Strategy De Rerum Natura
What Renaissance Hedge Fund Can Teach Us
Math explains nature says Neil deGrasse Tyson, and “I think; therefore I am,” says Rene Descartes. There can be no doubt about that. This is On the Nature of Things, the nature of the universe, and mathematics is visible everywhere in nature. The nature of things explains the laws of physics, how the cosmos works, how things curve, how patterns form and why things are. Math is in both the physical and the metaphysical. Even what we see as beauty can be explained by math — those geometric shapes in nature.
Too often we are fooled by randomness, not understanding the beauty and opportunity in volatility. Which is just the nature of things. So strategy harnesses opportunity for us to thrive.
According to the ancient Roman poet and philosopher, Lucretius, De rerum natura or On the Nature of Things. His writings tell us how the world became modern. It’s Renaissance swerve. So our existence and change in this world is an unpredictable swerve that occurs at no fixed place or time. That our universe is nothing more than atoms moving and colliding in space and time.
And this is how nature creates things. We are carbon, nothing special, void of any meaning and the universe neither knows who we are nor cares about us. There is nothing divine or deterministic about our humanity, it’s just nature in which we take up space and exist in random uncertainty.
It is up to us to deal with nature, in our time and place in the universe, to develop our strategies to find our way and to thrive in it. So our outcomes are dependent on the strategies we build and the decisive actions we take.
Solving the Market, First
Jim Simons, founder of hedge fund Renaissance Technologies LLC, the most successful hedge fund in history. So what can we learn from Jim Simons’s Renaissance success? What type of swerve did it take to consistently outperform the market? To achieve average annual returns close to 40% over the past 30 years? The Renaissance Medallion Fund has been averaging staggering annual returns since 1988. Making millionaires and billionaires out of many.
The easy story to believe is that Simons is a genius but he wouldn’t say that, because there are no secrets to the extraordinary success of his team. An adherence to math is the necessary scientific process that the universe requires you to do. Understanding the laws of nature and that math is your best utility to getting good explanations and insights. Effectively, Simons established a curious drive and business culture to connect the dots to construct trading systems that run on data-driven insights.
Recognizing patterns that can bring clarity to complexity to drive valuable insights that can be leveraged to build effective investment strategies, is the swerve.
Effective strategy through data, harnessed to a defined decisioning framework using applied intelligence has proven effective to Renaissance.
From the founding, Simons pursued academics and algorithmic trading strategies first and foremost, and not star fund managers and personalities. Effectively staying away from the emotional ego-driven noise that comes with humans.
Simons, an academic and world-renowned mathematician himself, made the career shift, the swerve, to the investment world and started his hedge fund at the age of 40. But unlike most industry upstarts, Simons decided to focus on using math to generate strategies for performance, first. Staying away from human-driven investment philosophies.
The mathematical way sought to solve the market first, with data-driven strategy and performance before looking to grow assets under admin (AUM). Which is the traditional approach for investment manager firms to take.
Renaissance created an authentic system and culture that focused on math to sort things out and find the patterns in nature to solve the market without human interference.
Like Lucretius, Simons too may have understood the universe as a series of random events, so the goal was simple, make clarity out of randomness and complexity using math to decipher. And when you get through the fog of complexities you begin to see more clearly over the horizons of opportunities. Providing confidence to take decisive actions. Such a strategic approach to investing allows one to identify the objective truths, and then design the necessary trading strategies out of the whitespace. To capture big profits.
What makes Renaissance Medallion Fund different from other hedge funds, is its intellectually humbled approach to investing. It’s resigned to the nature of the universe. The management culture fosters learning and collaboration with a shared sense of mathematical purpose, believing that the scientific way has proven most effective and reliable.
So the swerve, the renaissance, was algorithmic investing coupled with big data analysis, the most optimal path and the one taken by Renaissance Technologies.
Using data-driven models avoided the flawed method that comes along with human-dominated investment decisions.
Commonsense, however, informs us that humans can’t ever process thousands or millions of data points like the awesome processing power of machines can. So a massive custom-built database relevant to their investment objectives was created to draw insights from and continually add new information. To build reliable and warrantable fact-based decisions. That system itself is the advantage.
The automated data ecosystem rigorously sorted information, cleaning and validating, finding patterns and providing useful investment insights with accuracy and consistency.
Allowing Renaissance to find anomalies, activating predictive models and strategies when patterns and trading sequences of opportunities appeared. However, the first principle of performance first was the overriding strategy!
The unwavering objective of Simons was that math explained the nature of things, therefore, randomness was the canvas to solve the market.
The story of Renaissance Technologies, unlike most hedge funds that focused on bigger, is better, the pursuit of significant AUM growth first. Simons focused instead, on the strategy-for-performance. And the more Renaissance solved the market the more AUM was gained.
Despite the many data-driven quantitative investment managers that popped up after Renaissance, trying to copy, few could match the level and return consistency. Many tried to replicate his system but misunderstood Simons’s authentic commitment to a learning and thinking culture.
So regardless of the new quantitative investment disciplines that emerged, managers were still traditional AUM hunters first. Jim Simons and the team were unmatched masters of their domain because they focused On the Nature of Things. Strategy is fundamental!
The Curious Case of Long-Term Capital Management
Let us look at the curious Case of Long-Term Capital Management (LTCM). Another hedge fund and the ideal example of an investment manager fail. To illustrate the reasons why you cannot ever circumvent the nature of things, and how ego-driven applications can lead to major blow-ups.
Unlike Renaissance, LTCM was neither authentic nor intellectually humble, it was not about learning but more about showing how smart they were. With nice pure mathematics-type investment models, putting their Nobel Prize-winning credentials out front in front. With elegant math as the hook to getting AUM.
LTCM was founded in 1994 and led by two Nobel Prize Laureates and other leading economists, who were referred to as “geniuses,” which they traded on too of course. LTCM used ego driven complex mathematical models to drive huge returns, or so it seemed.
LTCM operated at a highly leveraged position of 25:1; $25 of debt for every $1 of capital. Without any formal financial training, common sense alone should tell us that things may not be tenable with these types of ratios.
So, as things go, in August of 1998 the fund lost 44% of its value overnight. There was so much money lost back then, and so quickly, that the impact led to the Federal Reserve intervening and gathering 11 other banks to bail out LTCM at US$3.65 billion.
The liquidity crisis pushed LTCM’s leveraged positions to reach astonishing levels: 250:1. So the fund became increasingly fragile, and more vulnerable to unpredictable shocks.
It was a powder keg waiting for the spark to be lit; and along came the Russian liquidity crisis. Pow!
So for all the ‘genius’ accolades and Noble Prizes, there were elementary errors in judgment made when it came to their math. Inherently driven by ego and the belief that self-created artificial methods could get around or fool the nature of things. LTCM strategy was designed around a predictive mathematical, computer-driven investment model which ran by imputing infinite amounts of variables/data and receiving outputs to execute the trades.
In short, they figured they could corner the universe on data, cover all their bases and win every time. Hubris!
However, they forget that no model is absolute. Forgetting basic math/calculus rules, particularly, forgetting about the mighty independent variable. So regardless of how many dependent variables you throw at a model, the mighty independent can appear and crash the party, changing the outcome at a moment’s notice.
Accordingly, the LTCM model didn’t account for shock events, so the model was left vulnerable and fragile. The Russian liquidity crisis did it in. And just like that they were gone.
The lesson about LTCM is that despite its Nobel Laureates, star traders and mathematicians, they still failed because they failed De rerum natura.
As mathematician Sofia Kovalevskaya tells us, “Nonlinearity places limits on human hubris.” The natural world is random and uncertain, that’s what makes it the world, so models, in the end, can’t predict, they are just working theories that you may be able to gather useful insight from.
No risk can ever be eliminated because risk is infinite, generated, and distributed every day and everywhere in nature.
“Risk is based on the assumptions of the existence of a well-defined and constant objective probability distribution which is known and quite possible. Uncertainty has no scientific basis on which to form any calculable probability.”
John M. Keynes, 1937
On the Future and Artificial Intelligence
As we look towards the future of investment management, no doubt, algorithmic investing will continue to evolve and artificial intelligence will influence investing increasingly. However, without strategy first, we are effectively creating infinite loops of hallucinations.
With everyone and their grandmother now having access to intelligent technologies, there will be no meaningful competitive advantage via AI alone. ChatGPT does not make you smarter than most, it might just be the opposite.
However, the advantages will still be with those who authentically understand the De rerum natura, and do the work correctly using math to recognize patterns and gain value-creating insights.
Improper understanding of the utility of AI can also be a distraction from what it takes to win in this 21st century. Real learning and knowledge acquisition remain fundamental to transformation — finding your next swerve.
In the book ‘The Man Who Solved the Market,’ author Gregory Zuckerman, essentially concludes that Jim Simons and Renaissance revolutionized the hedge fund industry through a combination of math and culture. However, I believe it’s a result of empirical observation and application of human intelligence. Simons and his team were smart enough to know that building reliable and warrantable data ecosystems for pattern recognition was how best to utilize human intelligence, the nature of things. This was the winning generational investment management swerve.
So the Lucretius problem is fundamentally about how humans think and make decisions that must be optimally made to solve for randomness. So if we limit our knowledge potential by imposing our egos too heavily, and not detaching from our belief systems, we will not get the best out of our lives.
Intelligence, therefore, is not about ego or emotion, or like LTCM, proving how smart we are. Intelligence is about learning! In pursuit of objective truths; most efficiently and effectively. The truth is always De rerum natura, which can be proven by math.
