Negative Betas Research Articles

Have shifts in investor tastes led the market portfolio to capture ESG preferences?

Based on the growing concern about ESG issues in financial markets, in this paper we implement a generalization of the model proposed by Pástor, Stambaugh, and Taylor (2021), which predicts that when the market portfolio is not ESG-neutral and its greenness level increases, the market factor and the ESG factor become redundant, allowing the classic CAPM to account for ESG characteristics. Using market data series for the U.S. equity market, our results show that brown assets typically have negative ESG betas, the price of ESG risk is negative and progressively trends towards zero over time, and the explanatory power of the market portfolio on the ESG factor increases over time as the greenness level of the market portfolio improves. In any case, the period coinciding with the emergence of the COVID-19 pandemic implies a reversal of these trends. Our results suggest that efforts by public authorities to promote improvements in corporate ESG performance translate into lower cost of capital, especially in periods of overall declines in corporate ESG performance.

Is geopolitical risk priced in the cross-section of cryptocurrency returns?

We examine the role of geopolitical risk in the cross-sectional pricing of cryptocurrencies. We calculate cryptocurrency exposure to changes in the geopolitical risk index and document that coins with the lowest geopolitical beta outperform those with high geopolitical beta. Our findings suggest that risk-averse investors require additional compensation as motivation to hold cryptocurrencies with low and negative geopolitical betas, and they are willing to pay a premium for assets with high and positive geopolitical betas. The effect cannot be explained by known return predictors and is robust to many considerations.

Isolating momentum crashes

Across markets, momentum is one of the most prominent anomalies and leads to high risk-adjusted returns. On the downside, momentum exhibits huge tail risk as there are short but persistent periods of highly negative returns. Crashes occur in rebounding bear markets, when momentum displays negative betas and momentum volatility is high. Based on ex-ante calculations of these risk measures we construct a crash indicator that effectively isolates momentum crashes from momentum bull markets. An implementable trading strategy that combines both systematic and momentum-specific risk more than doubles the Sharpe ratio of original momentum and outperforms existing risk management strategies over the 1928–2020 period, in 5 and 10-year sub-samples, and an international momentum portfolio.

Does Momentum Trading Generate Extra Downside Risk?

Momentum strategies tend to provide low returns during market crashes, and they crash themselves when the market rebounds after significant crashes. This is reflected by positive downside market betas and negative upside market betas of zero-cost momentum portfolios. Such asymmetry in upside and downside risks is unfavorable for investors and requires a risk premium. It arises mechanically because of momentum portfolio rebalancing based on trailing asset performance. The asymmetry in upside and downside risks is a robust unifying feature of momentum portfolios in various geographical and asset markets. The momentum premium can be rationalized within a standard asset-pricing framework, where upside and downside risks are priced differently.

Negative Beta Equity Securities as Insurance

Theoretically, an equity security with a negative CAPM beta should behave like portfolio insurance in the sense that the security provides a positive return during a market downturn. However, equity securities with negative betas are relatively rare and simply determining that an equity security exhibits a negative beta is not enough for determining if the negative beta equity security will perform in the desired manner. Negative betas can, at times, be attributed to causes that diminish those securities9 usefulness as insurance. Some of these causes are explored in this article.

Hedging uncertainty with cryptocurrencies: Is bitcoin your best bet?

AbstractAre cryptocurrencies useful minimum‐variance hedging instruments? This paper develops a two‐step analytical framework to explore this question across time. First, it estimates dynamic optimal weights, calibrated when investing between the aggregate market and a respective sampled cryptocurrency. This is performed separately for 11 major cryptocurrencies using the dynamic conditional correlation approach of Engle. Second, using a fractional regression approach, it uncovers linkages between optimal weights in cryptocurrencies and sources of economic uncertainty. Overall, this paper makes the following important findings. First, optimal weights in cryptocurrencies all rose rapidly during the COVID‐19 pandemic. In all, bitcoin showed to be the leading cryptocurrency in terms of hedging effectiveness during this recent time period. Second, most cryptocurrencies exhibit zero or negative betas consistently across time, thus making them natural hedging instruments for investors seeking to reduce their portfolio's comovement with the market. Finally, cryptocurrencies serve as better hedges for economic uncertainties arising from equity and commodity markets. They are relatively less effective for uncertainties arising from risks in the banking industry and firm default risk. This paper contributes broadly to the asset pricing literature since our two‐step approach herein can tractably be extended to other asset classes or other econometric measures of systematic risk.

Explaining the risk premiums of life settlements

Life settlements may facilitate a more efficient insurance market, generate diversification benefits to investors, and even provide hedging benefits to Asia life insurers. The literature does not investigate what determines the risk premiums of life settlements, and we intend to fill this gap. We find that in spite of the premium for non-systematic mortality risk being substantial, the systematic premium is insignificant. On the other hand, the impact of tax on the life settlements' spreads is material. We further find that life settlements have negative betas and are quality assets when investors face market turmoil. The proprietary information provided by medical underwriters and the surrender behavior of the underlying policyholders are also significant determinants of the rate spreads for life settlements.

Measuring liquidity risk effects on carry trades across currencies and regimes

We study the effects of FX liquidity risk on carry trade returns using a novel low-frequency market-wide liquidity measure. We show conclusively that the vast majority of variation in carry trade returns can be explained by two risk factors (liquidity risk and market risk). Our results are further corroborated when the mimicking liquidity risk factor is replaced with a non-tradable innovations risk factor. Safe-haven currencies (SHC) provide insurance against crash risk by having negative liquidity betas, across all time periods. SHCs provide the highest levels of protection during periods of extreme volatility. We find that liquidity risk is priced in the cross-section of carry trade returns, and estimate the liquidity risk premium in the FX market to be around 412 basis points per annum.

Managerial ability premium factor and fund performance

We examine whether fund managers use corporate managerial ability (MA) as a point of reference in their portfolio investment decisions and find that skilled fund managers with significant loading on high-MA stocks outperform low-skill managers with low-loading on high-MA stocks by about 6% annually based on FFC 4-factor alpha over the 1990–2017 period. Consistent with our managerial ability premium (MAP) hypothesis we find negative MAP betas for high-selectivity funds (i.e., safer-funds with high exposure on High-MA stocks) and positive MAP betas for low-selectivity funds (i.e., funds with high exposure on Low-MA stocks). The implication of our findings is that the MAP has emerged as a new factor that has been overlooked in prior asset pricing studies.

Getting to the Core: Inflation Risks Within and Across Asset Classes

Decomposing inflation into core and non-core components (e.g., energy) sheds new light on the nature of inflation risk and risk premia. While stocks have insignificant exposure to headline inflation in the U.S., their core inflation betas are negative and energy betas are positive. Conventional inflation hedges such as currencies and commodities only hedge against energy inflation risk but not the core. These hedging properties are reflected in the prices of inflation risks: only core inflation carries a negative risk premium and its magnitude is consistent both within and across asset classes, whereas the price of energy inflation risk is indistinguishable from zero. The relative contribution of core and energy inflation varies over time, which helps explain why the correlation between stock and bond returns appears to switch sign in the data. We develop a two-sector New Keynesian model to account for these facts.

Observable Implications of the Conditional CAPM

The derivation of observable implications of the conditional CAPM theory often includes the joint (internally inconsistent) hypothesis that the stock portfolio used in the tests is the theoretical, mean-variance efficient, market portfolio. The present paper generalizes this derivation by avoiding this joint hypothesis. The generalization reveals that the conditional CAPM plausibly explains asset pricing anomalies, such as the unconditional alphas and betas of momentum, value, and size portfolios, while the unconditional CAPM theory is still rejected by portfolios with negative unconditional betas and positive unconditional alphas. Hence, relaxing this joint assumption does not render the CAPM theory untestable.

Observable Implications of the Conditional CAPM

The derivation of observable implications of the conditional CAPM theory often includes the joint (internally inconsistent) hypothesis that the stock portfolio used in the tests is the theoretical, mean-variance efficient, market portfolio. The present paper generalizes this derivation by avoiding this joint hypothesis. The generalization reveals that the conditional CAPM plausibly explains asset pricing anomalies, such as the unconditional alphas and betas of momentum, value, and size portfolios, while the unconditional CAPM theory is still rejected by portfolios with negative unconditional betas and positive unconditional alphas. Hence, relaxing this joint assumption does not render the CAPM theory untestable.

Liquidity and Volatility

Liquidity provision is a bet against private information: if private information turns out to be higher than expected, liquidity providers lose. Since information generates volatility, and volatility co-moves across assets, liquidity providers have a negative exposure to aggregate volatility shocks. As aggregate volatility shocks carry a very large premium in option markets, this negative exposure can explain why liquidity provision earns high average returns. We show this by incorporating uncertainty about the amount of private information into an otherwise standard model. We test the model in the cross section of short-term reversals, which mimic the portfolios of liquidity providers. As predicted by the model, reversals have large negative betas to aggregate volatility shocks. These betas explain their average returns with the same risk price as in option markets, and their predictability by VIX in the time series. Volatility risk thus explains the liquidity premium among stocks and why it increases in volatile times. Our results provide a novel view of the risks and returns to liquidity provision.

Does aggregate uncertainty explain size and value anomalies?

ABSTRACTThis paper examines the impact of aggregate uncertainty on return dynamics of size and book-to-market ratio sorted portfolios. Using VVIX as a proxy for aggregate uncertainty, and controlling for market risk, volatility risk, correlation risk and the variance risk premium, we document significant portfolio return exposures to aggregate uncertainty. In particular, portfolios that contain small and value stocks have significant and negative uncertainty betas, whereas portfolios of large and growth stocks exhibit positive and significant uncertainty betas. Using a quasi-natural experimental setting around the financial crisis, we confirm the differential sensitivity of small versus big and value versus growth portfolios to aggregate uncertainty. We posit that due to their negative uncertainty betas, uncertainty-averse investors demand extra compensation to hold small and value stocks. Our results offer an uncertainty-based explanation to size and value anomalies.

Can Exposure to Aggregate Tail Risk Explain Size, Book-to-Market, and Idiosyncratic Volatility Anomalies?

We examine the impact of aggregate tail risk on return dynamics of size, book-to-market ratio, and idiosyncratic volatility sorted portfolios. Using changes in VIX Tail Hedge Index (ΔVXTH) as a proxy for aggregate tail risk, and controlling for market, size, book-to-market, and aggregate volatility risk, we document significant portfolio return exposures to tail risk. In particular, portfolios that contain small, value and volatile stocks exhibit consistently positive and statistically significant tail risk betas, whereas portfolios of big, growth and non-volatile stocks exhibit negative tail risk betas. We posit that due to their positive tail risk exposures, tail risk-averse investors demand extra compensation to hold small, value, and high idiosyncratic volatility stocks. Our results offer a tail risk-based explanation to size, value, and idiosyncratic volatility anomalies.

Upside and Downside Risks in Momentum Returns

I provide a novel risk-based explanation for the profitability of momentum strategies. I show that the past winners and the past losers are differently exposed to the upside and downside market risks. Winners systematically have higher relative downside market betas and lower relative upside market betas than losers. As a result, the winner-minus-loser momentum portfolios are exposed to extra downside market risk, but hedge against the upside market risk. Such asymmetry in the upside and downside risks is a mechanical consequence of rebalancing momentum portfolios. But it is unattractive for an investor because both positive relative downside betas and negative relative upside betas carry positive risk premiums according to the Downside-Risk CAPM. Hence, the high returns to momentum strategies are a mere compensation for their upside and downside risks. The Downside Risk-CAPM is a robust unifying explanation of returns to momentum portfolios, constructed for different geographical and asset markets, and it outperforms alternative multi-factor models.

Positive Alpha and Negative Beta (A Strategy for Counteracting Systematic Risk)

Undiversifiable (or systematic risk) has long been an enemy of investors. Many countercyclical strategies have been developed to counter this. However, like all insurance types, these strategies are generally costly to implement, and over time can significantly reduce portfolio returns in long and extended bull markets. In this paper, we discuss an alternative technique, founded on the premise of physiological bias and risk-aversion. We take a behavioral discussion in order to contextualize the insurance like characteristics of option pricing and discuss how this can lead to a mispricing of the asymmetric relationship between the VIX and the S&P 500. To test this, we perform studies in which we find statistical inefficiencies, thereby making it possible to implement a method of hedging index option premium in a way that has displayed no monthly drawdowns in bullish periods, while still providing large returns in major sell-offs. The three versions of the strategy discussed have negative betas to the S&P 500, while exhibiting similar risk-adjusted excess returns over both bull and bear markets. Further, the performance generated over the entire period, for all three strategies, is highly statistically significant. The results challenge the weak form of the Efficient Market Hypothesis and provide evidence that the methods of hedging could be a valuable addition to an equity rich portfolio for the purpose of counteracting systematic risk.

Does Market Irrationality in the Media Affect Stock Returns?

This paper investigates whether news suggestive of irrationality within financial markets have an impact on stock returns. We construct a lexicon of words for 'market irrationality' and score daily news articles based on the number and proportion of words they contain from the lexicon. We find that reported market irrationality has a significant negative impact on subsequent stock market returns and exacerbates stock market volatility. Furthermore, stocks with large, negative irrationality risk betas outperform stocks with large, positive betas on average by 10.3% annually. Accounting for the Fama-French factors, this results in an alpha of 8.6% annually, which is significant at the 1% level. These results suggest that a large, positive IRR beta amplifies a stock's reaction to market irrationality while a large, negative IRR beta dampens it. The subsequent IRR betas' mean-reversion is consistent with this conjecture.

Is Paying for TSR Paying for Performance? Observations on the the SEC's Proposed Rules

This paper highlights the strengths and weaknesses of the U.S. Securities & Exchange Commission’s (SEC’s) proposed rules on disclosure of pay versus performance, makes several suggestions to improve the proposed rules, presents some surprising data showing that CEO pay is much more highly correlated with gross TSR than relative TSR, explains the importance of “industry beta” in making relative TSR an accurate measure of management performance and shows that for companies with negative industry betas – about one company in six – paying for TSR is paying for management performance. The key weakness of the proposed rules is that the SEC’s interpretation of “compensation actually paid” – the statutory language – undermines the matching of pay and performance periods and makes pay for performance look much worse than it really is. Our key suggestion for improvement is an alternative interpretation that does match pay and performance periods. The paper concludes with a discussion of the comment letter writers who criticize the SEC’s use of TSR as a measure of management performance. They identify the right problem – factors beyond management control – but make unpersuasive arguments for using operating measures instead of relative TSR taking account of industry beta.

Does Aggregate Uncertainty Explain Size and Value Anomalies?

Following seminal works of Knight (1921) and Ellsberg (1961), we distinguish uncertainty from risk and examine the impact of aggregate uncertainty on return dynamics of size and book-to-market ratio sorted portfolios. Using VVIX as a proxy for aggregate uncertainty and controlling for market risk, volatility risk, correlation risk, and the variance risk premium, we document significant portfolio return exposures to aggregate uncertainty. In particular, portfolios that contain small and value stocks have significant and negative uncertainty betas, whereas portfolios of large and growth stocks exhibit positive and significant uncertainty betas. Using a quasi-natural experimental setting around the financial crisis, we confirm the differential sensitivity of small vs. big and value vs. growth portfolios to aggregate uncertainty. We posit that due to their negative uncertainty betas, uncertainty-averse investors demand extra compensation to hold small and value stocks. Our results offer an uncertainty-based explanation to size and value anomalies.