There is an investor who achieved much higher returns than Warren Buffett, Ray Dalio, Peter Lynch, George Soros, Charlie Munger & essentially all of the other great investors that you can think of.
Investor | Average Return |
Warren Buffett | 20% |
Ray Dalio | 13% |
Peter Lynch | 29% |
George Soros | 26% |
Charlie Munger | 20% |
Jim Simons | 66% |
This is not just over one or two years, this is over the past 31 years of consistently. If you invested $100 & were able to achieve a 66% return every year after 31 years that $100 would be worth $665 million. To regularly achieve something that high was unheard of until Jim Simons came along.
How Did Jim Simons Do It?
Jim Simons Strategy – Quant King
- Jim Simons relies on quantitative analysis to decide the trades he makes. He’s a numbers man. He was a math genius who got a Bachelor’s & Ph.D. in Mathematics when he was young. He used his maths skills to become rich. He used his math skills to break codes with the National Security Agency as well as teaching at MIT.
Fundamental Analysis
- Back in 1982 quantitative analysis was not a thing. People generally relied a lot on perception & homemade systems to trade. For the first two years, Simmons did just this. He used ordinary fundamental & technical approaches to trade in the market. A lot of it was based on intuition & instinct.
- He just likes the emotional side of trading & he wanted to find a way where you could almost guarantee that money would be made. Kind of like at a casino where the house is always going to profit because the odds are rigged in their favor. They don’t get emotional they just want you to keep playing. Simmons aspired to create a model like this but for trading in the stock market where if you just keep trading you’re guaranteed to win because the odds are in your favor.
“No models for the first two years like normal people do. We were extremely successful. I think it was just plain good luck. Nonetheless, we were very successful but this was a very gut-wrenching business. You come in one morning you think you’re a genius & next morning you come & you feel like a useless one.”
Jim Simmons
Strategy 1 – Find Anomalies & Profit
- To do this way Simmons needed a lot of data. For the quantitative analyst, data is key & he would gather information on everything.
“Whether annual reports, monthly, quarterly reports, the historic data itself, volumes. We take in terabytes of data a day.”
So, his team would gather all of this data backtrack it across history & search for anomalies. Where is this something consistently odd happening that I can profit from? Anomaly might be something like every time the date is leading into Christmas the stock would increase in price. Most investors would try explaining the reasons why Simmons did not care he just cared that the data showed it consistently happened & once he found the anomaly he simply would buy the stock leading into Christmas & sell after Christmas each time making a profit. Simmons would do this across thousands of data sets & search where the abnormalities were that he could benefit from.
Strategy 2 – Short-Term Trend Following
Secondly, he & his team would look for trends. This was an approach that worked very well in the early days of trading. The best place to go find trends back in the day was in the commodity market. Copper, Gold, Silver, Oil, etc. these things often follow the pattern. Here’s a typical example of the price data of a commodity for a year. We’ll say it’s Wheat. Simmons would zoom in on smaller time frames say 20 days & he would notice that the commodity is trending. Maybe it’s trending upwards because fewer farmers can sell during this time or trending downwards because of oversupply. As we said before Simmons doesn’t care about the reasons why, all he cares about is that it is happening & how he can profit. So, if it was trending upwards he would trade it & buy & it was downwards he could short it & make some profit on the way down. The system worked very well for him early on even though it sounded quite easy, but after a while, people started to catch on to this method & it became more obsolete.
“Years ago such a system would work, not beautiful but it would work. So, you’d make money, you’d lose money. It was a very vestigial system.”
Simmons would need to upgrade a strategy if he wanted to keep making money in the market or risk going fats.
Strategy 3 – Reversion-Predicting Signals
- In the book ‘The Man Who Solved the Markets’ Gregory Zuckerman stated that Medallion which is Simmons’s flagship fund that averages 66% return earned profits from trending & reversion predicting signals, especially one called Deja Vu. reversion in terms of trading is when the price of a particular stock will revert to the average or it will revert to a particular metric. Sometimes it will fall below the average, sometimes above but the job of Simmon’s team would be to profit from these fluctuations.
- For example, you would place a stock like Apple in the algorithmic model, then it would look at a bunch of different data points. Maybe, Revenue, Book Value, or PEG ratio. Next, it would start to look for patterns. Where would it see the same things happen over & over again where would you get that feeling of deja vu? Maybe, the model would spot their overtime. Apple generally has a price-to-book value of 43. Sometimes it will dip below, sometimes above. But the pattern would always reverse back to 43. Again Simmons would see this, he wouldn’t care about the reasons why, he would just know that it happens & he would take advantage of this pattern. His firm would simply make a trade when the price goes below 43, it reverts to 43 & he makes some profit. If it goes above 43 he could short the stock & they just keep doing this until the pattern changes.
Strategy 4 – Employ High IQ Doctors, not Investors
To create models that could take in such vast & complex amounts of data, then find patterns & then profit Jim would need to find a team of very smart people. The team helps solve complex trading algorithms. People with Ph.D. and Doctorate degrees top 1% of IQs people who can code. Instead of going for people on Wall Street & with finance backgrounds, Jim looked to universities.
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