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The Cross-Section of Volatility and Expected Returns
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TLDR
This paper examined the pricing of aggregate volatility risk in the cross-section of stock returns and found that stocks with high sensitivities to innovations in aggregate volatility have low average returns, and that stock with high idiosyncratic volatility relative to the Fama and French (1993) model have abysmally low return.Abstract:
We examine the pricing of aggregate volatility risk in the cross-section of stock returns Consistent with theory, we find that stocks with high sensitivities to innovations in aggregate volatility have low average returns In addition, we find that stocks with high idiosyncratic volatility relative to the Fama and French (1993) model have abysmally low average returns This phenomenon cannot be explained by exposure to aggregate volatility risk Size, book-to-market, momentum, and liquidity effects cannot account for either the low average returns earned by stocks with high exposure to systematic volatility risk or for the low average returns of stocks with high idiosyncratic volatilityread more
Citations
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Identifying the relative importance of stock characteristics in the UK market
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Momentum and Information Uncertainty
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Uncertainty, Momentum, and Profitability
TL;DR: In this article, the authors argue that momentum and profitability factors share a common source in uncertainty, and they find that uncertainty subsumes price momentum and operating profitability; it also accounts for the majority of the profits associated with earnings momentum and return on equity, especially in large firms.
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Asymmetric Effects of Volatility Risk on Stock Returns: Evidence from VIX and VIX Futures
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Is There Momentum in Equity Anomalies? Evidence from an Emerging Market
Adam Zaremba,Adam Szyszka +1 more
TL;DR: In this paper, an active asset allocation strategy based on the momentum effect was proposed for the Polish stock market, where the authors identify and replicate 100 anomalies in the cross-section of returns and translate them into a profitable strategy.
References
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Posted Content
The Capital Asset Pricing Model: Some Empirical Tests
TL;DR: In this paper, the authors present some additional tests of the mean-variance formulation of the asset pricing model, which avoid some of the problems of earlier studies and provide additional insights into the nature of the structure of security returns.
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No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns
TL;DR: In this paper, the generalized autoregressive conditionally heteroskedastic (GARCH) model of returns is modified to allow for volatility feedback effect, which amplifies large negative stock returns and dampens large positive returns, making stock returns negatively skewed and increasing the potential for large crashes.
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The Impact of Jumps in Volatility and Returns
TL;DR: In this article, the authors examined a class of continuous-time models that incorporate jumps in returns and volatility, in addition to diffusive stochastic volatility, and developed a likelihood-based estimation strategy and provided estimates of model parameters, spot volatility, jump times and jump sizes using both S&P 500 and Nasdaq 100 index returns.
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Intertemporal Asset Pricing Without Consumption Data
TL;DR: In this article, a new way to generalize the insights of static asset pricing theory to a multi-period setting is proposed, which uses a loglinear approximation to the budget constraint to substitute out consumption from a standard intertemporal asset pricing model.
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Liquidity Risk and Expected Stock Returns
TL;DR: This article investigated whether market-wide liquidity is a state variable important for asset pricing and found that expected stock returns are related cross-sectionally to the sensitivities of returns to fluctuations in aggregate liquidity.