Risk and return: Long-run relations, fractional cointegration, and return predictability

Tim Bollerslev, Daniela Osterrieder, Natalia Sizova and George Tauchen ()

Journal of Financial Economics, 2013, vol. 108, issue 2, 409-424

Abstract: Univariate dependencies in market volatility, both objective and risk neutral, are best described by long-memory fractionally integrated processes. Meanwhile, the ex post difference, or the variance swap payoff reflecting the reward for bearing volatility risk, displays far less persistent dynamics. Using intraday data for the Standard & Poor's 500 and the volatility index (VIX), coupled with frequency domain methods, we separate the series into various components. We find that the coherence between volatility and the volatility-risk reward is the strongest at long-run frequencies. Our results are consistent with generalized long-run risk models and help explain why classical efforts of establishing a naïve return-volatility relation fail. We also estimate a fractionally cointegrated vector autoregression (CFVAR). The model-implied long-run equilibrium relation between the two variance variables results in nontrivial return predictability over interdaily and monthly horizons, supporting the idea that the cointegrating relation between the two variance measures proxies for the economic uncertainty rewarded by the market.

Keywords: High-frequency data; Realized and options implied volatilities; Volatility risk premium; Long-memory and fractional cointegration; Return predictability (search for similar items in EconPapers)
JEL-codes: C22 C32 C51 C52 G12 G14 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (90)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:108:y:2013:i:2:p:409-424

DOI: 10.1016/j.jfineco.2013.01.002

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