Low Volatility Anomaly Research Articles

The Benefits of Socially Responsible Investing: An Active Manager’s Perspective

There has been a lot of research on the predictive power of environmental, social, and governance (ESG) ratings, the relationship between ESG ratings and subsequent stock performance, and whether using ESG data in stock analysis and portfolio management was value-additive or valuedetracting. In this article, the authors examine the relationship between the ESG ratings of a company and its stock returns, volatility, and risk-adjusted returns in the post-2008 financial crisis era. They explore the negative relationship between ESG and volatility in greater depth, given the well-documented low-volatility anomaly (outperformance of low-volatility stocks). Both (high) ESG rating and (low) volatility positively impact stock returns, but the ESG effect is independent of the low-volatility effect, and ESG is a positive contributor in its own right. Given the controversy surrounding the effect of ESG-based investment restrictions, the authors test the effect of restricting the investible universe by deleting the lower tail of ESG companies on portfolio performance. Asset managers can thus actively use the association between corporate ESG ratings and stock return, volatility, and risk-adjusted return to enhance their stock-picking and portfolio-construction abilities.

The Effective Combination of Risk-Based Strategies with Momentum and Trend Following

The Efficient Market Hypothesis (EMH) has been widely called into question in the investment literature, through two main anomalies: timing and low-volatility anomalies. In this paper, we aim to combine the predictive power of timing and low-volatility strategies to deliver better risk-adjusted portfolio performance. We adopt a two-step approach for a constant dataset composed of 18 country MSCI stock market indices over the 1975-2014 period. First, we use different timing strategies: moving averages and momentum. We select stock market indices based on different moving averages (6, 8, 10, and 12 months), while the momentum strategy ranks the different stock market indices into momentum subsets (low, medium, and high momentum). After the first step using the different timing strategies, the second step consists in building risk-based portfolios (MV, ERC, and MD) as well as 1/N benchmark portfolios for each of these timing strategies. Our results highlight the effectiveness, the relevance and the robustness of our approach. First, risk-based portfolios using relevant timing strategy indeed provide better returns, lower volatilities, higher Sharpe ratios, and lower Value-at-Risk (VaR) and Expected Shortfall (ES) than traditional risk-based portfolios. The second contribution of our approach features that risk-based strategies provide better risk-adjusted returns and lower VaR and ES than the 1/N portfolio within a context in which the first step is dedicated to the application of a relevant timing strategy. Finally, among these risk-based portfolios using relevant timing strategies, the MD and MV portfolios usually obtain the best risk-adjusted performance.

Requisite Assumptions for the Persistence of the Low Volatility Anomaly

Common explanations of the low volatility anomaly involve biases or frictions that cause investors to overpay for high volatility assets, giving them a negative alpha within the CAPM model, yet currently all such mechanisms are either heuristic or partial equilibrium. This paper shows that leverage constraints of Frazzini and Pedersen (2014) alone cannot explain this result if there also exist rational investors. If 3 non-standard assumptions are added — hybrid relative utility, delusional subset of investors, residual systematic risk across beta — then we can capture several facts existing models cannot simultaneously capture: a positive return to the market, positive holdings by rational investors to negative CAPM-alpha stocks, and a negative Security Market Line. New data relevant to these assumptions are presented.

Institutional Holding, Low Beta and Idiosyncratic Volatility Anomalies

Institutional investors subject to benchmarking, short-selling and leverage constraints have asymmetric effects on both low beta and low volatility anomalies documented by previous studies. Specifically, institutional investors prefer high-beta stocks to low-beta stocks to minimize the tracking error and utilize the embedded leverage of high beta stocks, leading to low-beta anomaly. They can act as the supply source of security lending to the short-sellers, mitigating the overpricing induced negative effect on expected returns from idiosyncratic volatility. Using size effect adjusted institutional ownership as a proxy for institutional limits to arbitrage, I confirm that mandated and financial constrained institutional investors contribute positively to the low beta anomaly but mitigate the low IVOL anomaly using sorting and Fama-MacBeth regressions. I distinguish the highly correlated low beta and low volatility anomalies and find a significantly positive risk premium for institutional holding. A strong January reversal effect of idiosyncratic volatility on expected return is also documented.

Practical Applications of Volatility versus Tail Risk: Which One is Compensated in Equity Funds?

Conventional investment theory says that securities with lower risk, or volatility, should have lower returns. But in practice, low-volatility funds do as well as—if not better than—high-volatility funds. The low-volatility anomaly holds true for equity funds as well, according to the authors of Volatility versus Tail Risk: Which One is Compensated in Equity Funds? in the Winter 2014 issue of The Journal of Portfolio Management. “If volatility isn’t compensated, then what kind of risk is compensated [in terms of higher returns]?” asks co-author James Xiong, Head of Quantitative Research at Morningstar Investment Management. Read this Practical Applications report to find out. Xiong’s co-authors are Thomas M. Idzorek, President of Morningstar Investment Management and Roger G. Ibbotson, Chairman and CIO at Zebra Capital Management and Professor at the Yale School of Management.

Country and Sector Drive Low-Volatility Investing in Global Equity Markets

Low-risk stocks have historically outperformed high-risk stocks, delivering better long-term returns with less volatility. This counterintuitive effect has persisted since 1926, violating one of the basic tenets of finance theory. We investigate the role of country and sector effects in low-volatility investing in global equities and find that the benefit of the low-volatility anomaly can be earned through country and sector selection in lieu of individual stock selection. We find that low-volatility investing has a pronounced “anti-bubble” behavior that is driven by country and sector positioning. Additionally, we see that employing a country–sector selection approach mitigates many of the implementation pitfalls associated with the minimum-volatility stock selection portfolio. We conclude that country and sector selection is a more practical approach than individual stock selection for capturing the benefits of low-volatility investing in global equities. <b>TOPICS:</b>Security analysis and valuation, analysis of individual factors/risk premia, global

The Limits to Arbitrage and the Low-Volatility Anomaly

The authors found that over 1963–2010, the existence and trading efficacy of the low-volatility stock anomaly were more limited than widely believed. For example, they found no anomalous returns for equal-weighted long–short (low-risk minus high-risk) portfolios and that alpha is largely eliminated when omitting low-priced stocks from value-weighted long–short portfolios. Furthermore, performance of long–short portfolios was significantly reduced by high transaction costs, reflecting the finding that the abnormal returns were concentrated among low-liquidity and smaller stocks. Amplifying liquidity needs, the anomalous excess returns quickly reversed, requiring frequent rebalancing. The authors’ findings have meaningful implications for implementing low-risk equity portfolio strategies.

Country and Sector Drive Low-Volatility Investing in Global Equity Markets

Low-risk stocks have historically outperformed high-risk stocks, delivering better long-term returns with less volatility. This counter-intuitive effect has persisted since 1926, violating one of the basic tenets of Finance Theory. We investigate the role of country and sector effects in low-volatility investing in global equities and find that this strategy has a pronounced “anti-bubble” behavior. As a result, most of the benefit of the low-volatility anomaly can be earned through country and sector selection in lieu of individual stock selection. Additionally, we see that this approach mitigates many of the implementation pitfalls associated with the minimum-volatility stock portfolio. We conclude that sector and country selection is a more practical approach to individual stock selection for capturing the benefits of low-volatility investing in global equities.

Diversified Risk Parity Strategies for Equity Portfolio Selection

This article investigates a new way of equity portfolio selection that provides maximum diversification along the uncorrelated risk sources inherent in the S&amp;P 500.This diversified risk parity strategy is distinct from prevailing risk-based portfolio construction paradigms. Especially, the strategy is characterized by a concentrated allocation that actively adjusts to changes in the underlying risk structure. In addition, x-raying the risk and diversification characteristics of traditional risk-based strategies like 1/N, minimum-variance, risk parity, or the most-diversified portfolio, the authors find the diversified risk parity strategy to be superior. Although most of these alternatives crucially pick up risk-based pricing anomalies like the low-volatility anomaly, the diversified risk parity strategy more effectively exploits systematic factor tilts. <b>TOPICS:</b>Equity portfolio management, portfolio construction, factor-based models

Low Risk Stocks Outperform within All Observable Markets of the World

This article provides global evidence supporting the Low Volatility Anomaly: that low risk stocks consistently provide higher returns than high risk stocks. This study covers 33 different markets during the time period from 1990-2011. (Two previous studies by Haugen & Heins (1972) and Haugen & Baker (1991) show the same negative payoff to risk in time periods 1926-1970 and 1970-1990.) The procedure for our study is intentionally simple, transparent and easily replicable. Our samples include non-survivors. We look at an international universe of stocks beginning with the first month of 1990 until December 2011; we compute the volatility of total return for each company in each country over the previous 24 months. Stocks in each country are ranked by volatility and formed into deciles. In the total universe and in each individual country low risk stocks outperform, the relationship with respect to Sharpe ratios is even more impressive. We believe this anomaly is caused primarily by agency issues, namely the compensation structures and internal stock selection processes at asset management firms which lead institutional investors on average to hold more volatile stocks. The article also addresses the implications for how corporate finance managers make capital investment decision in light of this evidence. The evidence presented here dethrones both CAPM and the Efficient Market Hypothesis.

The Limits to Arbitrage Revisited: The Low-Risk Anomaly

We show that over a long study period (1963-2010), the existence and trading efficacy of the well-known low-volatility stock anomaly are more limited than widely believed. For example, we find that the anomalous returns are not found within equal weighted long-short (low minus high risk) portfolios. Within value-weighted portfolios, the existence of alpha is largely eliminated when omitting low priced (less than $5) stocks. Furthermore, extracting any excess returns associated with a long-short portfolio is meaningfully hampered by high transaction costs reflecting the finding that the abnormal returns are concentrated among low liquidity and smaller stocks. Adding to the challenge, the anomalous excess returns quickly reverse requiring traders to rebalance frequently in attempting to extract profits, thus amplifying liquidity needs. Our findings are unchanged for various approaches to measuring the low-volatility anomaly.

Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly

Contrary to basic finance principles, high-beta and high-volatility stocks have long underperformed low-beta and low-volatility stocks. This anomaly may be partly explained by the fact that the typical institutional investor’s mandate to beat a fixed benchmark discourages arbitrage activity in both high-alpha, low-beta stocks and low-alpha, high-beta stocks.