The Economic Value of Forecasting Left-Tail Risk

Xiong, James X.; Idzorek, Thomas M.; Ibbotson, Roger G.

doi:10.3905/jpm.2016.42.3.114

“…Still, the success of the RSK measure is likely due to its relatively stable performance, compared with other jump-based strategies. This finding is similar to the findings discussed in Xiong et al (2016), who show that tail risks can be substantially reduced by forecasting skewness. Note also that the signed small jump variation (SRVSJ)-based portfolio has the highest Sharpe ratio, among all value-weighted portfolios.…”

Section: Single (Univariate) Portfolio Sorts Based On Realized Measuressupporting

confidence: 91%

New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section

Yu

¹

,

Mizrach

²

,

Swanson

³

2020

Econometrics

3

0

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We investigate the marginal predictive content of small versus large jump variation, when forecasting one-week-ahead cross-sectional equity returns, building on Bollerslev et al. (2020). We find that sorting on signed small jump variation leads to greater value-weighted return differentials between stocks in our highest- and lowest-quintile portfolios (i.e., high–low spreads) than when either signed total jump or signed large jump variation is sorted on. It is shown that the benefit of signed small jump variation investing is driven by stock selection within an industry, rather than industry bets. Investors prefer stocks with a high probability of having positive jumps, but they also tend to overweight safer industries. Also, consistent with the findings in Scaillet et al. (2018), upside (downside) jump variation negatively (positively) predicts future returns. However, signed (large/small/total) jump variation has stronger predictive power than both upside and downside jump variation. One reason large and small (signed) jump variation have differing marginal predictive contents is that the predictive content of signed large jump variation is negligible when controlling for either signed total jump variation or realized skewness. By contrast, signed small jump variation has unique information for predicting future returns, even when controlling for these variables. By analyzing earnings announcement surprises, we find that large jumps are closely associated with “big” news. However, while such news-related information is embedded in large jump variation, the information is generally short-lived, and dissipates too quickly to provide marginal predictive content for subsequent weekly returns. Finally, we find that small jumps are more likely to be diversified away than large jumps and tend to be more closely associated with idiosyncratic risks. This indicates that small jumps are more likely to be driven by liquidity conditions and trading activity.

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“…Taken as a whole, our paper contributes to the literature by documenting time-varying volatility interdependencies between value and momentum returns. Given the growing literature on momentum crashes and tail risks of investment strategies (see e.g., Bhansali 2008;Daniel and Moskowitz 2016;Xiong et al 2016;Grobys et al 2018;Baltas and Scherer 2019), an interesting avenue for future studies would be to examine potential tail risk interdependencies between value and momentum strategies.…”

Section: Discussionmentioning

confidence: 99%

Another look at value and momentum: volatility spillovers

Grobys

¹

,

Vähämaa

²

2020

Rev Quant Finan Acc

5

0

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This paper examines volatility interdependencies between value and momentum returns. Using U.S. data over the period 1926-2015, we document persistent periods of low and high volatility spillovers between value and momentum strategies. Moreover, we find that the intensity of the volatility spillovers may change substantially in very short periods of time and that these shifts in spillover intensity can be linked to prominent economic events and financial market turmoil. Our results further demonstrate that value returns increase and momentum returns decrease monotonically with increasing volatility spillovers between the two strategies. Given this linkage between spillover intensity and returns, we propose a simple trading strategy which utilizes a volatility spillover index for allocating funds between value and momentum portfolios. The proposed trading strategy outperforms value and momentum strategies and generates payoffs that are not subject to option-like behavior.Keywords Asset pricing · Value effect · Momentum effect · Volatility spillovers · Volatility spillover index JEL Classification G11 · G12 · G14

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“…Taken as a whole, our paper contributes to the literature by documenting time-varying volatility interdependencies between value and momentum returns. Given the growing literature on momentum crashes and tail risks of investment strategies (see e.g., Bhansali 2008;Daniel and Moskowitz 2016;Xiong et al 2016;Grobys et al 2018;Baltas and Scherer 2019), an interesting avenue for future studies would be to examine potential tail risk interdependencies between value and momentum strategies.…”

Section: Discussionmentioning

confidence: 99%

Another Look at Value and Momentum: Volatility Spillovers

Grobys

¹

,

Vähämaa

²

2017

SSRN Journal

1

0

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This paper examines volatility interdependencies between value and momentum returns. Using U.S. data over the period 1926-2015, we document persistent periods of low and high volatility spillovers between value and momentum strategies. Moreover, we find that the intensity of the volatility spillovers may change substantially in very short periods of time and that these shifts in spillover intensity can be linked to prominent economic events and financial market turmoil. Our results further demonstrate that value returns increase and momentum returns decrease monotonically with increasing volatility spillovers between the two strategies. Given this linkage between spillover intensity and returns, we propose a simple trading strategy which utilizes a volatility spillover index for allocating funds between value and momentum portfolios. The proposed trading strategy outperforms value and momentum strategies and generates payoffs that are not subject to option-like behavior.

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The Economic Value of Forecasting Left-Tail Risk

Cited by 11 publications

References 13 publications

New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section

New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section

Another look at value and momentum: volatility spillovers

Another Look at Value and Momentum: Volatility Spillovers

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