About book Fortune's Formula: The Untold Story Of The Scientific Betting System That Beat The Casinos And Wall Street (2006)
This is a very interesting book and one that explains complicated mathematical and economic ideas beautifully and simply. It is a story that involves gangsters, mathematicians, the founder of information theory, more gangsters and politicians and police (both corrupt and, well, even more corrupt). The formula to make a fortune is essentially this – if you are going to bet you need to be sure you have some sort of edge (not necessarily a ‘sure thing’, but an edge), in this book the gamblers generally count cards or find roulette wheels that are slightly off balance or stock they believe has been under or over priced. Then you place your bets according to how certain you are of winning and in a way that also covers you for ALL eventualities. So, if you are betting on a horse race you would bet on all of the horses running in that race according to how well you believe each might go.And this is the problem – because you are spreading your bets so widely you need to have a pretty good ‘edge’ to make any money. Generally, in betting situations, the person with the edge is either the house or the stockbroker. No matter if the horse or stock wins or loses, they take their cut.The book discusses people who have done very well from the stock market and betting on horse races and some of them have done so over a great number of years and despite the market either racing up or falling on its face. All this is very interesting. As one guy says, he has found the perfect method to ‘get rich slow’. So, why am I not taking out lots of money from my bank account or borrowing heaps so I can leverage my bets on stocks or my investments in blackjack? Because there are other just as compelling arguments made in the book that fortune’s formula (aka Kelly’s formula) doesn’t really work. Let’s say you have proof that someone has beaten the market for 20 years by 5% (people discussed in this book have done better than this) – does that prove their theory true? We like to think so. But does it? The problem is a form of selection bias. As soon as someone fails we know their theory doesn’t work, but how long does it take to know that someone’s theory will never fail? There is a universal law associated with this – any investing strategy will be certain to fail the moment I put money into it. My service to the world is to not invest.The things that put me off this formula – besides the major inconveniences of having to spend hours and hours of my life studying things like the stock market or horses – was where he showed that you are 1/3 likely to half your money before you double it – whoo-hoo. I’m not a gambler precisely for that reason. Like nearly everyone else in the world, I’m loss averse, but unlike so many of you I find no joy in even a ‘little flutter’.Some of the cameo appearances in this book are really what make it – everyone from J Edgar Hoover to Paul Newman have walk on roles and these are often very amusing. I loved the gangster who complained about the number of horse races he had to fix to buy off Hoover. The descriptions of casinos in the 1950s in the US – particularly if you had the audacity to actually win in them – was compellingly frightening. Not unlike The Godfather movies. But the most interesting thing was something I never knew at all. Do you know in 2001 where HAL is having his brain slowly shut down and he reverts to his childhood? (If not, stop reading this review now and borrow the film – it’s ok, I’ll wait) Back yet? Well, he sings a song – Daisy Bell or A Bicycle Made For Two – and what I didn’t know was that this was the first song a computer ever sung. The idea behind getting a computer to sing a song is really interesting too. You see, if you get a computer to say a sentence like this one it needs to be clear what it is saying or the listener won’t have a clue. But it is like listening to someone with an unfamiliar accent – at first you can’t understand a word, but it gets better as it goes along. The guy programming the voice is very familiar with it – so can understand what it is saying, but probably not the person who is first introduced to the computer voice. Programmers got around this by having the computer sing popular songs and because we know what is coming next we basically ‘help the computer along’. Sorry, need to stop soon, but have to say this – this is the inverse of another test I find very interesting. They get people to sit opposite each other and they give one of them a pencil and that person has to tap out songs they know – no humming or singing along, just tapping the pencil to the tune of the song. Then they ask the person who is doing the tapping how confident they are that the person listening will be able to guess the song – generally people say they are very confident. After all, they have the tune with full orchestration and four part harmonies playing in their head. People are generally outraged when the person listening can’t guess the song, even more so when they guess seemingly completely random songs. I did this in a class this year and it was really fun. I asked a kid to tap out the Australian National Anthem and I think someone guessed it was happy birthday – you should have seen the kids face who had done the tapping.Much the same argument is made in this book as in Fooled By Randomness – that is, if you are going to bet you need to expect the improbable, because the improbable is never as improbable as you might like to think. In maths talk – 20 sigma events happen all the time. You’d better be prepared for them. Good luck with that.
I enjoyed this book so much that I bought the book! (I was reading a copy I checked out from my library.) It never failed to amaze me how many smart people ended up using their brains for cheating the system. The book talked about how telecom was advanced thanks partly to horse betting, that many bettors were trying to cheat their bookies. Gambling then led to invention of "fortune formula" which calculated the odd of winning and how much bet should be placed given the odd. Soon after the formula was lent to much of the investment world.I found the story to be quite fascinating. May be it's in human nature to beat the system, especially when the reward seems so tempting. One part in the book sums it all for me:In a 1984 speech, [Warren] Buffett asked his listeners to imagine that all 215 million Americans pair off and bet a dollar on the outcome of a coin toss. The one who calls the toss incorrectly is eliminated and pays his dollar to the one who was correct. The next day, the winners pair off and play the same game with each other, each now betting $2. Losers are eliminated and that day's winners end up with $4. The game continues with a new toss at doubled stakes each day. After twenty tosses, 215 people will be left in the game. Each will have over a million dollars. According to Buffett, some of these people will write books on their methods: How I Turned a Dollar into a Million in Twenty Days Working Thirty Seconds Morning. Some will badger ivory-tower economists who say it can't be done: "If it can't be done, why are there 215 of use?" "Then some business school professor will probably be rude enough to bring up the fact that if 215 million orangutans had engaged in a similar exercise, the result would be the same--215 egotistical orangutans with 20 straights winning flips."The bottom line is that you can win big, but you are also bound to lose at some point... whenever that may be. You must be prepared and know that it's the fact. Most people think they can beat the odd, bet all, and lose big. It's a great little book, and I can't wait to read it again!
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Very interesting account of Kelly Criterion, which has as its backdrop the dawn of the computer age and development of information theory. Computers made possible a deeper and more accessible understanding of probability than was available before, an example of which was solving of the odds of blackjack.For investors, the most interesting thing in the book is the treatment of geometric versus arithmetic returns. Basically, the Kelly Criterion suggests a way to think about sizing investments according to perceived edge and risk, and investors who think about investment decisions this way may be better positioned to compound wealth over many periods and after many individual investment decisions (geometric return). In contrast, the mean-variance parameters of modern portfolio theory apply to one period optimizations for expected (arithmetic) return (that period could be one year, or the rest of your life). MPT also assumes markets are efficient and there is no information edge, only an optimal portfolio allocation determined by investor's risk tolerance and required return.Presented, however, with the dynamic and evolving set of investment opportunities, and with plenty of inefficiencies in the market, thinking in terms of maximizing the return and minimizing drawdown potential of each decision makes more sense to me than a static one period optimization.
—Bryce
As an MIT math major who worked in finance, this is the only non-technical book I have ever read that tells the true story of how to think about finance. If you are curious about making the first steps into understanding the "real" world of finance, the one that high-powered hedge funds continue to use (albeit in far more advanced forms) this is a great place to start. However, Fortune's Formula isn't a textbook; it's a story with a technical backdrop. You'll learn some conceptual math, but mostly you'll learn the story behind scientific thinking in the world of finance, a story gangsters, gambling, white collar crime, and some of the smartest people who ever lived. The world of investing books is rife with various degrees of BS ranging from naive garbage to outright lies as well as volumes of dense, dry tomes of dubious value. This book is probably the most truthful and readable exception to those rules that exists.
—Luke Schiefelbein
I started and quit this book a while back. I picked it up again after reading "Trading Bases" because I remembered that it offered an explanation of the Kelly betting strategy. I think the reason that I didn't like it the first time was twofold: 1) The Kelly criterion seemed over-simplified and maybe even wrong; and 2) I had nothing to apply it to at the time. Now that I understand it, and have more active interests in investing (and possibly building a betting model for baseball), it is more alluring. The book covers the 20+ people that were involved in coming up with, critiquing, and arguing against the Kelly criterion; in fact, it was too many people to keep up with and made many of the personalities blur together. I would have liked more about the theory and its practical applications and less about the myriad of people that were peripherally involved. However, it still keep my interest and I enjoyed it on my second try.
—Douglas Cosby
