By Neil Wilson
Inside the Black Box
By Rishi Narang
In the investment world, quant trading enjoys a status that seems akin to that of science fiction in literature. To say that many investors regard quant with distrust or disdain may be a little strong, but you know what I mean.
For me, this type of suspicion or hostility has always been misplaced. To continue the comparison: There are plenty of great books, such as Aldous Huxley's "Brave New World," that also may be described as science fiction. What should matter most is not whether they are called science fiction but whether they are indeed great literature.
The same standard should apply to investing. There indeed may be plenty of mediocre or poor quality quant strategies that have been invented over time, and even some that have blown up—much as there has been a lot of instantly forgettable pulp fiction. But the best quants, such as Jim Simons' Medallion fund, have track records that stack up well against even the very best fundamental investors such as Warren Buffett. They deserve to be taken seriously.
In his excellent new book, "Inside the Black Box," seasoned quant investor Rishi Narang—the founder and chief executive of Telesis Capital—sets out to demystify the world of quant investing, and does so in a way that should be intelligible to any thoughtful investor. "It is my aspiration," he says at the start, "to explain quant trading in an intuitive manner. I explain what quants do and how they do it by drawing on the economic rationale for their strategies and the theoretical basis for their techniques."
He is admirably thorough in addressing the task and the text is highly readable throughout. The book has a logical structure, which gradually builds an ever more complete picture of what it is that quants do, how they do it, and what the issues really are that surround quant trading. And these are not only the ones that you might see in the press.
After an introductory section on the basics of quant trading, as the title promises, Narang takes the reader inside the black box—and looks at the different types of alpha models for deriving returns, such as the trend-following systems of CTAs and the mean reversion approaches of statistical arbitrage.
Narang goes into similar detail on risk models, including theoretical, empirical and transaction cost models, which look at fees; as well as slippage and market impact. Putting all this together, he goes on to explain how quants build portfolio construction models with systematic approaches to weightings and optimization. Data and research are, of course, crucial inputs into quant trading approaches, and Narang also offers separate chapters on these key areas.
But the book is much more than a simple "beginner's guide" to quants, and it really gets interesting in the final third, where he looks in some detail at the risks inherent in quant approaches and the criticisms of quant trading—and how to evaluate them.
Some of these risks have been revealed by market events over the years, such as exogenous shocks, including terrorist attacks and what Narang calls regime change risk, such as the sudden emergence and then collapse of the dot-com bubble. But, as he points out, these affect all investors.
A more exclusive concern with quants is what he calls contagion risk, which arises from the emergence of too many similar quant strategies running too much money in a similar way.
In a detailed analysis of events, Narang concludes that this risk was at least one of four factors, along with VAR-based volatility targeting and leverage adjustments, which led to the quant meltdown in August 2007.
Most of the standard criticisms of quants, however, are carefully considered and then thoroughly dismissed. Many quant managers may have underestimated the market risks they were taking in August 2007, but they really did not cause any increase in overall market volatility, which as he shows barely ticked up at all during that period.
Similarly, Narang flatly rejects the widely held conviction that quants are all the same, given the wide array of strategies and dispersion in performances. And, of course, quants have not done worse than other strategies in the most difficult markets, such as in the market collapse of 2008. On the contrary, CTAs—which form one of the biggest subsets among quant traders—were mainly positive during that tumultuous period.
To find out more about how to evaluate quants, read this book.