Jim Simons: The godfather of quantitative finance

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In an age where the finance industry is being disrupted across the planet, it makes sense to talk about one of the pioneers of what we now know today as quantitative finance. The financial world is currently run by computer algorithms. Most of these algorithms have infiltrated the financial system to the point of ubiquity.

It was partly driven by technology that paved the way for investors to think of new ways on how to capitalize on it. One of those early pioneers was Jim Simons. He ran a company that’s been mostly driven by algorithms and perceived elusiveness that captivates even the most avid investor.

A man whose life has revolved around mathematics. When he started trading in his early 40s after he had left his successful academic career; it make sense to bring his own mathematical twist to it.

He left academia in 1978 and after 4 years of tinkering and testing out his models, he finally made the leap to start his own firm in 1982.

His flagship fund was named Renaissance Technologies. I am assuming he was inspired by the renaissance period between the 14th and 17th centuries, which is basically the foundation of our modern scientific and technological framework.

The Renaissance

Sir Isaac Newton

That period spawned scientists, philosophers, and artists who we might be familiar with through scientific notations and formulas; if we take a physics class for example.

It featured heavyweights such as Sir Isaac Newton, who was fundamental in classical physics at the time and still is today. A true genius in every sense of the word.

Nicolaus Copernicus

Nicolaus Copernicus was another notable scientist of that period who revolutionized astronomy. At the time that field of thought was heavily attached to theological reasoning.

Popes and their religious followers thought that the earth was at the center of the universe and everything revolves around it.

Through Copernicus’s mathematical models and discovery, he proved that concept wrong. It was a dagger in the religious community at the time. We should also take into consideration the power the church had at the time.

It was a pretty brave move that costed him to get ostracized.

Galileo Galilei

Lastly, Galileo Galilei was also another important figure who built on Copernicus’s earlier work and made lots of new discoveries in astronomy and other areas of natural science.

In summary, the main underlying theme of this period was a rebirth.

A new beginning that was detached from the antiquated physical laws laid down by early-age philosophers such as Aristotle, and Pythagoras for example.

Inspiration

Jim Simons saw Renaissance Technologies as a company that will bring new innovations to the field of finance. One of his main ideas was to remove humans from the equation and allow his entire system to be run by algorithms.

Algorithms that can interpret huge swaths of data and find patterns that the average investors couldn’t see.

While successful investors such as Warren Buffett relied heavily on the basic thinking framework of humans to solve investing problems and pick stocks.

Mr. Simons uses formulas to decipher the market. Over time his company outperformed the market. Since 1998 Renaissance’s Medallion Fund outperformed the market by over 66% percent annually without fees being taken into consideration.

If we should add fees into the equation it would outperform by 39%. His results eluded the market leaving pundits questioning if he has solved the age-old problem of profiting off of data.

Early Pioneers

Louis Bachelier

He wasn’t the first to think of applying mathematical knowledge to finance, we owe that to Louis Bachelier. Mr. Bachelier was considered the first person to have written a scholarly work on mathematical finance.

One of his most well-known works was his theory on stochastic models which we now call Brownian Motion.

Basically, the stochastic process is seen as a random walk on a graph.

If we should look across the financial landscape today and delve into the graphical representation of the markets. Most of it can be seen as a random walk. Mr. Bachelier basically tried to solve it or at least demystify the reasoning behind the market.

The Trident

Myron Scholes

His models were further built on by three very important figures to the overall industry, Fisher Black, Myron Scholes, and Robert Merton. Fisher Black and Myron Scholes collaborated on the famous Black Scholes model.

Fischer Black

That is so often used today to price options and other flavors of financial products in the derivatives market. If we should tie this into Jim Simons’ success, we can see that he was largely influenced by these paragons of finance at the time. A mere decade later he started his own firm to test his own theories.

Robert Merton

I should also give a note to Edward Thorp who was also influential in the field of mathematical investing. In his autobiography, most of his thinking derived out of probabilities and understanding chances.

The markets were usually seen as gambling houses. Even though it can still seem that way to skeptics, these men help to bring reasoning into the industry.

When other firms hired financial professionals fresh out of the ivy League, he hired scientists, physicists, mathematicians, and other professionals from fields of quantitative rigor.

This paid off pretty profitably over time. Fast forward to today’s era, quantitative trading has taken over the industry of finance and has spawned companies such as D.E Shaw which uses “ghost patterns” to predict the market.

Troubles

Even though Jim Simon’s career has been successful, like many fund managers, he had his fair share of troubles. In early September they were forced to settle a tax bill with the Internal Revenue Service (IRS) which is basically a watchdog when it comes on to taxes.

They settled on paying $6.8 billion in back taxes which stemmed from Renaissance tax treatment of basket options between 2005 through 2015. At the time this allowed Renaissance Technologies to convert short-term capital gains to long-term gains until July 2015 when the IRS finally gave close to the practice.

Peter F. Brown who is the CEO of Renaissance Technologies further elaborated on the subject in a letter sent to clients.  It basically gave portfolio managers “The ability to receive the value of appreciation in certain portfolios, but protected Medallion against declines in excess of the premiums it paid on the options,” he said. The situation is more nuanced than what is being discussed here and will be further ironed out in other proceedings.

During the financial meltdown of the mid-2000s, the company was not immune to the financial climate at the time. Their fund fell by almost 36.73 percent between May of 2007 and April of 2009, according to HSBC.

Renaissance all over again

Renaissance Medalion Fund grew over 77% in 2020. Yet again, pretty impressive returns. If money was the topic of this piece, I could’ve created an entire essay on the financials and what to make of it. From a technological perspective, we are seeing a shift in finance. Opensource technological tools are being available at our fingertips.

As a result of this, we are seeing the average investor who has the knowledge wants to create their version of Renaissance Technologies within their home or offices.

We are seeing different experiments being applied to the market. For example, certain firms are using machine learning to do natural language processing. Natural language processing can allow them to get a sentiment of the market. It is done through analyzing large amounts of textual data derived from websites, news blogs, forums. They will then allow the algorithm to automatically predict the market or gain a certain level of inference which might lead to profitability. It’s a pretty interesting concept.

Machine learning and cognitive computing – 3d rendering

Algorithmic trading is one of the methods that are popular these days. I am sure Jim Simons may have a plethora of knowledge on this topic. It is popular because it’s currently easier to create and test a model if you have the requisite knowledge.

Algorithmic trading allows you to basically automate your trading process based on deterministic rules programmed by the subject.

In summary, with all the innovation happening around finance from cryptocurrencies, decentralized finance, artificial intelligence, etc. They are all driven by mathematical algorithms.

That was introduced by ambitious men who thought differently about the methodologies and systems behind the market. Jim Simons along with others was pivotal in this introduction.

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