Ask most options traders which parameter matters more for pricing: volatility or dividends. Almost everyone says volatility. And almost everyone is wrong. Chapter 64 of Wilmott’s book shows that for many common option structures, the sensitivity to dividend yield actually exceeds the sensitivity to volatility. Once you see the numbers, you start treating dividends very differently.
Here is something that should make every options trader stop and think. The “optimal” time to exercise an American option depends on who you are. The textbook answer assumes the holder is delta hedging. But if the holder were delta hedging, why would they buy the option in the first place? Chapter 63 of Wilmott’s book, based on a 1998 paper with Dr. Hyungsok Ahn, digs into this question and reaches a conclusion that is great news for option writers.
Would you rather have a guaranteed $5 million or a 50/50 shot at $10 million? Most people take the sure thing. Mathematically the expected value is the same. But something inside you says the safe option just feels better. That feeling is exactly what utility theory tries to capture, and Chapter 62 of Wilmott’s book lays down the framework for it.
Every derivatives textbook makes the same quiet assumption: option trading does not affect the stock price. The stock does its random walk thing, the option value follows, and hedging is just a passive activity. But think about this. In many markets, the nominal value of options traded exceeds the value of trade in the underlying stock itself. When everyone is delta hedging, they are all buying and selling the stock in predictable amounts at predictable times. Can we really pretend this has no effect? Chapter 61 of Wilmott’s book says no, and the consequences are fascinating.
Delta hedging is wonderful in theory. You adjust your position continuously, and risk vanishes. In practice, it is messy. You have to trade at discrete times. Transaction costs eat your lunch. And for some contracts, like barrier options or anything with a discontinuous payoff, the required hedge ratios become absurd. You end up buying and selling enormous quantities of the underlying at exactly the wrong moments. Chapter 60 of Wilmott’s book introduces static hedging as the cure for many of these headaches.
Almost everything in quantitative finance is built around one assumption: you hedge. You buy the option, you delta hedge, you eliminate risk, and the drift of the stock does not matter. Beautiful theory. But Chapter 59 of Wilmott’s book asks an uncomfortable question: what if you are not hedging?
The jump diffusion models from the previous chapter have a fundamental problem. You have to estimate the probability of a crash, and that is incredibly hard to do. How often does a 15% market drop happen? Once every 5 years? 10 years? 50 years? Nobody really knows. Chapter 58 of Wilmott’s book takes a completely different approach. Instead of guessing crash probabilities, it asks: what if the worst happens?
Here is a thing that bothers every honest quant at some point. The lognormal random walk, the thing Black-Scholes is built on, assumes that stock prices move smoothly. Small steps. Continuous paths. Nice and clean. But if you have ever watched a market during a crisis, you know that prices do not always walk. Sometimes they jump. Chapter 57 of Wilmott’s book tackles this head on and introduces jump diffusion models.
Every few chapters, Wilmott stops talking about theory and shows you a concrete product that exposes why the theory matters so much. Chapter 56 does exactly this. The cliquet option is a structured product that looks innocent on the surface but hides extreme sensitivity to volatility modeling. If you price it with the wrong volatility assumptions, you can be off by a factor of ten in your risk estimate. That is not a rounding error. That is a blowup waiting to happen.
Here is a frustrating reality of stochastic volatility models. You pick a model because it is tractable (Heston, anyone?). You get nice semi-closed-form solutions. But what if the model does not actually describe reality well? You have traded accuracy for mathematical convenience, and in finance, that trade can cost you real money.
Wilmott does not like the market price of risk. He says so right at the start of Chapter 54, and his reasoning is solid. The market price of volatility risk is not directly observable. You can only back it out from option prices, and that only works if the people setting those prices are using the same model you are. If you refit the model a few days later and get a different answer, was the market wrong before? Or is it wrong now? You end up chasing your own tail.
Most people who model stochastic volatility start by writing down a nice-looking equation and then try to fit it to data. Wilmott thinks this is backwards. In Chapter 53, he starts with the data and builds the model from the ground up. It is a refreshingly practical approach. Instead of picking a model because it is mathematically convenient, he asks: what does volatility actually do?
So we made it. Thirteen posts covering every chapter of Flash Boys by Michael Lewis. And now the big question: did any of it matter?
We’ve spent the last two weeks retelling Tim Richards’ “Investing Psychology” (ISBN: 978-1-118-72219-0). It’s been a bracing, sometimes painful journey through the glitches of the human mind.
Let us start with an uncomfortable truth. The Black-Scholes equation has three main parameters: volatility, interest rate, and dividend yield. Of these three, not a single one is known with certainty. Sure, you know today’s stock price. You know the expiry date. But the stuff that actually matters for pricing? You are guessing. Chapter 52 of Wilmott’s book takes this discomfort and turns it into a pricing framework.
Twenty-five posts. That is what it took to retell this book. And honestly, when I started this series back on February 4th, I was not sure I would finish it. A post a day for almost a month is a lot. But here we are.
So after all the chapters, all the experiments, all the arguments back and forth, Burton and Shah finally ask the big question. Who wins? Is the market efficient or not? Time for a new theory entirely?
The book ends the way it started. With a cable buried under American soil and the people who live above it having no clue what it does.
We’ve reached the end of the tour. In the final chapter of “Investing Psychology,” Tim Richards pulls back the curtain on the entire investment industry.
Volatility is not constant. We knew that already. The deterministic volatility surface tries to fix this by making volatility a function of stock price and time. But the surface changes every time you recalibrate. The model is fundamentally incomplete.
Can you grow a stock market bubble inside a classroom? Not a metaphor. An actual bubble where prices rise above what everyone in the room knows the thing is worth?
This chapter hit me different than the rest of the book. Maybe because Sergey Aleynikov is from the former USSR, same as me. Maybe because I spent 20 years in IT and know what it feels like when non-technical people judge your work. Probably both.
We’re nearing the end of Tim Richards’ “Investing Psychology.” In Chapter 8, he tackles the myths that keep us trapped in bad financial habits.
You look at the market. Calls with the same expiry but different strikes have different implied volatilities. The Black-Scholes model says this should not happen. Constant volatility means one number for all strikes. But the market does not care what Black-Scholes says.
In Part 1 we talked about the misfits Brad recruited to build IEX. Now we get to the good stuff. They launched it. And then Goldman Sachs did something nobody expected.
We’ve spent a lot of time dismantling our egos and exposing our biases. Now, in Chapter 7, Tim Richards gives us a toolkit to build something better. He calls it “Good Enough Investing.”
You know all those behavioral biases we talked about in earlier chapters? Loss aversion, status quo bias, overconfidence. The big question hanging over all of them is simple. Where do they come from? Are we born with them? Did we learn them from our parents and culture? Or is there something deeper going on inside our actual brains?
You cannot see volatility. You cannot touch it. You cannot even measure it precisely at any given instant. And yet, it is the single most important input in options pricing. Get volatility wrong and nothing else matters. Get it right and you can make a lot of money.
Chapter 7 is called “An Army of One.” And it starts not with trading algorithms or secret cables. It starts with a guy on the subway on September 11, 2001.
Continuing our look at Chapter 6. We know we need to look at the numbers. Now let’s look at the specific mental exercises that can save your portfolio.
Every time you buy or sell stock to rebalance your hedge, you pay a little toll. The bid-offer spread. The commission. The market impact. These are transaction costs, and they are the silent killer of options hedging strategies.
Try selling your house by tomorrow. Not in a month, not after listing it and staging it and waiting for offers. Tomorrow. For cash.
Black-Scholes says you should hedge continuously. Rebalance your portfolio every instant, forever, and all risk disappears like magic. Beautiful theory. Completely impossible in practice.
Chapter 6 is where everything gets real. Brad and his team stop talking about the problem and start building the solution. They quit their jobs, raise money, hire puzzle solvers, and design a stock exchange from scratch. And the centerpiece of the whole thing is a coil of fiber optic cable stuffed inside a box the size of a shoe.
We’ve spent the last five chapters talking about how biased we are. Now it’s time for the “how-to” part. How do we actually fix these mental glitches?
Stocks make more money than bonds. Everyone knows that. But here’s the thing. They make way more money than bonds. And when economists tried to explain why the gap is so big, they couldn’t. Not with their standard models. Not even close.
What if I told you that the day of the week affects your stock returns? Or that one specific month is consistently better than the other eleven? Sounds like astrology for finance people, right?
Before we tear Black-Scholes apart, Wilmott wants to make something clear. This model is a triumph. It changed finance forever. Two of its three creators won the Nobel Prize. Everyone in derivatives uses it, from salesmen to traders to quants. Option prices are often quoted not in dollars but in volatility terms, with the understanding that you plug that number into Black-Scholes to get the price.
We’ve reached the end of our retelling of Cyril Demaria’s “Introduction to Private Equity, Debt and Real Assets.” It’s been quite a journey—from Christopher Columbus to multi-billion dollar mega-funds.
This chapter hit me personally. I’m from the former USSR myself. I know people exactly like Sergey Aleynikov. Brilliant programmers who left because the system wouldn’t let them be what they were meant to be. Reading this felt less like a book and more like a story someone told me over tea.
Picking up from Part 1 of Chapter 5. We know the institutions are playing a different game. Now let’s look at the actual humans running the show and why their biology might be messing with your money.
We are now entering Part 5 of Wilmott’s book: Advanced Topics. Everything so far was classical foundation. Lognormal random walks, Black-Scholes, delta hedging, portfolio theory. Well-established stuff. From here on out, we go beyond the standard model and into territories where things get interesting, controversial, and sometimes dangerous.
By the end of 2010, Brad’s team had built a weapon. Thor worked. It protected investors from getting front-run by high-frequency traders. But here’s the problem. They had built a defense against an enemy they barely understood.
When we have a toothache, we go to a dentist. When we have a legal problem, we call a lawyer. So when we have money to invest, we go to a professional, right?
For a long time, private equity was a small, quiet industry that stayed below the radar. But those days are over. Today, it’s a global powerhouse, and that change is bringing some big questions.
Every trader has said something like this at some point: “The stock has good fundamentals, it’s cheap, but the price action looks terrible. I’m going to wait.”
If you’ve ever bought a house, you know it’s a long, stressful process. You have to get an inspection, talk to the bank, and negotiate with the seller. Now imagine doing that for a multi-million dollar company.
All the math in the world does not help if the people using it are reckless, clueless, or dishonest. Chapter 44 is Wilmott’s tour through the greatest hits of derivatives disasters. These are not abstract case studies. Real people lost real billions, institutions collapsed, and careers ended. Some of these stories are tragic, some are farcical, and a few are both.
Every person I know who works in IT started from the bottom. Fixing cables, carrying equipment, dealing with angry users. Nobody hands you a corner office in tech. You earn it by touching the actual hardware. And that’s exactly why Ronan Ryan understood something that every Wall Street trader missed.
Picking up from Part 1 of Chapter 4. We know that groups are dangerous. Now let’s look at how the way information is “framed” changes how we spend our money.
Benjamin Graham is probably the most famous contrarian investor who ever lived. Together with David Dodd, he invented what we now call value investing. The whole idea is simple. Buy stocks that other people don’t like. Stocks with low prices compared to their earnings or book value. Cheap stocks. Unpopular stocks.
Most people think of private equity as just owning a piece of a company. But the “private markets” universe is much bigger than that. It also includes two other major categories: Private Debt and Private Real Assets.
Value at Risk tells you what to expect on a normal day. But what about the days that are not normal? What about crashes? Chapter 43 introduces CrashMetrics, which is Wilmott’s own creation. If VaR is about routine market conditions, CrashMetrics is the opposite side of the coin. It is about fire sales, panic, and the far-from-orderly liquidation of assets.
In 1992 two economists published a paper that accidentally shook the foundations of modern finance. They did not mean to. They were actually trying to defend the system. But what they found in the data was so clear and so stubborn that it changed how everyone thought about stock prices.
Chapter 2 of Flash Boys is where we meet Brad Katsuyama. And honestly, this is where the book really starts cooking. Because Brad is not some Wall Street hotshot from Goldman Sachs. He’s a Canadian guy from Toronto who ended up in New York almost by accident.
Humans are social animals. We evolved to survive in groups, and that means we have a deep-seated need to fit in. But in Chapter 4, Tim Richards explains that while “conforming” kept our ancestors alive, it’s making modern investors broke.
Private equity isn’t just one thing. It’s a whole universe that follows a company from its very first day until it’s a giant corporation.
Chapter 1 of Flash Boys opens like a heist movie. Two thousand workers are digging across America. They don’t know why. They don’t know what they are building. And they are told to keep their mouths shut.
Continuing with Chapter 3 of “Investing Psychology.” We’re looking at all the weird external stuff that influences our money.
Experience actually helps with some biases. Research shows that older investors are less prone to the disposition effect (selling winners and holding losers).
We talked about Value at Risk (VaR) earlier in the book. You know the concept: estimate how much you can lose from your portfolio over a given time, with a given confidence level. Cool idea. But where do you get the actual numbers? Volatilities, correlations, credit data? Chapter 42 is about two systems that try to answer that question: RiskMetrics and CreditMetrics. Both came from JP Morgan, and both became industry standards.
You ever played the Madden NFL video game? For years, EA Sports put a top player on the cover. And then something funny kept happening. The cover athlete would have a terrible next season. Injuries, bad stats, team losses. Fans started calling it the Madden Curse. Some players actively tried to avoid being on the cover.
Every day you make decisions based on past data. What to eat for breakfast. How to approach your boss with a question. You look at what happened before and try to predict what will happen next.
If you ever invest in a private equity fund, don’t panic when you look at your statement after the first year. It’s probably going to show that you’ve lost money. This is what we call the J-Curve.
If you hold a bond and the issuer might default, you want insurance. That is the basic idea behind credit derivatives. You pay someone a regular premium, and if the bad thing happens, they pay you. Chapter 41 of Wilmott’s book walks through the main types of credit derivatives, from simple default swaps to the multi-name products that helped blow up the global financial system in 2008.
Michael Lewis starts “Flash Boys: A Wall Street Revolt” with one of the best ironies I’ve seen in a finance book. After the 2008 financial crisis, after everything Goldman Sachs did, the only Goldman employee who got arrested was a guy who took something FROM Goldman. Not someone who helped crash the economy. A Russian programmer named Sergey Aleynikov who copied some code.
We like to think of ourselves as independent thinkers. The “American Dream” is built on the idea that you can do anything if you just try hard enough. But in Chapter 3, Tim Richards shows us that we’re heavily influenced by the situation we’re in, often without even knowing it.
In Chapter 39 we valued default risk by modeling the firm’s assets, earnings, and cash. That is the “look inside the company” approach. Chapter 40 takes a completely different path. Instead of trying to understand why a company might default, just model default as a random external event. Roll a die. If you get a 1, the company defaults. Simple.
So I just finished re-reading Flash Boys by Michael Lewis, and honestly, it hits different every time. This book came out in 2014 and people are still arguing about it. That tells you something.
People are sticky. Not physically. Mentally. We stick to whatever we already have, whatever is already happening, whatever is the default. And this stickiness costs investors real money every single day.
Picking up from where we left off in Chapter 2. We’ve established that we’re all overconfident. Now let’s look at how that overconfidence turns into specific, expensive mistakes.
Here’s a fun fact: you’re probably already an investor in private markets.
Even if you’ve never heard of a “General Partner,” if you have a pension fund or an insurance policy, your money is likely being funneled into private companies. Big institutions like banks and pension funds take the premiums we pay and invest them in non-listed companies to get better returns.
We usually think of the USA as the birthplace of modern finance. But when it comes to venture capital, the story has a very French twist.
We all like to think we’re smart. If we didn’t think we were going to make money, we wouldn’t invest. But here’s a cold splash of water: 93% of American drivers think they’re “above average.” Mathematically, that’s impossible.
Welcome to Part Four of Wilmott’s book: Credit Risk. Up until now, every product we priced assumed that all cashflows are guaranteed. Coupons get paid. Bonds get redeemed. Nobody goes bankrupt. That was a comfortable world to live in, but it is not reality.
You know that feeling when you buy a stock right after seeing a scary headline, and then two weeks later you wonder what you were thinking? That’s a perception bias doing its work on your brain.
We’ve talked about history, but let’s get into the real engine of private equity: the entrepreneur.
Cyril Demaria makes one thing very clear: without entrepreneurs, private equity has no reason to exist. The entrepreneur is the one who takes a bunch of separate pieces—time, money, ideas—and turns them into something way bigger than the sum of its parts.
Theory is nice. But at some point you have to price actual products that real people are trading. Chapter 38 of Wilmott’s book takes two interesting fixed-income contracts and walks through how to price them from scratch. No hand waving. Just the math, the logic, and even the code.
Continuing our deep dive into Chapter 1 of Tim Richards’ “Investing Psychology.” Last time, we talked about how our senses lie. Today, we’re looking at why we think we’re in charge when we definitely aren’t.
You know that feeling when you lose a $20 bill on the street? It ruins your whole afternoon. But finding $20 on the street? Nice, sure. You smile for maybe five minutes and forget about it.
We saw how Christopher Columbus was basically a 15th-century startup founder. But for private equity to become a real industry, something big had to change. We needed a shift from “kings and queens” to “partners and contracts.”
In earlier chapters of Wilmott’s book, we modeled interest rates by picking one short-term rate and deriving the entire yield curve from it. Works fine for simple stuff. But Heath, Jarrow, and Morton said: why model just the short end when you can model the whole forward rate curve at once?
Wandering around the average investor’s mind is like taking a tour of Wonderland with the White Rabbit. Most of what we think is true is actually false.
Economics has a favorite character. The Rational Man. He always knows what he wants. He always picks the best option. He never panics, never gets confused, never makes a dumb choice because he’s tired or emotional.
If you think venture capital is a modern invention from Silicon Valley, think again. It’s actually hundreds of years old. In fact, Cyril Demaria argues that Christopher Columbus was one of the first great venture capitalists.
We have spent several chapters building interest rate models. Vasicek, CIR, Hull and White, Ho and Lee, Black-Derman-Toy. Each one chosen for its nice mathematical properties, clean closed-form solutions, and easy calibration. But here is the uncomfortable question Wilmott asks in Chapter 36: do any of these models actually match what interest rates do in the real world?
I’ve spent over 20 years in IT and a lot of time looking at charts and numbers. One thing I’ve learned is that the math is often the easy part. The hard part is the gray matter between your ears.
You ever watch financial news and hear someone say “the market broke through resistance” or “the market looks tired”? These phrases sound like the market is some living creature with feelings. And if you come from a science background, your first reaction is probably: what does that even mean?
Because it’s so hard to get good data on private equity, people start taking shortcuts. And those shortcuts lead to some big mistakes.
One-factor interest rate models have a fundamental problem. They assume that a single number, the spot interest rate, drives the entire yield curve. That means all rates of all maturities move together in lockstep. If the spot rate goes up by 1%, every other rate adjusts accordingly. The yield curve can shift up and down, but it cannot twist or tilt independently at different maturities.
Remember the dot-com bubble? Companies with zero profit, sometimes zero revenue, trading at insane valuations. Analysts invented new ways to justify the prices. “Forget earnings, count the eyeballs!” And for a while, it worked.
I already talked about why private companies are so secretive. But there’s a whole industry built on trying to find their secrets anyway.
Most people know what a mortgage is. You borrow money to buy a house, you make monthly payments, and after 20 or 30 years you own the house free and clear. But what happens to all those mortgages after the bank gives them out? They get bundled together and sold to investors. That is a mortgage-backed security. Chapter 34 of Wilmott’s book explains how these things work, why they are tricky to price, and what makes them different from every other fixed-income product.
For decades, traditional finance people had a simple answer to the noise trader problem. Milton Friedman said it. Eugene Fama said it. Fischer Black said it. The answer was: irrational traders will lose their money to smart traders and disappear.
Imagine a bond that can transform into stock. That is a convertible bond. Chapter 33 of Wilmott’s book dives into one of the most fascinating instruments in finance, a hybrid security that sometimes acts like debt and sometimes acts like equity. It sounds simple on the surface, but underneath it is a deeply complex contract involving American option features, stochastic interest rates, path dependence, dilution, and credit risk.
One of the biggest problems with private companies is that they don’t have to tell you anything. In the stock market, companies have to share their financial reports all the time. But in the private world, there’s no law saying they have to.
Economics has a rule that sounds so obvious it barely needs saying. If two things are identical, they should have the same price. If they don’t, someone will buy the cheap one and sell the expensive one until prices meet in the middle. Easy. Done. Move on.
Before behavioral finance became a real academic field, people already knew something was off with markets. Traders in the 1920s had their own rules. Value investors in the 1930s had theirs. And nobody was waiting for professors to tell them the market was irrational. They lived it every day.
If you thought equity options were complex, welcome to the world of interest rate derivatives. Chapter 32 of Wilmott’s book takes everything we learned about modeling bonds and the yield curve and applies it to actual products that traders buy and sell every day. Caps, floors, swaptions, callable bonds, and a whole zoo of exotic contracts.
The words “private equity” get thrown around a lot. But people use them in different ways, and it gets really confusing.
Cyril Demaria started this book because he couldn’t find anything good to read about private equity. Most of what was out there just didn’t make sense. It didn’t match what actually happens in the real world.
Chapter 2 of Burton and Shah’s book is about the math behind stock prices. Don’t run away yet. I promise to keep it simple. The chapter introduces something called CAPM and the “market model.” These are the tools that traditional finance uses to describe how stock prices should behave. And if you want to understand why behavioral finance matters, you need to know what it’s arguing against.
In the last chapter, we saw one-factor models for interest rates. You pick a model, choose some parameters, and out comes a theoretical yield curve. But here is the problem: that theoretical yield curve almost certainly does not match the actual yield curve you see in the market. And if your model gives wrong prices for plain vanilla bonds, how can you trust it to price anything more complex?
I’ve been reading a lot of books on finance lately. Most of them are either too simple or way too complicated for anyone who doesn’t have a PhD in math. But I found one that actually makes sense. It’s called “Introduction to Private Equity, Debt and Real Assets” by Cyril Demaria.
With Chapter 30, we enter Part Three of the book: fixed-income modeling and derivatives. Up to now, interest rates have been either constant or known functions of time. That is fine for short-dated equity options. But for longer-dated contracts, and especially for bonds and interest rate derivatives, we need to treat the interest rate itself as random. This changes everything.
Chapter 1 of Burton and Shah’s book gets right to the big idea. The Efficient Market Hypothesis. EMH for short. This is the theory that traditional finance is built on, and it is the thing behavioral finance tries to tear apart.
Theory is nice, but at some point you have to look at real contracts. Chapter 29 of Wilmott’s book takes a collection of actual term sheets for equity and FX derivatives and walks through them one by one. The goal is practical: can you look at a piece of paper describing some exotic contract and figure out how to price and hedge it?
Let me tell you something that took me years to figure out. Traditional economics and finance are built on one really big assumption: that people are rational. And not just a little rational. Perfectly, mathematically, always-making-the-best-choice rational.
By this point in the book, Wilmott has been classifying exotic options into tidy categories. Asian options got their own chapter. Lookbacks got their own chapter. Barrier options got their own chapter. But the universe of exotic derivatives is large and growing, and eventually the classification exercise breaks down. Chapter 28 is where Wilmott gives up on neat categories and just throws a bunch of interesting exotics at us. It is a grab bag, and it is fun.
I’m starting something new here. Over the next 25 days, I’m going to retell the book Behavioral Finance: Understanding the Social, Cognitive, and Economic Debates by Edwin T. Burton and Sunit N. Shah.
Most options we have seen so far give the holder a choice at one specific moment. With a European option, you decide at expiry. With an American option, you pick the best time to exercise. But what if the option let you actively trade during its entire life, and then insured you against losses? That is the idea behind the passport option, and Chapter 27 of Wilmott’s book uses it to introduce stochastic control.
Every trader has the same fantasy: buy at the absolute lowest price and sell at the absolute highest. You can buy a contract that pays you as if you did. That is the lookback option, Chapter 26.
Asian options are probably the most practical exotic derivatives. In crude oil markets, they are not even considered exotic. They are the vanilla. Chapter 25 applies the framework from Chapter 24 to options whose payoff depends on an average price.
Barrier options showed us weak path dependence. The contract cared about the path, but we still solved a two-variable problem. Chapter 24 takes the next step: strong path dependence. Cannot be hidden in boundary conditions. We need an extra variable.
Barrier options used to be exotic. Now they are one of the most heavily traded option types. Chapter 23 goes deep on them. Simple enough to understand, useful enough to be everywhere, tricky enough to mess up if you do not pay attention.
We have spent a lot of time on vanilla calls and puts. But now Wilmott opens Part Two of the book, and things get interesting. Chapter 22 introduces exotic derivatives, contracts that keep quants employed and traders nervous.
Chapter 21 is short and completely different from everything else in the book. No equations. No theorems. Instead, Wilmott describes a classroom trading game designed to teach option pricing through actual experience. The game was created by one of his former students, David Epstein, and it is surprisingly brilliant in its simplicity.
People have been trying to predict financial markets since markets existed. Chapter 20 of Wilmott’s book takes an honest, slightly skeptical tour through the methods traders use. The verdict? Mixed at best. And Wilmott is not shy about saying so.
Any smart investor, whether a billion-dollar bank or a retiree with a savings account, should know the answer to one question: how much could I lose? Chapter 19 introduces Value at Risk (VaR), the industry standard for answering exactly that.
Up until now in Wilmott’s book, we have been hedging everything. Buy a derivative, hedge with the underlying, pocket risk-free returns. Banks love it. But not everyone plays that game. Fund managers buy and sell assets trying to beat the bank rate. They take risk on purpose. Chapter 18 is about doing that intelligently.
Chapter 17 starts with a confession that always gets Wilmott in trouble with bank training managers. He wants to call his lecture “Investment Lessons from Blackjack and Gambling.” They want him to change the title because regulators might frown on it. Wilmott thinks this is silly. Investment and gambling share the same mathematical roots. And most professional gamblers he knows understand risk and money management better than most risk managers at banks.
Chapter 16 is a short but important one. It asks a question that every quant should think about deeply: is the normal distribution actually a good model for financial returns? The answer is “mostly yes, but catastrophically no.” And that “catastrophically no” part has wiped out entire firms.
In Part 1 we covered the intuition behind the binomial model: delta hedging, risk-neutral pricing, and why probabilities do not matter for option values. Now we get to the practical side. How do you actually build a binomial tree, compute option prices, estimate Greeks, handle American options, and connect everything back to Black-Scholes?
Chapter 15 of Wilmott’s book introduces the binomial model, and honestly it might be the single most important chapter for building intuition about how option pricing actually works. Forget stochastic calculus for a moment. This model uses nothing more than basic arithmetic, and yet it arrives at exactly the same answers as Black-Scholes.
Swaps are one of the biggest markets in finance. The total notional principal is comfortably in the hundreds of trillions of dollars. Chapter 14 of Wilmott’s book explains how they work, why they exist, and how they connect to the bond pricing we covered in the previous post.
We are leaving the world of options for a bit and entering the world of fixed income. This is the world of bonds, interest rates, and cashflows. Chapter 13 of Wilmott’s book is a self-contained introduction that does not require anything from earlier chapters. If you have ever wondered what a yield curve is or why bond traders care about something called “duration,” this is the post for you.
This chapter is one of the most practically important in the entire book. Wilmott starts with a bold statement: there is money to be made from options because they may be mispriced by the market. He knows the efficient market crowd hates this idea. But volatility arbitrage hedge funds clearly believe it, so let us look at the math.
So far in this series we have been looking at options on a single stock. One underlying, one random walk, one volatility. Life was simple. But the real world is messier. Many popular contracts depend on two, five, or even twenty different assets at the same time. Welcome to the world of multi-asset options.
Most of derivative pricing theory goes out of its way to avoid thinking about probability. The whole point of hedging and no-arbitrage is to eliminate uncertainty. You do not need to know where the stock is going; you just need to build a portfolio that does not care. But Chapter 10 of Wilmott’s book asks us to step back and look at the randomness underneath. Where might the stock actually end up? How long before it hits a certain level? These questions matter for American options, for speculation, and for understanding what the math is really doing.
European options are simple: you wait until expiry, check if they are in the money, and either collect the payoff or walk away. American options give you more power and more headaches. You can exercise at any time before expiry, which sounds great but raises a hard question: when exactly should you do it? Chapter 9 of Wilmott’s book tackles this problem, and the ideas that come out of it show up again and again throughout the rest of quantitative finance.
The vanilla Black-Scholes model assumes a clean world: no dividends, constant parameters, one type of underlying. Real markets are messier. Chapter 8 of Wilmott’s book starts adding realism. Dividends, currencies, commodities, stock borrowing costs, time-dependent parameters. Each generalization is surprisingly straightforward once you understand the basic framework, which is the good news. The bad news is that you need to keep track of which adjustments apply to your specific situation.
Chapter 7 is one of the meatiest chapters in the first part of Wilmott’s book. It does two big things: first, it derives the actual Black-Scholes formulas for calls, puts, and binary options step by step. Second, it introduces the Greeks, which are the sensitivity measures that traders live and die by every single day. Wilmott makes an interesting argument early on: getting the hedging right is more important than getting the price right. Let me explain why.
If you have ever cooked something on a metal pan, you already understand partial differential equations. No, seriously. The way heat flows from the burner through the pan to your food follows the exact same type of math that prices options on Wall Street. Chapter 6 of Wilmott’s book makes this connection explicit, and honestly it makes the whole thing feel a lot less scary.
Wilmott calls Chapter 5 “without doubt, the most important chapter in the book.” He is not exaggerating. Everything before this was setup. Everything after this builds on what happens here. The Black-Scholes equation was first written down in 1969, the derivation was published in 1973, and finance has never been the same since.
Chapter 4 is the toolbox chapter. Before we can price options, we need the mathematical machinery to handle random variables properly. The centerpiece is Ito’s lemma, the rule that replaces ordinary calculus when things are random. Wilmott goes out of his way to make this accessible, and honestly, it is not as scary as it sounds.
Chapter 3 is where the real modeling begins. Wilmott takes us from “stock prices look random” to “here is the specific mathematical model for that randomness.” By the end of this chapter, we have the fundamental equation that drives almost everything in quantitative finance.
Chapter 2 is where Wilmott introduces the main character of the book: options. Also known as derivatives or contingent claims. No heavy math here yet, just definitions, jargon, and some clever strategies people use to make (or lose) money.
Chapter 1 of Wilmott’s book starts gently. No scary equations yet. Just the basic building blocks of finance that everything else in the book rests on. If you have worked in finance for a while, you know most of this already. But if you are coming from math or engineering background, this is the foundation you need.
I’m about to do something a bit ambitious. I’m going to retell the entire “Paul Wilmott on Quantitative Finance” - one of the biggest, most comprehensive textbooks on quantitative finance ever written. And I’m going to do it in plain English.
We made it. Over the past few months, I walked you through all ten chapters of “Free to Choose” by Milton and Rose Friedman. From the power of a simple pencil to constitutional amendments, from the Great Depression to school vouchers, from trade wars to inflation. Fifteen posts. One big idea: people make better decisions for themselves than governments make for them.
In one massive government building, employees spend their days trying to convince Americans to stop smoking. In another building, a few miles away, other employees spend their days spending taxpayer money to help farmers grow more tobacco. Both groups are hardworking. Both groups believe they are serving the public good. And both groups are paid with your money. That image – a government at war with itself – is where the Friedmans begin their final chapter. And it captures everything that has gone wrong.
Take a five-dollar bill out of your wallet. Now cut a rectangle of the same size from a glossy magazine. Both are pieces of paper. Both have pictures and numbers on them. One can buy you lunch. The other is garbage. Why? That question – why green paper has value – is where the Friedmans begin their chapter on inflation. And the answer is stranger than you might think.
If someone asked you what improved the life of workers over the past two centuries – shorter hours, higher pay, safer conditions – what would you say? Most people would answer “labor unions” or “the government.” The Friedmans say both answers are wrong. And they have numbers to back it up.
In Part 1, we saw how regulatory agencies – the ICC, the FDA – were created to protect consumers and ended up protecting the industries they were supposed to regulate. But the Friedmans are not done. What about product safety? What about the environment? What about energy? And if government regulation keeps failing, what is the alternative? Part 2 answers these questions – and the answer is not what you might expect.
Imagine you hire a bodyguard to protect you. A few years later, you realize the bodyguard is now working for the people you needed protection from – and you are still paying his salary. That, in short, is what happened with most of America’s consumer protection agencies. They were created to defend ordinary people. They ended up defending the industries they were supposed to regulate.
In Part 1, we saw how American schools started private, got taken over by government, and slowly became bloated bureaucracies that serve themselves more than students. Friedman proposed a voucher plan – give parents the money and let them choose where to send their kids. Simple idea. But if it is so simple, why has it not happened? And what about colleges and universities – are they suffering from the same disease?
Your child goes to a school you did not choose. The teachers follow a curriculum you had no say in. The building may be falling apart or it may be beautiful – that depends almost entirely on your zip code. If you are wealthy, you can move to a better district or pay for private school. If you are not, you are stuck. And the people who run the system have very little reason to care what you think. That is the state of American education. How did it get this way?
“All men are created equal.” We hear those words so often they slide right past us. But what do they actually mean? Thomas Jefferson wrote them. He also owned slaves until the day he died. Clearly, even the man who drafted the Declaration of Independence did not mean everyone is identical in talent, strength, or intelligence. So what did he mean – and how has the meaning of “equality” changed over two centuries?
In Part 1, we saw how the welfare state grew from a handful of emergency programs during the Great Depression into a sprawling empire that spent more than the Army, Navy, and Air Force combined. We looked at Social Security, the welfare mess, and the math that did not add up. Now the question is: why do these programs keep failing, and what would actually work better?
Imagine you sign up for a retirement plan. Your employer tells you the money goes into a trust fund. Every paycheck, a chunk disappears under the label “contribution.” You believe that somewhere, in some account with your name on it, your savings are growing. Then one day you find out there is no account. There is no fund. The money you paid in was handed directly to someone who retired before you. And your retirement depends entirely on whether people who come after you are willing to do the same for you. That is Social Security. And it is just one piece of a much larger story.
The Great Depression was not what you think it was. Most people believe it was the ultimate proof that capitalism is dangerous and unstable. That free markets, left alone, will eventually destroy themselves. Friedman says this story is almost exactly backwards. The Depression was not a failure of the free market. It was a failure of government – specifically, a small group of people at the Federal Reserve who had the power to prevent the disaster and chose not to use it.
Every country says it wants to protect its workers. Every government says tariffs and controls are there to help ordinary people. Friedman says: look at the results, not the speeches. In almost every case, the people these controls claim to protect are the ones who pay the highest price.
Nobody on this planet knows how to make a pencil. Not one single person. That is not a joke. It is the opening argument of Chapter 1 of Free to Choose, and once you understand it, you will never look at the economy the same way again.
Two documents changed the world in 1776. One told a king to back off. The other explained why free people, left alone, build prosperity almost by accident. Milton Friedman opens Free to Choose by connecting these two ideas and showing how they built the richest nation in history. He also warns that America has been slowly walking away from both.
Why do some countries become rich while others stay poor? Why do government programs meant to help people so often make things worse? And how does a simple pencil prove that millions of strangers can cooperate without anyone telling them what to do?
We made it. Fifteen posts, twelve chapters, and one very thorough book about hedge fund compliance. If you stuck with this series from beginning to end, thank you. That was a long ride.
This is the last real chapter. Scharfman wraps up the book by looking ahead. What trends are shaping hedge fund compliance going forward? What should people in the industry worry about?
This is Part 2 of Chapter 11. If you missed Part 1 about compliance consulting, start there. This half covers the interview with Vinod Paul from Eze Castle Integration. The focus here is cybersecurity, cloud computing, data protection, and disaster recovery for hedge funds.
Chapter 11 is different from everything before it. Instead of explaining rules and frameworks, Scharfman sits down with real people who do compliance work every day. He interviews two compliance service providers and lets them talk about what they actually see in the field.
Chapter 10 of Scharfman’s book is one of the most practical chapters so far. Instead of explaining rules or regulations, it focuses on six real mistakes hedge funds make with their compliance programs. Let me walk you through all six.
Chapter 9 is where Scharfman stops talking theory and starts showing what compliance looks like in practice. He gives us two hypothetical scenarios (basically role-play conversations) and two real SEC enforcement cases. Each one teaches a lesson about what can go wrong when compliance is treated as an afterthought.
Up until now in this series, we talked about compliance from the hedge fund’s point of view. How they build programs, hire people, write policies. Chapter 8 flips the script. Now we look at it from the investor side. How do investors figure out if a fund’s compliance is actually good?
Previous chapters talked about the people and systems behind hedge fund compliance. Chapter 7 shifts focus to paperwork. And yes, I know paperwork sounds boring. But here’s the thing: without proper documentation, a hedge fund’s compliance program basically does not exist. At least not in the eyes of regulators.
So far in this series we talked about in-house compliance. The people inside a hedge fund who make sure rules are followed. But here’s the thing. Sometimes that’s not enough. Sometimes you need to call in outside help.
Technology runs everything these days. Hedge funds are no different. Chapter 5 of Scharfman’s book looks at how hedge funds use technology specifically for compliance. Not for trading. Not for making money. For following the rules and keeping records.
In the last chapter we talked about the Chief Compliance Officer. The person in charge. But here’s the thing. One person can’t do everything. Even the best CCO needs a team. Chapter 4 is about how that team gets built and how the whole thing works together.
Every hedge fund needs someone who keeps things legal. That person is the Chief Compliance Officer, or CCO. Chapter 3 of Jason Scharfman’s book breaks down what a CCO actually does, what qualifications they need, and how the whole regulatory reporting process works.
Chapter 2 of Scharfman’s book is all about regulation. Who makes the rules for hedge funds? Who enforces them? And what happens when the regulators actually show up at your door? Let’s break it down.
Let’s start with the basics. What does “compliance” even mean? In simple words, compliance is how an organization follows the rules. Every industry has rules. Healthcare, construction, science, finance. The government usually writes these rules, but sometimes they come from other places too.
So I just finished reading “Hedge Fund Compliance: Risks, Regulation, and Management” by Jason A. Scharfman, and I wanted to share what I learned. This book is dense. Like, really dense. But the stuff inside is important if you want to understand how hedge funds actually follow the rules (or don’t).
Twenty-nine posts. Twenty biases. Four investor types. Two guidelines. And one big idea that runs through everything: you are not a rational investor, and that is okay as long as you know it.
Chapter 27 is the final content chapter of the book, and it is the one that brings everything together. After learning about 20 biases, two guidelines, a diagnostic framework, and two case studies, we now get the detailed profiles of all four Behavioral Investor Types.
We have spent the last 23 chapters learning about 20 different biases. That is a lot of biases to keep track of. Even for a financial advisor who does this for a living, diagnosing each client for all 20 biases would take forever.
Chapter 25 is where all the theory from the entire book gets applied to actual people. Well, fictional people. But they feel real enough that you will probably recognize yourself or someone you know in one of them.
After 20 chapters of learning about individual biases, Pompian finally gets to the big question: so what do you actually DO with all this knowledge?
This is the last emotional bias in Pompian’s book, and it is an interesting one because it touches on identity. Affinity bias is about investing based on who you think you are (or who you want to be), rather than what actually makes financial sense.
The opening quote of this chapter is from Harry Markowitz, the father of Modern Portfolio Theory. He said he split his retirement contributions 50/50 between bonds and equities because he wanted to “minimize my future regret.” Not maximize returns. Not optimize the efficient frontier. Minimize regret.
You know that feeling when you are selling something on Craigslist and you think your used couch is worth $500, but nobody will pay more than $200? That is endowment bias in action. The moment you own something, it magically becomes more valuable in your mind.
Machiavelli said it over 500 years ago: “Whosoever desires constant success must change his conduct with the times.” But here we are, centuries later, and most of us still prefer to just… not change anything.
So here is what happened: I read this chapter about self-control bias and immediately thought about every time I bought something I did not really need instead of putting that money into savings. This one hits close to home for pretty much everyone.
If loss aversion is the most damaging emotional bias, overconfidence is probably the most common one. And Pompian goes as far as calling it “one of the most detrimental biases that an investor can exhibit.”
We are now entering Part 4 of Michael Pompian’s book, and this is where things get really interesting. We are moving from cognitive biases (errors in thinking) to emotional biases. And the first one is a big one.
Imagine you are on a cruise ship. Over the entire trip, you see exactly the same number of green boats and blue boats. But most of the green ones pass by toward the end of the trip, and the blue ones are spread out earlier. When you get home, which color do you remember seeing more? Green. Obviously green. You saw so many of them.
Imagine a fund manager who concentrated her entire portfolio into 15 stocks, made two huge winning bets, had four terrible losers, and ended up beating her benchmark by 6% per year over five years. Impressive track record, right? Most investors would look at those returns and throw money at her.
“Heads I win, tails it’s chance.” That quote from researchers Ellen Langer and Jane Roth opens Chapter 14 of Pompian’s book, and honestly, it is the most perfect summary of self-attribution bias I have ever seen.
Quick question: what kills more people in the United States, shark attacks or falling airplane parts? If you said shark attacks, you are wrong. Falling airplane parts are actually 30 times more likely to kill you. But shark attacks are dramatic, they are all over the news, and they make great movie plots. So your brain says: sharks are clearly the bigger threat.
Yogi Berra once said: “You better cut the pizza in four pieces, because I’m not hungry enough to eat six.” It is funny because it is absurd. The amount of pizza does not change based on how you slice it. But here is the thing: when it comes to money and investing, people make exactly this kind of mistake all the time. They just do not realize it.
Let me ask you something. Is the population of Canada greater or less than 20 million? Now, without looking it up, guess the actual number.
Here is a question for you. You find $500 on the street. Same week, you get a $500 check from your mother as a gift. Is this the same money? Logically, yes. A dollar is a dollar. But here is the thing: most people will treat these two amounts completely differently. The street money? Easy come, easy go. Let’s spend it on something fun. Mom’s check? Better save it. She said it was for a rainy day.
David Beckham said “Hindsight is a wonderful thing.” Chapter 9 is the last of the belief perseverance biases in Pompian’s book, and it might be the most relatable one. Because we all do this. Every single one of us.
Abraham Lincoln said: “I claim not to have controlled events, but confess plainly that events have controlled me.” If Lincoln could admit that, why can’t most investors?
Colin Powell said it best: “Fit no stereotypes.” Chapter 7 of Pompian’s book is about representativeness bias, which is basically your brain using shortcuts and stereotypes instead of doing actual math.
Francis Bacon said it centuries ago: humans are “more moved and excited by affirmatives than by negatives.” Chapter 6 of Pompian’s book is about confirmation bias, and honestly, this might be the most dangerous bias in the whole book.
Warren Buffett opens this chapter with a quote about needing a sound framework for decisions and the ability to keep emotions from corroding that framework. Chapter 5 is about one specific way emotions corrode it: by making you too slow to update your beliefs.
You know that feeling when you buy something and then find out there was a better deal elsewhere? That little knot in your stomach? Congratulations, you just experienced cognitive dissonance.
Chapter 3 of Pompian’s book is short but important. It is the setup chapter. Before getting into 20 specific biases over the next 20 chapters, he wants you to understand what biases are, why they matter, and how they break down into categories.
Chapter 2 of Pompian’s book is basically a history lesson. But here’s the thing: it is a surprisingly interesting one. Because when you trace where behavioral finance came from, you realize that humans have been making the same stupid money mistakes for centuries.
There is a great quote at the start of this chapter. Meir Statman from Santa Clara University says: “People in standard finance are rational. People in behavioral finance are normal.” That one sentence pretty much captures the whole idea of this book.
I just finished reading a book that honestly changed how I think about investing. And I’ve been investing for a while now.
That is it. Twenty-nine chapters, seven parts, and around forty posts later, we are done with “Trading and Exchanges: Market Microstructure for Practitioners” by Larry Harris (ISBN: 0-19-514470-8, Oxford University Press, 2003).
This is the last chapter of the book, and Harris saved a spicy one for the end. Chapter 29 is about insider trading. You might think it is simple: insiders trade on secret info, SEC catches them, they go to jail. But Harris shows that the whole topic is way more complicated than that. There are actually serious economists who argue insider trading should be legal. Let me explain.
In Part 1 we looked at how bubbles form and crashes happen. Now the obvious follow-up: can we actually prevent this stuff? Or at least make it less painful? Harris walks through the tools markets use to deal with extreme volatility, and the picture is more complicated than you would expect.
This is the most dramatic chapter in the entire book. Bubbles inflate, crashes wipe out fortunes, and panic replaces logic. If you ever watched a stock chart go vertical and wondered “how does this end?”, Harris answers that question here. Spoiler: badly for whoever is holding the bag last.
Chapter 27 is a fascinating time capsule. Harris wrote this around 2003, when the debate between floor trading and electronic trading was still alive. The NYSE was building a new trading floor. The Chicago exchanges were still mostly pit-based. Reading it now, knowing how completely electronic trading won, is like reading someone in 1995 carefully weighing the pros and cons of email versus fax machines.
Should all trading in a stock happen in one place, or is it okay to have dozens of venues competing for your order? Chapter 26 is about exactly this tension, and honestly, it is one of the most relevant chapters in the whole book if you want to understand why modern markets look the way they do.
If you use Robinhood or any zero-commission broker, this chapter explains how the sausage is made. You pay zero commission, sure. But someone is paying your broker for the privilege of filling your order. That someone is a wholesale dealer, and the payment is called “payment for order flow.” Chapter 25 breaks down how this works and whether it hurts you.
The New York Stock Exchange used to have these people called specialists. Each one was assigned a handful of stocks and was basically the boss of all trading in those stocks. They stood at a physical post on the floor, saw every order coming in, ran the opening auction, and traded with their own money when nobody else would. One of the most privileged positions in finance. And one of the most controversial.
If you have money in a Vanguard or Fidelity index fund, or you buy SPY or VOO through your brokerage app, Chapter 23 is basically about you. Harris wrote this in 2003, but it reads like a prediction of what actually happened. Index investing went from a niche idea to the default way normal people invest. This chapter explains why.
This is the part of the book where Harris basically tells you that almost everything you think you know about picking winning traders is wrong. If Part 1 was about how hard it is to evaluate past performance, Part 2 is about why predicting future performance is nearly hopeless. And honestly, it is one of the most important chapters in the entire book.
Chapter 22 should be required reading before anyone picks a mutual fund, hires a money manager, or brags about stock returns at a dinner party. Harris basically proves, with math, that telling skill from luck in investing is almost impossible.
You know how every finance influencer tells you “minimize your trading costs”? Cool advice. But nobody tells you how to actually measure those costs. That is what chapter 21 is about. It turns out measuring transaction costs is surprisingly hard, and every method has problems.
Chapter 20 is one of the shorter chapters in the book, but it covers something every trader thinks about constantly: volatility. Why do prices move? Why do they sometimes move way more than the actual news justifies? Harris breaks it down into two types and explains why the distinction matters more than most people realize.
Everyone in finance talks about liquidity. Traders want it, exchanges advertise it, regulators worry when it disappears. Yet if you ask five people what liquidity actually means, you will get five different answers. Chapter 19 is where Harris finally pins it down. His definition is simple: liquidity is the ability to trade large size quickly, at low cost, when you want to trade. That is it. But the simplicity hides a lot of complexity.
If you are a big institutional trader at a mutual fund or pension fund, your daily problem is not “what to buy.” The portfolio manager already decided that. Your problem is how to buy it without the whole market figuring out what you are doing and trading against you.
We’ve just spent 38 posts deconstructing Larry Harris’s masterpiece, “Trading and Exchanges: Market Microstructure for Practitioners.”
In Part 1 we covered what arbitrage is, the different types (pure vs speculative), and how arbitrageurs keep prices consistent across markets. Sounds like easy money, right? Buy low here, sell high there, pocket the difference. This part is about why it is not that simple. Harris lays out four specific risks that make arbitrage genuinely dangerous, and he has some incredible real-world examples to prove it.
In the final chapter of “Trading and Exchanges,” Larry Harris looks at one of the most controversial topics in finance: Insider Trading. It’s the ultimate “informational advantage,” but is it actually harmful to the economy?
Chapter 17 is about arbitrageurs, and it is one of those chapters that changes how you think about markets. Arbitrageurs are the people who keep prices consistent across different markets and different instruments. Without them, you could have oil priced at 80 dollars in New York and 70 dollars in London, and nobody would fix it.
In the second half of Chapter 28, Larry Harris looks at what happens after the crash starts. When the market is in freefall, regulators have several “panic buttons” they can press to try and restore order.
Chapter 16 is basically the Warren Buffett chapter. Not that Harris mentions Buffett by name, but the whole idea of value trading is: figure out what something is really worth, wait for the market to misprice it, buy low, sell high. That is the entire philosophy in one sentence. The hard part is everything else.
Say you manage a pension fund and you need to sell 500,000 shares of some stock. You cannot just drop a market order on the exchange. The order book does not have that much liquidity sitting around. If you try to force it through, you will eat through every level of the book and crash the price on yourself. Chapter 15 is about how these giant trades actually get done.
In Chapter 28, Larry Harris looks at the scariest moments in financial history: Bubbles and Crashes. These aren’t just “volatility”; they are moments where the relationship between price and reality completely breaks down.
In Chapter 27, Larry Harris looks at the ultimate showdown: The Floor vs. The Computer. In an age of high-speed fiber optics, why do we still have people in colorful jackets yelling at each other in lower Manhattan?
In Part 1 we covered dealer spreads, the two spread components (transaction costs and adverse selection), and why uninformed traders lose no matter what order type they use. Now Harris finishes the chapter with equally important stuff: what determines equilibrium spreads in real markets, how public traders compete with dealers, and what factors predict whether a given instrument will have wide or narrow spreads.
In Chapter 26, Larry Harris looks at the high-stakes competition between the marketplaces themselves. If you’re a developer building an ECN or a regulator at the SEC, this is the battlefield.
Harris calls chapter 14 the most important chapter in the book. Bold claim for page 297, but he backs it up. The lesson is simple and painful: uninformed traders lose money no matter what they do. Not because they pick the wrong side. Because they trade at all.
In Chapter 25, Larry Harris explains why the stock market isn’t just one big room. It’s actually thousands of little private rooms all trying to steal business from the main floor. This is Market Fragmentation.
Dealers are merchants. They buy low, sell high, pocket the difference. If you ever bought a used phone from a resale shop, you understand the concept. The shop bought it for less, sells it to you for more. Financial market dealers do the same thing with stocks, bonds, and currencies.
So we made it. 17 posts later, and we’ve covered the entire “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann. That was a lot of ground.
So we made it through all 15 chapters of Behavioral Finance and Investor Types by Michael M. Pompian. Here’s what I think about the whole thing.
In Chapter 24, we go to the floor of the New York Stock Exchange to meet the Specialists. These aren’t just regular traders; they are members who have been given a specific job by the exchange: keep the market for your stocks “fair and orderly.”
This is the chapter where Harris explains how scammers work the stock market. Chapter 12 is about bluffers: traders who trick other people into bad trades so they can profit. If you ever wondered how pump and dump schemes actually function at a mechanical level, this is it.
This is a retelling of Chapter 14 (Conclusions) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
So we made it. 9 chapters, 17 posts, one brain that’s a little more aware of its own tricks.
This was “Investing Psychology: The Effects of Behavioral Finance on Investment Choice and Bias” by Tim Richards (ISBN: 978-1-118-72219-0, Wiley 2014). And it was worth every page.
This is it. Chapter 15 of Behavioral Finance and Investor Types by Michael M. Pompian is where everything comes together. All those chapters about biases, personality types, asset classes, and financial planning? They were building up to this. The final chapter answers the obvious question: okay, I know my investor type, now what do I actually do with my portfolio?
In Chapter 23, Larry Harris explores one of the biggest financial innovations of the last 50 years: Index Trading. Today, more money moves in index products (like the SPY ETF or S&P 500 futures) than in the individual stocks themselves.
Chapter 11 is about the shady side of trading. Harris introduces order anticipators: people who profit not by knowing what a stock is worth, but by figuring out what other traders are about to do and trading before them. They are parasites. Harris uses that word deliberately. No better prices. No liquidity. They just extract money from other people’s trades.
Theory is nice. But does behavioral finance actually work when real people sit across from real bankers with real money on the table?
We made it. Chapter 9 is the final content chapter of Tim Richards’ “Investing Psychology.” And it’s not really about new ideas. It’s a wrap-up. A summary. A last attempt to remind you what you should have learned, and why most of us will still ignore it.
In the second half of Chapter 22, Larry Harris digs into why that 5-star mutual fund you saw in a magazine might be a terrible investment. The industry is designed to hide the losers and highlight the lucky.
In Part 1 we covered the four types of informed traders: value traders, news traders, technical traders, and arbitrageurs. Now we get to the really good stuff. What happens when all these informed traders compete? How efficient do prices actually get? And why can markets never be perfectly efficient?
Chapter 14 of Behavioral Finance and Investor Types by Michael M. Pompian takes a step back from psychology and biases. Instead it asks a very basic question: do you actually have a plan? Not an investment strategy. Not a stock pick. A plan. Because financial planning and investing are not the same thing, and a lot of people confuse the two.
This is a retelling of Chapter 12 (Fintech) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
Chapter 8 of Investing Psychology is where Tim Richards takes everything from the book and turns it into a myth-busting session. Ten myths. All of them things most people believe. All of them wrong. Or at least, way more complicated than we think.
In Chapter 22, Larry Harris asks the million-dollar question: Are you a genius, or just lucky? Most people trade because they want to get rich quickly, but few realize that beating the market is one of the hardest things in the world.
Chapter 10 is where Harris gets into one of the most important ideas in the entire book: how certain traders actually make prices accurate. Not because they want to help society. They just want to make money. The price accuracy is a side effect.
Chapter 13 of Behavioral Finance and Investor Types by Michael M. Pompian is about the single most important investment decision you will ever make. Not which stocks to buy. Not when to buy them. It is about how you split your money across different types of investments. That is asset allocation.
Part 1 covered stocks and the basics of asset classes. Now in the second half of Chapter 12 of Behavioral Finance and Investor Types, Michael Pompian walks through the rest of the investment universe: bonds, hedge funds, real assets, and finally how to put them all together into a portfolio.
Previous: Chapter 6 Part 2
After six chapters of bad news about our brains, Chapter 7 finally gives us something we can actually use. Richards calls it “Good Enough Investing.” Not perfect investing. Not beat-the-market-every-year investing. Just good enough.
In Chapter 21, Larry Harris explains that the commission you pay your broker is only a tiny part of your total cost. For active or large traders, the Implicit Costs are where the real damage happens.
Here’s a question most people never think about. When you walk into a private bank and sit down with an advisor, what exactly is the process? Is there even a process? Or does the advisor just pick investments based on their own favorites and hope for the best?
Chapter 9 is one of those chapters you might be tempted to skip because it sounds theoretical. “Good Markets.” Sounds like an econ textbook subtitle. But Harris actually makes a case here that affects literally everyone, not just traders.
We continue with Chapter 6 of Tim Richards’ Investing Psychology. In Part 1, we covered the early debiasing strategies. Now we get into the harder stuff: why we can’t let go, why we fall in love with stocks, and whether “good enough” is actually good enough.
Chapter 10 of “Behavioral Finance for Private Banking” is where everything from the earlier chapters comes together. All the biases, prospect theory, loss aversion, mental accounting, it all converges here. Into one practical question: how do you figure out how much risk a client can actually handle?
Up to this point in Behavioral Finance and Investor Types, Michael Pompian has been talking about psychology, biases, and investor personalities. Chapter 12 switches gears. Now he lays out what you can actually invest in. Because knowing your own biases is great, but at some point you need to understand the tools on the table.
In Chapter 20, Larry Harris tackles Volatility. Most people see volatility as “risk” or “scary price swings,” but Harris breaks it down into two very different components.
In Part 1 we covered the “normal” reasons people trade: investing, borrowing, exchanging assets, hedging. Those are utilitarian traders who use markets to solve real-world problems. Now we get to the uncomfortable half. Gamblers, speculators, fools, and everyone in between.
Chapter 6 is called “Debiasing.” After five chapters of telling us how broken our brains are, Richards finally starts talking about what we can actually do about it. The short answer: there is no magic fix. But there are tools that help.
You’ve probably heard the standard advice. When you’re young, put your money in stocks. As you get older, shift to bonds. Simple. Clean. Fits on a napkin.
If the Preserver is the cautious tortoise and the Follower goes with the crowd, the Accumulator is the person at the poker table who shoves all in and stares you down while doing it. Chapter 11 of Behavioral Finance and Investor Types by Michael M. Pompian introduces the most aggressive of the four behavioral investor types.
In Chapter 19, Larry Harris breaks down the most overused word in finance: Liquidity. Everyone wants it, but very few people can define it.
Chapter 8 opens Part II of the book, and it asks one of those questions that sounds obvious until you actually try to answer it: why do people trade?
So you picked your ideal portfolio. Good stocks, some bonds, maybe real estate. Everything is balanced perfectly. Now what? Do you just sit there and never touch it again?
And that’s a wrap on “Hedge Fund Analysis” by Frank J. Travers.
Over the past 20 posts, we went through the entire book, from the history of hedge funds all the way to the final scoring model. Here’s what I think you should take away from all of this.
We continue with the second half of Chapter 5 from Tim Richards’ “Investing Psychology.” If Part 1 was about how the professional investing industry takes your money, Part 2 is about how corporations and your own trading habits finish the job.
In Chapter 18, we look at the world from the perspective of the Buy-Side Traders—the mutual funds, pension funds, and insurance companies that actually own the capital. For these players, every trade is a tactical battle over Order Exposure.
Chapter 10 of Behavioral Finance and Investor Types by Michael M. Pompian introduces the Independent. If the Follower from the last chapter was the passenger, the Independent is the person who insists on driving. And reading the map. And ignoring the GPS because they “know a shortcut.”
In Part 1 we covered what brokers do, different broker types, and how they make money. Now we get to the uncomfortable part: what happens when your broker does not have your best interests in mind.
Chapter 12 is the final chapter and it is where everything comes together. After all the sourcing, screening, interviewing, number crunching, operational checks, risk reviews, and reference calls, Travers shows us how to take all that work and turn it into a single, structured decision.
When we get sick, we go to a doctor. When something breaks, we call a professional. So when it comes to investing, we hand our money to financial experts. Makes sense, right?
Chapter 7 of “Behavioral Finance for Private Banking” is about structured products. If you’ve never heard of them, don’t worry. Most people haven’t. But by the end of 2007, there were more than 340 billion Swiss francs invested in them in Switzerland alone. That’s 6.5% of all assets under management. Over 20,000 different structured products listed on the Swiss stock exchange.
In the second half of Chapter 17, Larry Harris explains why being an arbitrageur isn’t just about finding a “money machine.” It’s a risky business that requires massive capital and perfect timing.
Chapter 9 of Behavioral Finance and Investor Types by Michael M. Pompian introduces the Follower. And honestly, this one probably describes more people than any other type in the book.
You open Robinhood, tap “Buy,” and 0.3 seconds later you own shares of Apple. Simple, right? But between your thumb tap and that trade actually happening, there is a whole chain of people and systems doing work for you. Chapter 7 is about those people. Brokers.
Chapter 11 opens with a Reagan quote, “Trust but verify.” That pretty much sets the tone. You have spent hundreds of hours doing investment, operational, and risk due diligence on a hedge fund. But have you actually checked whether the people running it are who they say they are?
In Part 1 we covered how groups and social pressure mess with your investment decisions. Now let’s get into something even sneakier: how language, trust, and social networks warp the way we think about money.
This is a retelling of Chapter 6, Part 2 (sections 6.7-6.9) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
Chapter 8 of Behavioral Finance and Investor Types by Michael M. Pompian introduces the first of the Behavioral Investor Types: the Preserver. And honestly, if you’ve ever been too scared to invest your savings because “what if the market crashes tomorrow,” this chapter is about you.
In Chapter 17, we meet the Arbitrageurs. These are the traders who make sure the world makes sense. If gold is $2,000 in New York and $1,990 in London, the arbitrageur buys in London and sells in New York until the prices match. They are the “price harmonizers.”
Chapter 6 is where Harris explains the actual machinery that matches buyers with sellers. If you ever wondered what happens between the moment you hit “buy” and the moment your order fills, this is the chapter.
This is a retelling of Chapter 6 Part 1 (sections 6.1 through 6.6) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
Chapter 7 of Behavioral Finance and Investor Types by Michael M. Pompian is where theory finally meets practice. After six chapters of background, frameworks, and definitions, you actually get to take the quizzes and figure out what type of investor you are. Two quizzes, to be specific.
Chapter 4 of Investing Psychology is where Tim Richards talks about something we all deal with but rarely notice: other people messing with our financial decisions. Not on purpose. Just by existing around us.
Chapter 10 opens with a Warren Buffett quote: “Risk comes from not knowing what you’re doing.” Hard to argue with that. Travers uses this chapter to walk us through the risk due diligence process, and honestly, some of the findings are pretty eye-opening.
In Chapter 16, Larry Harris introduces us to the Value Traders. While dealers provide “immediacy” for small orders, value traders provide “depth” for the massive moves. They are the market’s ultimate safety net.
In Part 1 we covered trading sessions and the main execution systems: quote-driven dealer markets and order-driven markets. Now let’s get into brokered markets, hybrid structures, crossing networks, and the information plumbing that holds everything together.
In Part 1 we covered the big picture of operational due diligence and why so many hedge fund failures trace back to operational problems. Now in Part 2, Travers lays out exactly what to check, what questions to ask, and then shows us a real example interview with the operations team at Fictional Capital Management (FCM).
Previous: Chapter 3 Part 1
We’re still in Chapter 3 of Tim Richards’ “Investing Psychology.” In Part 1, we covered how situations mess with your head. Now let’s talk about something even weirder: your mood, the weather, and why shouting “Fire!” in a theater is basically what happens during a market crash.
This is a retelling of Chapter 5 (Diagnostic Tests for Investment Personality) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
Chapter 6 of Behavioral Finance and Investor Types by Michael M. Pompian is where it all comes together. After two chapters on personality theory and personality testing, Pompian finally introduces the thing the whole book is building toward: his Behavioral Investor Type (BIT) framework.
In Chapter 15, Larry Harris takes us away from the public exchange and into the “Upstairs Market.” If you want to buy 500,000 shares of a stock, you don’t just dump a market order into your app—you’d move the price 10% against yourself before the order was half-finished.
Chapter 5 is where Harris gets into the actual plumbing. You know how in previous chapters we talked about types of traders and types of orders? Now we are looking at the arena where all that happens. Market structure. The rules, the systems, and the “who gets to trade with whom” part.
Chapter 4 covered the history of personality theory. Now in Chapter 5 of Behavioral Finance and Investor Types, Michael Pompian moves to the practical side: how do you actually test for personality? Because having a theory is nice, but you need a way to measure it. And that’s what this chapter is about.
Previous: Chapter 2 Part 2
You survived your own ego in Chapter 2. Good job. But here’s the problem. Even if you fix your overconfidence, your environment can still ruin your investing decisions. Chapter 3 of Tim Richards’ book is all about situational finance. The idea that the world around you pushes you into decisions you think are your own.
Chapter 9 is where Travers shifts from talking about investment analysis to something most people overlook: the boring operational stuff that actually prevents you from losing all your money to fraud.
Chapter 4 of “Behavioral Finance for Private Banking” is short but it hits hard. It asks one simple question: what is actually happening inside your brain when you make money decisions?
So I just finished walking through all nine chapters of Richard Wilson’s “The Hedge Fund Book.” And here’s what I think after going through the whole thing.
In the second half of Chapter 14, Larry Harris gives us the “cheat sheet” for predicting how wide a bid/ask spread will be. If you’re building a trading system or managing a portfolio, these are the variables that determine your “slippage.”
Every time you tap “buy” in your brokerage app, you are sending an order. But most people have no idea there are many different kinds of orders, and each one has very different consequences for your wallet. Chapter 4 is basically a field guide to all of them.
Traditional finance has this idea that money is the great equalizer. Doesn’t matter if you’re from Japan or Nigeria or Norway. We all want the same thing: good returns, low risk. Press a few buttons, buy some stocks, done.
In Part 1 we covered the basics and operations side of hedge fund FAQs. Now we get to the stuff that actually makes or breaks a fund in the real world: finding money and building a career. Richard Wilson collects the most common questions he gets about marketing, sales, and working in the industry. Let me walk you through what he says.
In Part 1 we covered the theory behind onsite interviews. Now Travers takes us inside the actual visit to Fictional Capital Management. This is where we get to see how all those interview techniques play out in a real (well, fictional but realistic) setting.
In Part 1 we talked about overconfidence, loss aversion, and the disposition effect. Now let’s keep going with the rest of Chapter 2. This part gets into emotions, Black Swans, mental accounting, and some practical ideas on how to not sabotage yourself.
Chapter 4 of Behavioral Finance and Investor Types by Michael M. Pompian takes a step back from finance entirely. Instead, it walks through the history of personality theory. Why? Because before you can classify investor types, you need to understand how psychologists figured out personality types in the first place.
In Chapter 14, we look at the Bid/Ask Spread. This is the most important number in trading because it’s the price you pay for Immediacy. If you want to trade right now, you pay the spread. If you’re willing to wait, you try to earn the spread.
In Part 1 we covered the players: buy side, sell side, brokers, dealers. Now Harris walks us through what they actually trade, where they trade it, and who makes sure nobody burns the whole thing down.
This is a retelling of Chapter 2 (second half) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
Chapter 9 of “The Hedge Fund Book” by Richard C. Wilson is basically one giant FAQ section. Wilson says his company gets over 150,000 emails a year, and a huge chunk of them ask the same questions over and over. So he put together the most common ones with answers. Smart move.
Chapter 2 of Tim Richards’ book is called “Self-Image and Self-Worth.” And the title tells you everything. This chapter is about how your ego quietly destroys your investment returns.
You have done the phone calls, crunched the numbers, analyzed the portfolio. Now it is time to actually show up at the hedge fund’s office and talk to people face to face.
Chapter 3 of Behavioral Finance and Investor Types by Michael M. Pompian is where the real meat starts. This is the catalog of all the ways your brain sabotages your investing. Pompian calls them “the building blocks” and splits them into two big groups: cognitive biases and emotional biases.
In Chapter 13, we meet the Dealers. Larry Harris compares them to any other merchant—like a car dealer or a grocer. They buy inventory at a low price (the Bid) and sell it at a high price (the Ask). Their product isn’t the stock itself; it’s Immediacy. They are selling you the ability to trade right now.
Chapter 3 is a guided tour of the entire trading industry. Harris warns upfront it’s packed with jargon. He also says you can skip it if you already know this stuff. But if you’re new to how markets work, this chapter is the map you need before going deeper.
Chapter 2 of “Behavioral Finance for Private Banking” is where the book gets really practical. This is where Hens, De Giorgi, and Bachmann lay out the specific mental traps that mess up our investment decisions. And there are a lot of them.
In Part 1 we looked at how to get portfolio data from 13F filings and started breaking down Fictional Capital Management’s long book. Now we continue with more portfolio metrics and, more importantly, the liquidity analysis that catches the fund manager in a contradiction.
So we made it through the whole book. Seventeen posts later, here’s where I stand on “Introduction to Private Equity, Debt, and Real Assets” by Cyril Demaria (3rd edition, Wiley, ISBN 978-1-119-53737-3).
Chapter 8 of “The Hedge Fund Book” by Richard C. Wilson is about governance. If that word already made your eyes glaze over, stick with me. This is actually one of the more important chapters, because it explains why hedge funds blow up and how simple oversight structures can prevent it.
This is Part 2 of Chapter 1 from “Investing Psychology” by Tim Richards. If you missed the first part, go read Chapter 1 Part 1 first. We covered how your senses trick you. Now we get into how your brain takes shortcuts and how other people’s behavior messes with your money.
In Chapter 12, Larry Harris introduces us to the Bluffers. If the Informed Traders are the data scientists, the Bluffers are the illusionists. They don’t have any real information; they just want you to think they do.
Before getting into theory, Harris tells stories. Chapter 2 walks you through real trading scenarios, from a regular person buying stock to a soybean processor hedging in the futures pit. Each story shows a different corner of the market.
Chapter 2 of Behavioral Finance and Investor Types by Michael M. Pompian opens with a quote I really like. Meir Statman from Santa Clara University said: “People in standard finance are rational. People in behavioral finance are normal.” That pretty much sums up the whole chapter.
After eight chapters of theory, Demaria drops a real case study on us. Not a made-up example. An actual deal. Advent International investing in Kroton Educacional SA, a Brazilian education company. This is where all the concepts from the book come alive.
Chapter 7 of “The Hedge Fund Book” by Richard C. Wilson gets into the big leagues. We’re talking about hedge funds managing $1 billion or more. What do they do differently? Why do they keep getting bigger while most small funds stay small? Wilson lays out ten best practices from giant funds and brings in two interviews to back it up.
Chapter 7 opens with two quotes. One from Bernard Madoff saying he can’t discuss his proprietary strategy, and one from George Soros about how it’s not about being right or wrong, but how much you make when right and how much you lose when wrong. That contrast alone tells you everything about why portfolio analysis matters.
Previous: Intro post
Chapter 1 of Investing Psychology is called “Sensory Finance.” And it starts with a punch to the ego.
In Chapter 11, Larry Harris introduces us to Order Anticipators. These are parasitic speculators. They don’t care about what a stock is worth, and they don’t provide liquidity. They just want to know what you are about to do so they can do it first.
Chapter 1 is where Harris lays out what this whole book is about. And honestly, even this intro chapter packs more useful information than most entire YouTube courses on “how to trade.”
This is a retelling of Chapter 1 (Introduction) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
Chapter 1 of Behavioral Finance and Investor Types by Michael M. Pompian opens with a Picasso quote: “I’d like to live as a poor man, with lots of money.” That pretty much sets the tone. We all want financial success, but something keeps getting in the way. And that something is usually us.
So I just finished reading this book called Behavioral Finance and Investor Types by Michael M. Pompian. And honestly? It messed with my head a little. In a good way.
So I just finished reading “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann. Second edition, published by Wiley in 2018. ISBN: 9781119453703.
This is the final chapter. Demaria wraps up the whole book by looking forward. Where is private equity going? What are the big risks ahead? And could the industry actually destroy itself by being too successful? Let’s go through it.
Chapter 6 of The Hedge Fund Book is all about due diligence. Basically, it is the homework you do before handing someone your money. And after Madoff, after LTCM, after Bayou, everyone agrees on one thing. That homework was not being done properly. This chapter shows what good due diligence looks like and what happens when people skip it.
At this point in the book, we have collected the basic info from the hedge fund manager, done an initial review, and had a phone interview. Now comes the numbers part. Chapter 6 of “Hedge Fund Analysis” by Frank J. Travers is about crunching performance data, and it is packed with formulas and statistics.
I just finished reading “Investing Psychology: The Effects of Behavioral Finance on Investment Choice and Bias” by Tim Richards. And I need to talk about it.
In the second half of Chapter 10, Larry Harris explores the economics of being “smart.” If you’re an informed trader, your life is a constant battle against competition and the paradox of your own success.
So I just finished reading “Trading and Exchanges: Market Microstructure for Practitioners” by Larry Harris. And I have thoughts.
This is one of those books that’s been sitting on finance reading lists for years. Published in 2003 by Oxford University Press (ISBN: 0-19-514470-8), it’s basically the textbook on how markets actually work. Not the “buy low sell high” stuff you see on social media. The real mechanics. How orders flow, why spreads exist, what dealers actually do, and why some traders consistently lose money to others.
Every industry has a chapter it would rather skip. For private equity, this is that chapter. Demaria titles it “Private Equity and Ethics: A Culture Clash,” and he does not hold back. Fraud, job destruction, fake philanthropy, and the long fight for transparency. Let’s go through it.
In Part 1, we watched Travers set up and begin his initial phone call with Jaime Williams from Fictional Capital Management. Now we pick up where we left off, with the conversation getting into the really meaty stuff: asset growth, liquidity, short selling, risk management, and the all-important question of what makes this fund special.
Chapter 5 of “The Hedge Fund Book” opens with a Muhammad Ali quote about suffering through training to become a champion. That sets the tone perfectly. Starting a hedge fund is not glamorous. It’s years of grinding before anything clicks.
If the market is a giant statistical calculator (as Larry Harris calls it), then Informed Traders are the data scientists providing the inputs. In Chapter 10, we look at the people who actually do the work to figure out what things are worth.
Private equity used to be the quiet kid in the back of the finance classroom. Small groups of rich people pooling money together to buy companies, fix them up, sell them. Nobody outside the industry really cared. That changed. PE firms got huge, went public, and started buying companies the size of small countries. Chapter 6 of Demaria’s book asks the obvious question: is private equity going mainstream? And if so, what does that mean for everyone involved?
You have done your homework. You read the DDQ, you looked at the presentation, you reviewed the monthly letters, and the numbers did not scare you away. Now what?
Chapter 4 of The Hedge Fund Book is called “The Shooting Star.” And the title tells you everything. Some hedge funds grow super fast, look amazing for a while, and then crash. Like a shooting star. Bright, quick, gone.
In Chapter 9, Larry Harris steps back from the “how” of trading to look at the “why.” Why should a regular person, who might not even own a single stock, care about whether the New York Stock Exchange has a central limit order book or how fast orders are linked?
You want to buy a company. Or at least a piece of one. How does that actually work? Chapter 5 of Demaria’s book lays it out in 7 steps. The whole thing takes 3 to 18 months depending on the deal. And really, the entire process boils down to one word: trust. Buyer and seller have to trust each other enough to make a deal happen. Let’s walk through it.
In Part 1 we looked at what a Due Diligence Questionnaire (DDQ) is and how Travers uses it to collect initial data on a hedge fund. In this second part, we cover the rest of the DDQ, the other materials you should request, how to analyze performance data, and one of the most useful free tools out there: SEC 13F filings.
Chapter 3 of “The Hedge Fund Book” by Richard C. Wilson is called “Hedge Fund Marketing Pro.” It opens with a quote that basically says there are three ways to raise capital: have rich friends, land early institutional allocations, or do hard work. That sets the tone for the whole chapter. No shortcuts. Just grind.
In the second half of Chapter 8, we meet the players who are actually trying to make a living in the arena. If trading is a zero-sum game, these are the people trying to take your money.
This is the final piece of Chapter 4. We covered venture capital, growth capital, LBOs and special situations before. Now Demaria walks us through the rest of the private markets universe: private debt, real assets, and a handful of other instruments that sit at the edges of the asset class.
So you have narrowed your list of hedge fund candidates. You ran the screens, looked at the charts, compared the numbers. Now what?
Here’s a stat that surprised me. A 2006 study by Capco found that more than half of hedge fund failures happen because of operational problems, not bad investment picks. Think about that. Most funds don’t blow up because the portfolio manager made a bad bet. They blow up because the back office was a mess.
In Chapter 8, Larry Harris drops a truth bomb: Trading is a zero-sum game. For every winner, there is a loser. If you want to make money, you have to trade with someone who is going to lose.
If venture capital is the glamorous part of private equity, LBOs are where the real money lives. According to Demaria, leveraged buyouts represent roughly 69% of all PE fund investments. This is the heavy machinery of finance, and Chapter 4 spends serious time explaining how it works.
Chapter 3 kicks off Part Two of the book, and this is where things get practical. We are done with the history lessons and strategy overviews. Now Travers rolls up his sleeves and shows us how to actually evaluate a hedge fund step by step.
Chapter 1 of “The Hedge Fund Book” by Richard C. Wilson kicks things off with the basics. And honestly, if you’ve ever wondered what a hedge fund actually is without getting a headache from finance jargon, this chapter does a solid job explaining it.
In the second half of Chapter 7, Larry Harris gets into the messy reality of the Principal-Agent Problem. You are the principal (the boss), and the broker is the agent. In a perfect world, they do exactly what you want. In the real world, they have their own bills to pay.
Chapter 4 is where Demaria gets into the actual strategies private equity funds use to make money. He starts with the one everyone has heard of: venture capital. The stuff that turns garage projects into billion-dollar companies. Or, more often, burns through cash and produces nothing.
If you aren’t trading for your own account on the floor, you’re using a broker. In Chapter 7, Larry Harris explains that brokers are more than just order-takers—they are the grease that keeps the wheels of the market turning.
The introduction of The Hedge Fund Book starts with a pretty bold question. What if you could sit down with 30 hedge fund veterans and just ask them everything? What if someone spent over $80,000 hiring professionals with 7 to 30 years of experience to share their best advice?
Chapter 1 gave us the history. Now in Chapter 2, Travers answers the big question: what actually is a hedge fund, and why would anyone put money into one?
So you want to know if a private equity fund is actually good? Turns out, that’s way harder than it sounds. There is no stock ticker refreshing every second. No public quarterly earnings call. You are stuck with imperfect tools and incomplete data. Welcome to Section 3.3 through 3.5 of Demaria’s book.
In Part 1, we covered the earliest roots of hedge funds, from Japanese rice traders to Karl Karsten’s statistical forecasting and Benjamin Graham’s value-oriented approach. Now we get to the person who took all those ideas and built something that actually changed Wall Street forever.
The preface of “The Hedge Fund Book” starts with Richard Wilson explaining why he wrote this thing in the first place. And honestly, his reason is pretty relatable. He read most hedge fund books out there over seven years and couldn’t find one that gave you straight, unfiltered advice from actual hedge fund managers.
In Chapter 6, we get into the “code” of the market. Order-driven markets don’t rely on a dealer to set prices; they rely on a set of rules. If you’re a developer building an exchange, these are your requirements.
So you have a bunch of big investors who want to put money into private equity but don’t want to pick companies themselves. What do they do? They hand their money to a fund manager and say “go make us rich.” Sounds simple. But the details of how that relationship works, how the fund manager gets paid, and what stops them from just enriching themselves at your expense? That is where it gets interesting.
Chapter 1 of Travers’s book opens with a quote from Mark Twain: “History doesn’t repeat itself, but it does rhyme.” And then Travers immediately proves it by describing a 1970 article from Fortune magazine that sounds like it was written yesterday. Hedge funds losing money, managers getting overconfident, regulators circling. That article is from 1970. Let that sink in.
In Chapter 5, Larry Harris explains that the market structure—the rules and the tech—is just as important as the orders themselves. It determines who has the power and who gets the profit.
I just finished reading “The Hedge Fund Book: A Training Manual for Professionals and Capital-Raising Executives” by Richard C. Wilson. And I wanted to share what I learned from it in a way that actually makes sense to normal people.
Here’s something most people don’t realize. If you have a pension, pay insurance premiums, or even have a retirement savings account, there’s a good chance some of your money is sitting in private equity right now. You didn’t choose it. Nobody asked you. But that’s how the system works.
There are somewhere between 8,000 and 10,000 hedge funds out there. Let that sink in for a second. Even if you had infinite money, how would you figure out which ones are actually good?
If you can’t personally stand on the exchange floor and shout your trades, you need orders. In Chapter 4, Larry Harris breaks down the different types of instructions you can give your broker and why the specific type you choose is the biggest factor in your success.
In part 1 we talked about how the US basically invented private equity. Now the question is: can everyone else just copy the homework? Demaria’s answer is basically “it’s complicated.” Europe tried to adapt the American model. Emerging markets are still figuring things out. And the results are… mixed.
In the second half of Chapter 3, Larry Harris dives into the different types of markets and the rules that keep them from turning into the Wild West.
I just finished reading “Hedge Fund Analysis: An In-Depth Guide to Evaluating Return Potential and Assessing Risks” by Frank J. Travers, and I want to break it down for you in a series of blog posts.
Chapter 2 of Demaria’s book opens with a fun question: is modern private equity a French invention? The word “entrepreneur” is French. The guy who basically created modern venture capital, Georges Doriot, was French. But he did it in America. At Harvard, not in Paris. That tells you something about where the conditions were right.
In Chapter 3, Larry Harris zooms out to give us the “big picture” of the trading industry. If you want to understand market microstructure, you first need to know who the players are and what they’re actually trading.
Chapter 1 of Cyril Demaria’s book opens with a story you probably did not expect in a finance textbook. Christopher Columbus. Yep, the guy with the ships.
In Chapter 1, we talked about the theory. In Chapter 2, Larry Harris gives us four stories to show how these concepts work in the wild. If you’ve ever wondered what happens behind the scenes of a “Buy” button, this is for you.
If you’ve ever wondered why prices move the way they do, or why some people seem to always make money while others lose, you’re looking for market microstructure.
You would think that a thing called “private equity” would be easy to define. It has two words. One means private. The other means equity. Should be simple, right?
I just finished reading “Introduction to Private Equity, Debt, and Real Assets” by Cyril Demaria (3rd edition, Wiley, ISBN 978-1-119-53737-3) and I wanted to share what I learned.
Have you ever wondered what actually happens when you click “buy” on your trading app? Most people think about the stock price or the company’s earnings, but very few understand the actual machinery that makes the trade happen.