Using Big-Data Techniques to Construct Hedge Portfolios
Using a three-pass method to isolate individual risk premia.
Using Big-Data Techniques to Construct Hedge PortfoliosWhen investors consider the liquidity of a stock portfolio, they are usually interested in how readily the underlying holdings can be bought or sold. For example, a portfolio of large-cap equities, or heavily traded stocks of big companies, is generally considered to be more liquid than a portfolio of small-cap equities, or lightly traded stocks of small firms.
Although the focus on the average liquidity of the portfolio’s holdings is largely correct, it paints an incomplete picture, according to research by Chicago Booth’s Lubos Pastor and University of Pennsylvania’s Robert F. Stambaugh and Lucian A. Taylor. The portfolio’s construction matters too.
“The more diversified a portfolio, the less costly is trading a given fraction of it,” the researchers write. “For example, a fund trading just one stock will incur higher trading costs than a fund spreading the same dollar amount of trading over 100 stocks, even if all the stocks are equally liquid.”
Using a three-pass method to isolate individual risk premia.
Using Big-Data Techniques to Construct Hedge PortfoliosPastor, Stambaugh, and Taylor derive a simple measure of a portfolio’s liquidity by relating it to the portfolio’s trading costs. They suggest that portfolio liquidity is the average liquidity of the portfolio’s stocks multiplied by the portfolio’s level of diversification. Better-diversified portfolios are more liquid in that they can be traded more cheaply.
Diversification is a foundational concept in finance, yet there is no widely accepted standard for measuring it. The researchers derive a simple measure of diversification and demonstrate that it can be computed as “coverage” (the number of stocks in the portfolio) multiplied by “balance” (how the stocks are weighted relative to market cap). Portfolios holding more stocks are better diversified, and so are portfolios with weights that are closer to market-cap weights.
Analyzing 2,789 actively managed mutual funds between 1979 and 2014, the researchers find that fund portfolios have become more liquid over time, with both balance and coverage rising, taking off particularly from 2000 right up until the 2007–10 financial crisis, when balance (but not coverage) dipped slightly. Both components of diversification continued to rise after the crisis. The levels of coverage rose faster than the level of balance as mutual-fund managers poured ever more names into their portfolios.
“The sharp increase in diversification after 2000 is remarkable,” the researchers write, adding that “the portfolios of active mutual funds have thus become more index-like: they hold an increasingly large fraction of all stocks in the market, and their weights increasingly resemble market weights.”
The research captures the rise of closet indexing among active mutual-fund managers, a phenomenon that may be caused by managers hewing toward the benchmark they are trying to outperform. While diversification has some benefits in terms of risk management and liquidity, the close resemblance of active portfolios to passive indexes might leave some investors wondering why they’re bothering to pay for active management given the ubiquitous availability of cheap, passive alternatives.
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