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Is factor investing a smart way of investing in stocks?

Market theories tell us that returns of any stock can be explained by a set of hidden variables, plus a residual bit unique to that stock

Prodipta Ghosh        Last Updated: May 11, 2019  | 16:54 IST
Is factor investing a smart way of investing in stocks?

Value investing, pioneered in early 20th century, and made popular by legendary investors like Warren Buffet has a common-sense appeal. Buying securities lower than their fair value sounds like a good trade. But it is hardly that straight forward.

First, determining the intrinsic value of a stock is not easy. Equity valuation is as much art as science. Second, value investing recommends eschewing diversification in favour of a concentrated portfolio. This may work well for institutional investors, with fire-power and access to the management. But this approach of investing in idiosyncratic risks can be ruinous for the retail investors who have informational and capital disadvantages.

If we are not investing at the scale of Buffet, we need to adapt our style as well. Factor investing is a proven alternative. It was pioneered in the 70s, supported by seminal academic research. It became popular in the real world following the Great Financial Crisis in 2008. The underlying systematic approach offers two major benefits. First, it allows us to test conventional wisdom. Second, it offers an advantage in diversification. So, what is a factor?

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Market theories tell us that returns of any stock can be explained by a set of hidden variables, plus a residual bit unique to that stock. Usually, we take overall market returns as the sole explainer. In this world, the value investor's job is to find stocks with high expected residual returns, assuming valuation measures can capture it. It turns out parts of this residual can be further explained by other fundamental characteristics of the stock. If they are stable and consistent, each of such characteristics can be thought of as a risk factor. In such a world, an investor's job is to identify factors with high expected returns and design portfolios to capture them. This is, in a nutshell, the essence of factor investing. We systematically probe the drivers of the markets, instead of taking concentrated exposure on idiosyncratic risks.

The time-tested factors in the equity market are value, momentum, quality, low volatility, size and liquidity. Each factor tries to isolate some specific characteristics of the market. Value factor, for example, tries to identify cheap stocks with potential, using metrics like book-to-market, earnings-to-price and cashflow-to-price. Apart from fundamentals, factors can be based on macro-economic or even statistical variables. By combining uncorrelated factors, investors can achieve a balanced portfolio. It also opens up the possibility of factor timing - an alpha strategy.

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Factor portfolio construction begins with rigorous research. Once we find a measure that significantly explains returns, the next step is to isolate this source. This is done by sorting stocks on this measure and creating a long-short portfolio (market neutral by design). The process is complex. But since it is quantitative, the output is transparent. And since it is scalable, it is cheaper as well. For small investors these days, investible factor portfolios are readily available in the form of ETFs in the developed markets. Expect to see a proliferation of them in the India market as well going forward.

Factor investing is no free lunch, of course. It comes with its own set of caveats. It is a beta strategy with periods of under and over performance. Like most quantitative strategies, it is susceptible to data mining and other biases. But it does not rely on elusive skills to pick the next multi-bagger. The transparent systematic approach does not cloud risks with promises of rewards. Factor investing is now an institutional favourite. Smart retail money will go the same way in the near future.

(The author is the Vice President at QuantInsti, an Algorithmic trading training institute.)

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