James Harris Simons (April 25, 1938 – May 10, 2024) was an American hedge fund manager, investor, mathematician, and philanthropist. He was the founder of Renaissance Technologies and the Medallion Fund and also known as the “Quant King”. He was very well known for his fund performance and stability as well as early adoption of quantitative approaches on trading. His approach on quantitative trading that had been wildly successful internally should be carefully reviewed by any traders who want to make a career in applied computational finance known as quantitative trading, algorithmic trading and high frequency trading.

Collected from Simon direct interview as well as credible source of information, this article aims to provide key insights of the “quant king” ’s career development. 

Key Insight 1: Basic Science Is the Core

Perhaps, with a top-tier background in science, who developed the Chern–Simons form (with Shiing-Shen Chern), and contributed to the development of string theory, Jim Simons prefers to work with the brightest scientist in natural science. This approach differentiates Jim Simon with the ordinary approach of focusing on top players in financial or technological markets. As a quant fund operates in the financial market utilizing the power of computing systems, people often classify themselves as fin-tech corporations which directly imply key players as either fin or tech experts. 

Jim Simons didn’t move along with the traditional thoughts. He believed in the ability of discovering new patterns in finance as a similar skill set in natural science. Thus, a great scientist in natural science should be a great candidate for his firm. That is the reason why he is looking for physicists, mathematicians, astronomers and computer scientists while finance knowledge is not even a requirement.

Key Insight 2: Give Smart People Freedom and an Environment for Interaction

"My algorithm has always been: you get smart people together and you give them a lot of freedom. Create an atmosphere where everyone talks to everyone else. Provide the best infrastructure. And make everyone partners. That was the model that we used in Renaissance." This may be the fuel behind the secret of RenTech long term growth. 

Simons also elaborated further with the concept of “smart” in his view as having a PhDs in natural science with at least 5 years of experience and a couple of good papers. This belief was that if one can do well in discovering patterns in nature then one can replicate that concept in the financial market.

Simons also gives a clear example of some projects that he funds enough for some members for a 5-year period without knowing clearly what they are going to do in the coming future. 

Key Insight 3: Huge Data Set, Best Infrastructure, Life-Long NDA and 100% Automation

Any good algorithm will deplete after a 5 years period so what is the long-term competitive advantage of RenTech?

First, it is a huge data set which contains basic data such as financial information and market data. Alternative data such as weather, temperature, humidity, wind speed is also collected. In fact, any data set that happens in the real time is collected if collectable. One may not know the reason why a data set is valuable until a connection is found.   

Second, infrastructure is a must. Without the best infrastructure, no algorithm, model or pattern can be utilized to its fullest. Continuous investing in the best infrastructure in the trading industry is one of key competitive advantages of RenTech. In the modern time, infrastructure is the most difficult barrier for new players to come into the field. 

Third, a life-long NDA is a requirement for all members of RenTech. This is due to the nature of unpatentable of any finding. Simons said as long as one algorithm is patent then there will be many people finding a way to go around the algorithm. So this is the nature of this industry for having no patent on algorithms at all.

Lastly, fully automation in any circumstances so no emotion and no interference may happen at any time. This approach increases the credibility of the system that all members know that no one can make trading decisions but the system only.

Controversial 

The Medallion Fund, which is exclusively available to internal members of RenTech, had been performing greatly. According to Gregory Zuckerman's book, its annual return was 62% before fees from 1988-2021. Though, the fund that was available to external investors was not even beating the SPY. Until 2020, the annualized return of the Renaissance Institutional Equities Fund (RIEF) was only 8.05 percent in comparison to 9.6 percent of SPY. The same pattern happened similarly in other external funds that were managed by RenTech.

Also, "Renaissance Technologies was able to avoid paying more than $6 billion in taxes by disguising its day-to-day stock trades as long term investments," said Sen. John McCain, the committee's ranking Republican, condemned Simons in the use of complex financial structure to shield short-term capital gains as long-term capital gains. In September 2021, it was announced that Simons and his colleagues would pay billions of dollars in back taxes, interest and penalties to resolve the dispute.

For many elite traders, Jim Simons is the one who did quant when there is no quant in the world. His lifelong career which lasts until now after his life comes to an end may be a message for those who want to pursue a career in applied computational finance. Whether you believe in it or not, a smart scientific team with freedom and a supportive environment for interaction with the best tool is the best algorithm by Jim Simons.