One of the best articles that I’ve read in 2018 was a Bloomberg piece I opened while commuting in the subway on a rainy weekday.
Kit Chellel’s ‘The Gambler Who Cracked the Horse-Racing Code’ was simply breath-taking.
It chronicles the life of Mr Bill Benter, a swashbuckling horse-racing gambler born in Pittsburgh in the United States, who originally started as a professional blackjack player in the colourful casinos of Las Vegas.
According to the article, Benter created algorithms to win bets at horse races, which led him to win close to a billion dollars in terms of accumulated gains over his entire career in Hong Kong’s famous Jockey Club.
That’s truly phenomenal… and inspirational.
I don’t know about you, but I know it isn’t easy to consistently win horse-racing bets. It’s incredibly tough, and Benter effectively pioneered a quantitative horse-racing hedge fund that would deliver returns via a probabilistic and systematic strategy. He did this years before quantitative analysis became mainstream.
Benter has retired from the scene for some time, and has inspired a whole new industry in his wake:
‘By the time he moved back to Pittsburgh, he’d inspired others in Hong Kong to form syndicates of their own. In response, the Jockey Club began publishing reams of technical data and analysis on its website to level the playing field. With a little effort, anyone could be a systematic gambler—or mimic one. The odds boards at Happy Valley and Sha Tin were color-coded to show big swings in the volume of wagers on a horse, specifically to reveal whom the syndicates were backing.
The robo-bettors’ numbers have continued to proliferate. After Woods’s death, his children maintained his Hong Kong operation, but other members of the team went into business for themselves. And Benter spread the secrets of his success in various ways: He gave math talks at universities, shared his theories with employees and consultants, and even published an academic paper laying out his system. The 1995 document—“Computer-Based Horse Race Handicapping and Wagering Systems: A Report”—became a manual for an entire generation of high-tech gamblers.
Today, online betting on sports of all kinds is a $60 billion industry, growing rapidly everywhere outside the U.S., where the practice is mostly banned. The Supreme Court, however, may lift federal restrictions this year, and if it does, American dollars will flood the market, increasing liquidity and the profits of computer teams. Big names from the world of finance have taken notice.’
Since then, I’ve re-read the article seeking to learn what I can from Benter’s example and experience. Here are some of my takeaways:
Consider the costs of operations
Trading and investing are done best when they’re treated as businesses.
When entrepreneurs and businessmen analyse opportunities, they don’t just look at the potential profits. They always consider the costs of operations as they need to factor in that in their estimates to know if it’s worth to jump in. Working from potential revenue (aka the top-line) down to the net profit margin (aka the bottom-line) is what they do.
Similarly, investors planning their strategies must factor the costs of their operations; factors such as fees, transaction costs and taxes. All these are your costs of admission to the game. Some investment activity may not seem that profitable or worth the effort after factoring the costs.
This is what Benter did when he started playing the races in Hong Kong:
‘Hong Kong racing uses a parimutuel (also known as “totalizer”) system. Unlike odds in a Vegas sportsbook, which are set in advance and give a decisive edge to the house, parimutuel odds are updated fluidly, in proportion to how bettors wager. Winners split the pool, and the house skims a commission of about 17 percent. (After costs, the Jockey Club’s take goes to charity and the state, providing as much as a tenth of Hong Kong’s tax revenue.) To make money, Benter would have to do more than pick winners: He needed to make bets with a profit margin greater than the club’s 17 percent cut.’
Find edges that you can exploit
Edges are either (i) behavioural, (ii) informational, (iii) analytical or (iv) technical in nature. All successful investors have one or a combination of these edges in order for them to take money out of the financial markets.
Is there something you know that others don’t? Do you have a superior way of understanding that others don’t? Do you have a stronger psychology and emotional temperament than others? Do you have privileged access or devices that allow you to operate in a way that others can’t?
Our professional horse-racing gambler worked hard to build his edges as stated in the article:
‘Benter’s model required his undivided attention. It monitored only about 20 inputs—just a fraction of the infinite factors that influence a horse’s performance, from wind speed to what it ate for breakfast. In pursuit of mathematical perfection, he became convinced that horses raced differently according to temperature, and when he learned that British meteorologists kept an archive of Hong Kong weather data in southwest England, he traveled there by plane and rail. A bemused archivist led him to a dusty library basement, where Benter copied years of figures into his notebook. When he got back to Hong Kong, he entered the data into his computers—and found it had no effect whatsoever on race outcomes. Such was the scientific process.’
Once you have positive edges, you need to exploit it ruthlessly and continue to refine them and build new edges. Without edges, you’re relying on lady luck for success.
What are some of your proprietary edges for your investment strategy?
For a fully systematic strategy, nothing beats the live-tests
Benter and his ex-partner, Alan Woods, would constantly adjust fire when building their probabilistic model. The article mentioned that the duo worked together make their system more robust:
‘Twice a week, on race days, Benter would sit at the computer and Woods would study the racing form. Early on, the betting program Benter had written spat out bizarre predictions, and Woods, with his yearlong head start studying the Hong Kong tracks, would correct them. They used a telephone account at the Jockey Club to call in their bets and watched the races on TV. When they won, there were satisfied smiles only. They were professionals; cheering and hooting were for rubes.’
A systematic strategy that is created out from a complete back-test without deliberate filtering, refining and thoughtful testing of historical assumptions may not be robust for the future. This is the reason why you hear of quants out there who blow up from time to time – their strategies and models could simply be too overfit to a certain market regime or conditions.
If you’re interested to know what this process is like, check out Chris Dover’s work. Here’s one of his recent tweets.
What other participants expect matters
Over the years I’ve realised that it takes time for people who are new to the game to understand this. Most investors just starting out attempt to win in markets by looking at whatever they think is useful, analysing and then proceeding to make a judgment.
However, there are many other investors and sophisticated players who are doing the same thing. And these people collectively act upon what they understand, and that drives asset prices in markets.
This implies that if you want to understand how things eventually move, you can’t just look at things on the surface. You need to think deeper, and factor in what your peers and the crowd at large are thinking. Oaktree Capital’s Howard Marks calls this ‘Second-Level Thinking’.
The article talked about how Benter improved his model when he encountered the public betting odds at Happy Valley Racecourse:
‘A breakthrough came when Benter hit on the idea of incorporating a data set hiding in plain sight: the Jockey Club’s publicly available betting odds. Building his own set of odds from scratch had been profitable, but he found that using the public odds as a starting point and refining them with his proprietary algorithm was dramatically more profitable. He considered the move his single most important innovation, and in the 1990-91 season, he said, he won about $3 million.’
It may not be the same thing in financial markets, but knowing what others believe could happen is essentially trying to understand the ‘public odds’. Before you make an investment, have you ever considered what the average participant is thinking about what the average participant is thinking and doing?
Getting position sizing right is crucial
‘Between races, Benter struggled to make his algorithms stay ahead of a statistical phenomenon called gambler’s ruin. It holds that if a player with limited funds keeps betting against an opponent with unlimited funds (that is, a casino, or the betting population of Hong Kong), he will eventually go broke, even if the game is fair. All lucky streaks come to an end, and losing runs are fatal.
One approach—familiar to Benter from his blackjack days—was to adapt the work of a gunslinging Texas physicist named John Kelly Jr., who’d studied the problem in the 1950s. Kelly imagined a scenario in which a horse-racing gambler has an edge: a “private wire” of fairly reliable tips. How should he bet? Wager too little, and the advantage is squandered. Too much, and ruin beckons. (Remember, the tips are good but not perfect.) Kelly’s solution was to wager an amount in line with the gambler’s confidence in the tip.
Benter was struck by the similarities between Kelly’s hypothetical tip wire and his own prediction-generating software. They amounted to the same thing: a private system of odds that was slightly more accurate than the public odds. To simplify, imagine that the gambling public can bet on a given horse at a payout of 4 to 1. Benter’s model might show that the horse is more likely to win than those odds suggest—say, a chance of one in three. That means Benter can put less at risk and get the same return; a seemingly small edge can turn into a big profit. And the impact of bad luck can be diminished by betting thousands and thousands of times. Kelly’s equations, applied to the scale of betting made possible by computer modeling, seemed to guarantee success.’
Benter used the famous Kelly Criterion as a heuristic to size his bets that his system generates. This is an edge for him over the years at Jockey Club.
The more I learn about investing, the more I’ve realised that position sizing is an underrated and under-focused topic about the investment process. It’s obvious. A losing position sized too large could be detrimental in a portfolio, while a winning position sized too small is a huge opportunity cost to long-term success.
Figuring out and managing the fine line between both scenarios and what will work according to your strategy and circumstances may be the key to compounding money successfully for the long haul.
*Image credits to Bloomberg*