must reef those sails quickly, or risk capsizing.
The best traders are situationally aggressive, pressing bets in favourable conditions and aggressively reducing exposure when clouds gather. Do that, and you won’t become another casualty of the leverage trap, selling at the worst possible time or begging for a bailout. Live to play another day.
Edge Decay
No trading edge lasts forever. Markets are adaptive, and once a profitable strategy becomes widely known or the market regime shifts, the edge can erode or decay. The challenge for traders is determining whether a drawdown is due to normal variance or your edge truly decaying, essentially, “is it me, or the market?”. Here’s how to tell and what to do. First, recognise that edge decay is inevitable in some form. Almost all trading strategies stop working sooner or later, they have to evolve. Markets are a zero-sum game; any inefficiency will attract arbitrageurs and competition. For example, if a certain pattern reliably yields profits, you can bet high-frequency algorithms will eventually exploit and neutralise it. Inefficiencies get arbitraged away, sometimes gradually, sometimes suddenly. So a key skill is detecting when your best setup stops working.
How to know if it’s you vs the market? Start by examining if you have been executing your strategy with discipline. If not (you’ve deviated from rules, gotten emotional), poor performance may be self inflicted and you need fixing, not the setup. However, if you’ve traded it cleanly and still see a persistent drop in win rate or profit factor, the edge itself may be fading. Look for abnormalities - say your setup historically won 60% of the time, but in the last 30 instances, it’s only 40%. Is that within statistical variance or a structural break? If it’s a significant deviation that hasn’t reverted, that’s a red flag. Also, gather evidence beyond your own trading. Are other traders who use this strategy also struggling (if you have contacts or see chatter in forums)? Is market behaviour fundamentally different now (e.g. was a strategy that thrived in a trending, low vol market now floundering in a choppy, high vol regime)? For instance, many trend following systems had negative performance during certain range-bound years, not necessarily because the strategy “broke,” but the market regime was hostile to trend following. In that case, the edge didn’t vanish; it was just dormant until trends returned.
If you conclude the market has changed, then decide whether to repair it, rotate it, or retire it. These are the three R’s when an edge weakens…
Repair it if the strategy can be tweaked to revive its edge? Maybe tighten the entry criteria, add a filter (only take the setup in a strong overall market trend or with rising volume), or adjust risk management. For example, if a breakout pattern stops working because false breakouts increase, you might add a rule to require confirmation (like waiting for a retest of the breakout level). Or if a mean reversion trade stopped working because the volatility regime changed, perhaps incorporating a volatility filter (trade only when VIX is above/below a threshold) could help. Be careful as “curve fitting” a fix can lead to temporary improvement that doesn’t hold in real trading. The best repairs address a known cause. If you can identify why the edge decayed (say HFT bots now exploit it, or a fundamental change in market structure), you can sometimes adapt. Otherwise, you’re just guessing with tweaks.
Rotate it as sometimes a strategy is sound, but current market conditions don’t favour it. The smart move is to rotate it out of active use and shift to other strategies that are working now. Perhaps your momentum strategy is struggling, but a harvesting vol selling 0dtes is killing it. Keep the former on the bench and monitor. Many successful traders maintain several strategies and dynamically allocate capital to the ones showing strength. If you have only one setup, this is harder, which is why developing multiple trading approaches over time is valuable (trend following, mean reversion, arbitrage, options strategies, etc, so you’re not a one-trick pony vulnerable to regime shifts).
Retire it if evidence is clear that an edge is gone for good, it may be time to put it to pasture. This is tough as we grow attached to our profitable patterns. But clinging to a broken setup is deadly; it’s like a pro athlete not accepting retirement and tarnishing their legacy with poor performance (think Ronaldo). How do you know it’s truly time to retire it? If the logic of the setup no longer makes sense in the current market structure, or if it’s been unprofitable for a statistically significant period/trade count despite your best efforts to adapt, it’s likely done. For example, a strategy exploiting a specific regulatory arbitrage would need retirement if a rule change closes that loophole. Or say you had an edge trading a particular stock or sector which is now gone (maybe that stock got acquired, or that sector’s volatility died), recognise the end. I don’t think that retiring a strategy is necessarily failure, I’d say it’s evolution.
The main lesson is to stay vigilant and humble. Always ask yourself - If my edge disappeared, what would I do? Have an answer before it happens. Maintain a trading journal including notes on market context for wins and losse, this can help identify if losses are stemming from execution errors (you deviated from plan) or strategy issues (you followed the plan and still lost, repeatedly). If it’s the latter, don’t ignore the signs. Moreover, diversify. I think that as a trader matures, they should accumulate multiple small edges rather than one big one. This way, losing one edge isn’t career-ending. It’s like a business with multiple product lines: if one product goes obsolete, the business adapts. Finally, be ready to innovate continuously. Keep learning new techniques, markets, or styles.
In conclusion, edge decay is not an if, but when. Don’t take it personally when a beloved setup stops printing money. Recognise it, verify it, and then take action: repair if possible, rotate to thriving strategies, or retire and replace it. This ensures you evolve with the market, rather than becoming a relic of a bygone market phase. Adaptation is the only permanent edge.
As It’s a Hot Topic… What CTAs Actually Do
“CTA” (Commodity Trading Advisor) is shorthand for professional systematic trend followers: the funds that trade futures across asset classes using algorithms. They are often mystified in retail trading circles, but what they do is quite straightforward at its core. Understanding how systematic trend followers work can not only demystify their role but also inform your own trading on timing and market mechanics.
At heart, CTAs deploy trend plus volatility filter strategies. They attempt to capture medium term trends in markets (could be equities, bonds, commodities, FX) while controlling risk via volatility targeting. A basic CTA system might look at a market’s price over several look-back periods (1 month, 3 months, 1 year) and determine if the trend is up or down. For example, if the average risk-adjusted return over the past 3 and 6 months is positive, go long; if negative, go short. This is often done with moving averages, breakouts, or momentum indicators: all variations of detecting persistent price moves. But unlike a naive trend strategy, CTAs always incorporate volatility adjustments and risk management. They size positions such that each trade has equal risk contribution (risk parity) and scale positions down when volatility is high. For instance, if S&P futures become very volatile, the CTA will hold a smaller number of contracts to keep its risk in line. Conversely, when volatility is low, they can increase position size to maintain target risk. This results in a fairly smooth risk profile: CTAs aim for a consistent portfolio volatility (often around 10 to 15% annualised).
A hallmark of CTAs is that price beats narrative for them. They couldn’t care less why oil is going up or the dollar is falling; if the price is trending, they’re in. They are purely systematic, removing human bias. So while on CNBC, you hear debates about Fed policy or valuations, CTAs just follow the price. This sometimes puts them on the opposite side of conventional wisdom, like a CTA might be short equities because the trend flipped down, even as some talk about “great buying opportunities.” This dispassionate approach has advantages: CTAs don’t get married to a story; they’ll flip long to short on a dime if the trend warrants. Price momentum dominates their decision-making, so fundamentals or news only matter as far as they affect price trends. This is why you’ll see them pile into, say, a rallying index even if pundits call it overvalued: the narrative is irrelevant; price is the only truth for them.
One important effect, CTA flows can compound market moves. Since they all use variations of trend following, they often end up trading in the same direction around the same time. For example, imagine a sustained rally in gold, as gold breaks multi month highs like it is now, more and more CTA models generate buy signals. The CTAs start buying gold futures, adding a mechanical bid to the market. Their buying can extend the rally beyond what fundamentals alone might justify (at least in the short term). Similarly, in a downturn, CTAs will systematically sell into weakness (closing longs, going short), contributing mechanical offer pressure that can accelerate a dip. In essence, trend followers are trend amplifiers even though they are small. We saw this in late 2021–2022: as inflation soared and bonds and stocks both fell in a new regime, CTAs piled into short bond futures and short equity index positions (since trends were down). Their selling contributed to the relentless slide until a big reversal rally in Q4 2022 forced them to start covering in some fashion.
What does this mean for an individual trader? It means CTA positioning can affect timing, entries, and exits. If you know that CTAs are extremely long a market, it implies a lot of trend following money is already in. If that trend stalls, the risk is that CTAs will start flipping, creating a headwind. Conversely, if CTAs are heavily short and you see signs of a reversal, once the trend criteria flip, they’ll be forced to buy back shorts, adding fuel to the rebound. In practical terms, many (including myself) monitor estimates of CTA positioning (lots of banks and research firms publish models tracking CTA exposures). For example, you might read that CTAs are max long crude oil which could caution you that the long trade is crowded by systematic players, so any bearish catalyst could see a swift drop as they all sell. Or if CTAs are near flipping from long to short in equities (say the S&P 500 is flirting with a moving average trigger), you know a breach might trigger an extra wave of selling.
Another thing CTAs do is volatility filtering: if markets get too choppy, many models reduce position size or avoid signals to filter out whipsaws. That means in extremely volatile periods, CTAs might actually lighten up, which sometimes can dampen further volatility. But once a new trend asserts, they’ll scale back in.
Let’s break down a hypothetical CTA trading day - they track a wide array of markets (dozens of futures: stock indices, bond futures, FX pairs, metals, energy, agriculturals). Their algorithm computes signals, often end of day. Suppose today the 3 month and 6 month trend for EUR/USD turned from positive to negative: the CTA system flips from long euros to short euros. So at the market close (or open of next day), they’ll sell a bunch of EUR/USD futures to establish the short. Similarly, imagine the S&P 500 fell enough to hit a trailing stop: they reduce their long position or go flat. All these moves are fairly predictable by their rules. Sometimes you can literally see CTA activity in markets, often near the close or specific times, as they rebalance to maintain volatility targets (if market volatility jumped today, they might cut position sizes across assets to keep risk on target). This target vol mechanism means that after a big move day, CTAs may transact more. If S&P had a huge range day up, CTAs might buy more (trend confirmation) but also perhaps trim size a bit if volatility is now higher: it’s nuanced.
Why this matters for timing - knowing CTAs chase trends, a breakout or breakdown can see follow-through due to their entries. It might justify holding a breakout trade longer because you expect CTA money to come in behind you. Conversely, be wary of false breakouts that snap back, those can nail CTAs in whipsaws, causing them to exit quickly and reverse flows. A classic scenario… a market breaks a major level and CTAs pile in, but then it reverses sharply, the CTAs will exit, exacerbating the reversal. If you can spot that reversal early, you’re essentially front-running an avalanche of CTA exits.
Entry and exit considerations - If you prefer to trade counter trend, it’s usually wise to wait for evidence that momentum is fading and perhaps that CTAs have mostly finished their buying or selling. Stepping in front of a strong trend too early is painful because CTAs (and other trend followers) will keep pushing it. But once the trend’s over extension is clear and technical momentum wanes, betting on a reversal is extra juicy, knowing the trend following crowd will have to unwind. It’s akin to catching a turning tide. On the flip side, if you trade trends yourself, you could mirror some CTA principles like using volatility-adjusted position sizing (so you don’t get blown out in choppy periods), diversifying across markets, and being systematic in your rules. The success of CTAs over decades (many delivered equity-like returns with bond-like vol) shows the power of disciplined trend following. They’ve survived by sticking to their models and managing risk relentlessly.
One interesting note - CTAs often serve as “crisis alpha” providers, meaning they tend to perform in bear markets for stocks by shorting them. In the 2008 crisis, many trend following funds had one of their best years (same in 2022), because they flipped short across equities and commodities and rode the massive downtrend (and in 08 crisis were long bonds which were rallying). So, CTAs are sometimes viewed as market stabilisers as they provide liquidity by going short in panics and long in manias. Yet, as mentioned, they can exacerbate moves in the middle of trends.
In the current era, CTAs collectively manage hundreds of billions of dollars. That means their trading can noticeably impact large markets due to the leverage they gear. For example, research might estimate that if S&P 500 crosses a certain price, CTAs would need to sell $50 billion of equity futures. That’s actionable info for a short term trader, you could ride that wave or at least avoid fighting it.
Summarising what CTAs actually do in a nutshell… They use systematic trend following rules: buy rising markets, sell falling markets. They apply volatility filters and position scaling to target a steady risk level. They ignore narratives, focusing only on price and technical signals. Their flows can reinforce trends (creating self-fulfilling momentum) and occasionally overshoot prices relative to fundamentals. They cut positions during extreme volatility and aim for diversification across many markets. They represent a significant chunk of volume in futures, so their strategy shifts can move markets.
For a trader, being aware of CTA behaviour provides a sort of “map” of mechanical flows in the market. It’s a part of the puzzle beyond just fundamentals and retail trading. In essence, CTAs are the embodiment of “the trend is your friend” mantra, codified into algorithms. Knowing that they will be our friend until the trend bends (and then they might all rush for the exit) helps you plan your own entries, exits, and expectations. Price momentum matters, and CTAs are both witnesses to and contributors of that momentum. By aligning with or at least respecting what they do, you avoid getting run over and perhaps hitch a ride on the trend-followers’ train.
If I Had to Start Over
Imagine starting fresh with only $25k and your hard-won knowledge. What would I do differently?
First, with $25k and nothing else, I’d prioritise capital preservation. $25k is a solid stake, but not so large that you can weather huge hits. The game would be to avoid blowing that stake at all costs. This means strictly limiting risk per trade: perhaps 2% (so $500 risk per trade) or even 1% until consistency is proven. A newbie mistake is risking way too much on each trade, trying to get rich quickly from a small account. I’d remind myself that even with $25k, compounding at a reasonable rate can grow it, whereas a blown account goes to zero. So position sizing and risk management tools come first. I’d use a position size calculator religiously, set hard stop losses on every trade, and maybe use bracket orders to enforce them (so I can’t cancel out of fear/greed).
I would likely focus on a few simple, proven setups that match my personality and can be executed with discipline. For instance, one setup could be a trend pullback - identify a strong trend (maybe by a moving average filter) and buy on a pullback to support or a moving average, with a tight stop below. Another could be a breakout with a retest, so, instead of buying initial breakouts, let price break out, then buy on the retest of the breakout level if it holds. I’d also consider a reversal setup like a double bottom with bullish divergence, but only at key technical levels, since it’s lower probability. The key is to pick a small repertoire of setups that I deeply understand and have seen succeed historically, rather than chasing every hot pattern I see on Twitter. Each setup in my playbook would have clearly defined entry, stop, and exit rules.
I’d also structure my trading day. For example, if day trading, only trade certain hours (say the first 2 hours and last hour of market for volatility, and no forcing trades mid-day if nothing’s happening). Overtrading is a common newbie issue. A habit of patience, maybe even setting a rule like max 2 trades a day could protect me from churn. On swing trades, a habit might be to only check prices at designated times, to avoid micro-managing and emotional tinkering.
Tools-wise, aside from journals and charting, maybe use an alert system (so I don’t stare at screens all day). For example, set price alerts at levels of interest, then I can step away until the alert triggers, which should in turn help prevent boredom trades. I’d also use risk management tools like OCO orders to automate profit taking vs stop, so I don’t second-guess exits as much. Modern brokers have lots of features, so I’d familiarise and use them (bracket orders, trailing stops, etc).
In short, starting over, I’d keep it simple and systematic. Focus on mastering a few setups and execution, rather than chasing every opportunity. That likely means in the first 3 to 6 months, I might be quite inactive waiting for the right trade. That’s fine. It beats losing money on noise daily. Also, I’d track performance rigorously from day one: treating it like a fund.
Most importantly, I’d focus on the psychological side of the game.
The first go around, many of us learn these lessons the hard way.
So let’s pull it together…
Process over outcome - focus on refining your process (routine, risk rules, setup criteria) rather than fixating on each trade’s result. A robust process yields long-term results; a sloppy process can win short term but will bite later.
Discipline is paramount - while strategies and markets may change, the discipline not to violate your rules is a must. Your process should evolve, but your discipline should not. It should remain as rigid as steel. If you said you’ll cut a loss at -2%, do it every time. If your rule is not to trade during news, stick to it. This consistency builds the steady mindset that separates long-term winners from gamblers.
Risk management first - I hammered on volatility targeting, gross exposure, anti fragility: the common thread is to always know your downside and keep it in check. That means position sizing appropriately, diversifying sensibly (watch those hidden correlations), and using stops or hedges to guard against tail risk. By running risk deliberately, you ensure you’re around for the next opportunity.
Press your edge when it’s real - don’t stagnate… when you truly have a great trade idea, don’t be afraid to size up within your risk limits. Squeeze more from your best ideas by letting winners run and even adding to them when confirmed. Conversely, cut losers and avoid the overtrading trap. Fewer high-quality trades beat dozens of low-quality ones.
Longevity mindset - this isn’t a get-rich-quick scheme. Trading is a career, not a lottery ticket. That means actually looking after yourself - sleep properly, exercise, manage stress, and don’t bet the farm on every trade. Compounding is incredibly powerful, but it only works if you stay in the game long enough to let it work.
Cut the noise and excessive indicators.
Cut ego and emotions from decision-making. We all have impulses, but you must design systems to mitigate emotional trades. No revenge trades or doubling down out of prides. The market humbles those who can’t humble themselves.
Cut unsustainable habits. If you find yourself overleveraging to chase a loss, or neglecting sleep to monitor positions 24/7, step back and recalibrate. Those patterns lead to burnout and eventually blow up.
So ask yourself with each big or small trading decision… Am I acting in line with a durable process, or on a fleeting emotion?
This manual isn’t about an overnight transformation; it’s more about systematic evolution. Start with one area that resonates most. If you’re struggling with position sizing, implement the conviction scoring system. If you’re getting whipsawed by regime changes, focus on volatility targeting and gross exposure management.
If you enjoyed it, feel free to drop a like.
Have a good day,
Fed
amazing detailed note
Thank you. Great summary