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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 volatility

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The Return of the Size Anomaly: Evidence from the German Stock Market

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Idiosyncratic Volatility, Momentum, Liquidity, and Expected Stock Returns in Developed and Emerging Markets

TL;DR: In this paper, the authors examined the link between idiosyncratic risk and expected returns for a large sample of firms in both developed and emerging markets using Fama-French three-factor models.
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Switching Risk Off: FX Correlations and Risk Premia

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Indexing and Stock Price Efficiency

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Equity Returns and Idiosyncratic Volatility: UK Evidence

TL;DR: In this article, the authors examined the predictive ability of various measures of idiosyncratic risk and provided evidence which suggests that it is the idiosyncratic volatility of small capitalization stocks that matters for asset pricing.
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.