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.