2021
DOI: 10.1093/rfs/hhab051
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Stock Return Extrapolation, Option Prices, and Variance Risk Premium

Abstract: This paper presents a tractable dynamic equilibrium model of stock return extrapolation in the presence of stochastic volatility. In the model, consistent with survey evidence, investors expect future returns to be higher (lower) but also less (more) volatile following positive (negative) stock returns. The biased volatility expectation introduces a new channel through which past returns and investor sentiment affect derivative prices. In particular, through this novel channel, the model reconciles the otherwi… Show more

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Cited by 17 publications
(2 citation statements)
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“…Our paper also contributes to the growing theoretical literature studying the asset pricing implications of extrapolating past stock prices when forming future stock price expectations. In this literature, Barberis et al (2015) develop a heterogeneous agent model with two types of investors, the rational investors and extrapolators, whereas Jin and Sui (2022), Li and Liu (2020), and Atmaz (2021) develop homogeneous agent models in which the representative agent is an extrapolator. 3 Although these works capture various features of actual stock market returns, they typically generate only reversal, that is, a negative autocorrelation for all horizons.…”
Section: Introductionmentioning
confidence: 99%
“…Our paper also contributes to the growing theoretical literature studying the asset pricing implications of extrapolating past stock prices when forming future stock price expectations. In this literature, Barberis et al (2015) develop a heterogeneous agent model with two types of investors, the rational investors and extrapolators, whereas Jin and Sui (2022), Li and Liu (2020), and Atmaz (2021) develop homogeneous agent models in which the representative agent is an extrapolator. 3 Although these works capture various features of actual stock market returns, they typically generate only reversal, that is, a negative autocorrelation for all horizons.…”
Section: Introductionmentioning
confidence: 99%
“…The first contribution of this work is the introduction of two new additional predictors based on the Variance Risk Premium (VRP) originally proposed by Bollerslev et al (2009) and Bollerslev et al (2014), which is defined as the difference between the implied volatility (IV) and the realized volatility (RV). There is a large literature that showed that the VRP can be an effective variable to predict future equity returns, see Atmaz (2022) therein for more details. The intuition behind this evidence is that the increase (decrease) of risk aversion leads to asset prices being discounted, and later this discount is accrued, thus resulting in future higher (lower) returns.…”
Section: Introductionmentioning
confidence: 99%