Low-Volatility or Low-Beta Research
Profitability subsumes all of the quality factor, explaining both the performance of the strategies the investment industry market and the factors that academics employ—none of the quality factors generated significant positive alpha relative to profitability, the other Fama and French factors, and momentum.
The bottom line is that returns to the low volatility anomaly have only justified investing when low-volatility stocks were in the value regime, after periods of strong market performance, and when they excluded high-volatility stocks that have low short interest (providing clues as to how to improve its performance). This may be why live funds have been generating large negative alphas once we account for common factor exposures.
We examine the research around the question of what the proper framework for building a defensive factor strategy is.
Idiosyncratic volatility (IVOL) is the volatility of a security that cannot be explained by overall market volatility—it is the risk unique to a particular security. IVOL contrasts with systematic risk, which is the risk that affects all securities in a market (such as changes in interest rates or inflation) and, therefore cannot be diversified away. On the other hand, the risks of high IVOL stocks can at least be reduced through diversification.
The empirical evidence demonstrates that returns to the low-beta anomaly are well explained by exposure to other common factors, and it has only justified investment when low-beta stocks were in the value regime, after periods of strong market and small-cap stock performance, and when they excluded high-beta stocks that had low short interest.
Factor strategies need to be rebalanced in order to maintain their factor exposure. But different factors decay at different rates and this affects how they should be rebalanced. For example, momentum needs to be rebalanced more than value. This study digs into these questions.
In this article, the author examines several important questions related to asynchronous trading, or the variation in trading frequency that occurs when trading stocks or other assets.
We examine the short-duration premium using pre-scheduled economic, monetary policy, and earnings announcements. We provide high-frequency evidence that duration premia associated with revisions of economic growth and interest rate expectations are consistent with asset pricing models but cannot explain the short-duration premium. Instead, we show that the trading activity of sentiment-driven investors raises prices of long-duration stocks, which lowers their expected returns, and results in the short-duration premium. Long-duration stocks have the lowest institutional ownership, exhibit the largest forecast errors at earnings announcements, and show the highest mispricing scores.
The intuition behind betting against beta is that leverage-constrained investors, instead of applying leverage, obtain an expected return higher than the market’s expected return through overweighting high-beta stocks and underweighting low-beta stocks in their portfolios. Their actions lower future risk-adjusted returns on high-beta stocks and increase future risk-adjusted returns on low-beta stocks. We take a deeper look into this idea.
The superior performance of low-volatility stocks was first documented in the literature in the 1970s—by Fischer Black in 1972, among others —even before the size and value premiums were “discovered.” The low-volatility anomaly has been shown to exist in equity markets around the world. Interestingly, this finding is true not only for stocks but for bonds as well. In other words, it has been pervasive...but
Negative outcomes from unconditional long exposure to the VIX led Campasano to examine the performance of an Enhanced Portfolio that dynamically invests in the S&P 500 Index and VIX futures.
One of the big problems for the first formal asset pricing model developed by financial economists, the CAPM, was that it predicts a positive relationship between risk and return. However, empirical studies have found the actual relationship to be basically flat, or even negative. Over the last 50 years, the most “defensive” (low-volatility or low-beta, low-risk) stocks have delivered both higher returns and higher risk-adjusted returns than the most “aggressive” (high-volatility, high-risk) stocks.
Two of the more interesting puzzles in finance are the high beta anomaly (high beta stocks have lower returns) and the IVOL anomaly (stocks with [...]
We are proponents of focused (i.e., 50 stock) long-only value and momentum factor strategies.[ref]Please note that in the context of long/short factor investing, which is [...]
Open Source Cross-Sectional Asset Pricing Andrew Chen and Tom ZimmermannWorking paperA version of this paper can be found here What are the research questions? There has [...]
Betting against correlation: Testing theories of the low-risk effect Cliff Asness, Andrea Frazzini, Niels Joachim Gormsen, Lasse Heje PedersenJournal of Financial EconomicsA version of this [...]
In virtually all studies on asset pricing and asset pricing models, the one-month Treasury bill is the choice as the risk-free rate. In his study [...]
On the Performance of Volatility-Managed Portfolios Scott Cederburg, Michael S. O’Doherty, Feifei Wang, Xuemin (Sterling) YanJournal of Financial EconomicsA version of this paper can be [...]
Among the assumptions in the first formal asset pricing model, the CAPM, is that investors are risk-averse, they maximize the expected utility of absolute wealth, [...]
Tesla (TSLA) breached the $100 billion market capitalization in January 2020 and became the most valuable car manufacturer globally. However, valuing the company is challenging [...]
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