How to Invest by David M. Rubenstein

Author:David M. Rubenstein
Language: eng
Format: epub
Publisher: Simon & Schuster
Published: 2022-09-13T00:00:00+00:00

I. A stop/loss order requires a broker to buy or sell a client’s position in a stock as soon as the stock achieves a certain price—regardless of the reason. These orders are generally used to prevent further losses if a stock is going down or to lock in a profit if a stock is going up.

JIM SIMONS

Founder, Renaissance Technologies; mathematician and philanthropist

“The way I’ve really succeeded is by surrounding myself with great people.”

Great investors have traditionally relied on their intuition in making major investment decisions, though that intuition has typically been applied after a review of some type of information or data. The theory had always been that no type of machine-made decision could possibly be better than a human decision.

That is probably still true in most areas of investing. But in some areas—publicly traded securities, commodities, and currencies—the advent of sophisticated computers, using the best possible data, has spawned an approach known as quantitative investing. In this type of investing, complex computer-spawned algorithms are developed to take advantage of market inefficiencies, even if the inefficiencies exist for very brief periods. The result can be rapid computer-driven market sales or purchases, with potentially very high returns.

The undisputed master of this type of investing for the past three-plus decades has been Jim Simons, whose Renaissance Technologies hedge fund has achieved investment returns thought to be all but impossible. For his flagship Medallion fund (now available only to employees), average annual net returns have apparently exceeded 40 percent for more than 30 years.

As is often the case in the investment world, Jim’s spectacular returns attracted many others to use their math and quantitative expertise to build similar investment firms. And while all of these firms, including Jim’s, have complex algorithms that were developed by humans, the notion took hold that computers—properly programmed by humans—could make investment decisions and act on them better and more quickly than a human. This was revolutionary in the investment world, though the idea that machines can outperform humans in certain areas of investing is now largely the accepted wisdom.

Jim came to the investment world relatively late in a career that had earlier been focused on his real passion—mathematics. In that area, he was a world-class mathematician, leading the math department at the State University of New York at Stony Brook (from the age of 30) and developing award-winning math theorems. But he left his math career behind him—a rare occurrence in the math world—to develop a way in which his expertise could be applied to the trading world. The result changed the investment world forever.

Jim’s firm helped launch an industry where math and science skills are the coin of the realm in developing trading programs. Many others have followed him into the varied world of quant investing, but no one has exceeded his multiyear track record, and it seems no one is likely to do so anytime soon.

Jim’s success has enhanced his philanthropic efforts, many of which are focused—not surprisingly—on advancing research in math and science.

I have known Jim for many years, initially introduced by friends who had invested with him.

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