Many theories exist on how to make money in the markets, but one firm, Renaissance Technologies, has apparently found a way to consistently outperform all others. We spoke with Gregory Zuckerman, writer for The Wall Street Journal and author of a new book, The Man Who Solved the Market, about Renaissance founder Jim Simons and his approach that changed investing.
Renaissance has achieved the greatest performance likely ever seen in the history of finance. Over a 30-year time period, their flagship fund called Medallion has returned an average of 66 percent since 1988.
That sounds impressive, but it isn’t just its returns that make Renaissance's performance so attractive, Gregory Zuckerman told listeners. The amount of risk or volatility they've experienced over the past 30 years is extremely low, which means they consistently produced large returns with very little risk.
Even in the midst of turmoil or major market volatility, Renaissance has performed very well. In fact, some of the worst years for investors are some of its best, Zuckerman said. For example, during the tech market collapse and the 2008 financial crisis, Renaissance was up big, making billions of dollars in trading profits.
Renaissance conducts most of its investments on a very short-term basis, Zuckerman said, looking for patterns in markets on a timescale of around 2 days on average.
“They don't really do anything longer than a few months, generally speaking,” Zuckerman told Financial Sense Newshour. “When they do, they take advantage to some extent of the mistakes that we all make as investors. And that's why it makes sense that they would do best in times of panic, when there's greed or fear in the market.”
Science vs. Human Intuition
How did they do it? Renaissance employed a massive data-mining campaign decades ahead of their competition, and then mapped short-term trading patterns in the market that most others couldn't see, Zuckerman explained.
What distinguishes Renaissance from other quantitative investors, or "quants", is it doesn't look for the “why” in terms of returns. As long as a pattern is scientifically dependable and reliable, it will make a bet.
Ultimately, Renaissance determined that other large institutions trading in bulk and relying on human intuition are probably on the other side of the market.
“They use the scientific method,” Zuckerman said. “Their thesis continues to be that statistical analysis beats human analysis every time.”
Birth of Big Data
By some estimations, Renaissance and Simons were pioneers in “Big Data,” using the power of analysis and artificial intelligence to beat markets. The company seeks to gather all kinds of information, some of which was not traditionally used for making investment decisions.
Early on, it would send people to the Federal Reserve to data mine records going back to the 1700s. By the late 1990s and early 2000s, Zuckerman stated, it started acquiring every kind of data possible.
This includes anything one can test and build a model around, Zuckerman added, from shipping data and real estate acquisition information to anything that sets the tone in the economy.
Simons is also a unique character, beginning his career as a mathematician and professor who later went on to develop the people skills to recruit top talent to build Renaissance into what it is today. Under his guidance, Renaissance proved the data-driven approach is likely the most reliable way to beat markets.
The company was also an early adopter of using AI to identify value in markets. As long as the data is sound and the method is proven reliable, it doesn't matter so much to Simons if AI decision-making is a “black box,” as long as it works.
“They're scientists, they do experiments all day long and it's all testing what factors impact the markets,” Zuckerman said. “They believe that we as investors aren't aware of enough of the factors that influence markets. We all think of earnings, revenue, prices, price to earnings and those kinds of ratios. And their thesis is that many more factors affect markets then are generally acknowledged, and none of them are all that important in and of themselves. It's almost like an engineering challenge for them.”
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