The Price of Variance Risk

Dew-Becker, Ian; Giglio, Stefano; Le, Anh; Rodriguez, Marius

doi:10.2139/ssrn.2471079

Cited by 23 publications

(20 citation statements)

References 39 publications

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“…Our findings are consistent with Ait-Sahalia, Karaman, and Mancini (2014), Dew-Becker, Giglio, Le, and Rodriguez (2014), and Andries, Eisenbach, Schmalz, and Wang (2015). Dew-Becker, Giglio, Le, and Rodriguez (2014) show that the Sharpe ratios of a short position in variance swaps declines rapidly with maturity and is insignificant for maturities longer than two months. Andries, Eisenbach, Schmalz, and Wang (2015) focus on the Sharpe ratios of at-the-money index straddles instead, which is closely related to the results that we report in Table 6.…”

Section: Variance Risksupporting

confidence: 91%

The Term Structure of Returns: Facts and Theory

Koijen

Binsbergen

2015

SSRN Journal

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for generously sharing data for this project. Koijen acknowledges financial support from the European Research Council (grant 338082). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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Section: Variance Risksupporting

confidence: 91%

The Term Structure of Returns: Facts and Theory

Koijen

Binsbergen

2015

SSRN Journal

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“…Bondarenko (2014) documents that, for S&P 500 futures from January 1990 to December 2009, the average excess return for the variance contract is −26.30 per cent per month, indicating that the variance risk is priced and its risk premium is negative. Becker et al (2017) confirm that exposure to realized variance (RV) is sharply priced, with an annualized Sharpe ratio of five times larger than the Sharpe ratio on equities.…”

Section: Introductionmentioning

confidence: 69%

Portfolio allocation across variance risk premia

Chevallier

2019

JRF

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Purpose In asset management, what if clients want to purchase protection from risk factors, under the form of variance risk premia. This paper aims to address this topic by developing a portfolio optimization framework based on the criterion of the minimum variance risk premium (VRP) for any investor selecting stocks with an expected target return while minimizing the risk aversion associated to the portfolio according to “good” and “bad” times. Design/methodology/approach To accomplish this portfolio selection problem, the authors compute variance risk-premium as the difference from high-frequencies' realized volatility and options' implied volatility stemming from 19 stock markets, estimate a 2-state Markov-switching model on the variance risk-premia and optimize variance risk-premia portfolios across non-overlapping regions. The period goes from March 16, 2011, to March 28, 2018. Findings The authors find that optimized portfolios based on variance-covariance matrices stemming from VRP do not consistently outperform the benchmark based on daily returns. Several robustness checks are investigated by minimizing historical, realized or implicit variances, with/without regime switching. In a boundary case, accounting for the realized variance risk factor in portfolio decisions can be seen as a promising alternative from a portfolio performance perspective. Practical implications As a new management “style”, the realized volatility approach can, therefore, bring incremental value to construct the conditional covariance matrix estimates. Originality/value The authors assess the portfolio performance determined by the variance-covariance matrices that are derived by four models: “naive” (Markowitz returns benchmark), non-switching VRP, maximum likelihood regime-switching VRP and Bayesian regime switching VRP. The authors examine the best return-risk combination through the calculation of the Sharpe ratio. They also assess another different portfolio strategy: the risk parity approach.

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“…Values near 1 are observed in other contexts (e.g. Broadie, Chernov, and Johannes (2009) for put option returns, Asness and Moskowitz (2013) for global value and momentum strategies, and Dew-Becker et al (2017) for variance swaps).…”

Section: Combined Portfoliosmentioning

confidence: 84%

“… See Egloff, Leippold, and Wu (2010),Dew-Becker et al (2017),Van Binsbergen and Koijen (2017),Andries et al (2015), and Ait-Sahalia, Karaman, and Mancini (2015).5 See, for example,Bretscher, Schmid, and Vedolin (2018) for a study of the real effects of interest rate uncertainty,Elder and Serletis (2010) for oil price uncertainty,Darby et al (1999) for exchange rate uncertainty, andHuizinga (1993) andElder (2004) for inflation uncertainty.…”

mentioning

confidence: 99%