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The Cross-Section of Volatility and Expected Returns
TL;DR: 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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TL;DR: This paper found no pricing ability for aggregate firm-level variance for the period 1927 to 2012 or for any sub-period tested, and concluded that the aggregate firmlevel bid-ask spread is priced with future market returns rather than any of the aggregate firms-level risk measures.
Abstract: This paper models a market microstructure bias, driven by the bid-ask spread, that is evident in the pricing of aggregate firm-level risk embodied by the stock return variance estimates of Goyal and Santa-Clara (2003). Controlling for this bias, we find no pricing ability for aggregate firm-level variance for the period 1927 to 2012 or for any sub-period tested. Market microstructure also explains the time-trend of aggregate firm-level volatility observed from 1962 to 1997 (Campbell, Lettau, Malkiel, and Xu, 2001), and subsumes any relation between retail trading and future idiosyncratic volatility from 1983 to 1999 (Brandt, Brav, Graham, and Kumar, 2010). We conclude that the aggregate firm-level bid-ask spread is priced with future market returns rather than any of the aggregate firm-level risk measures.
4 citations
TL;DR: In this article, a consumption-based asset pricing model related to the literature on long-run risks is proposed to explain the anomaly that firms with high measures of default likelihood earn anomalously low returns, despite having relatively high CAPM betas.
Abstract: The distress puzzle refers to the empirical regularity that firms with high measures of default likelihood earn anomalously low returns, despite having relatively high CAPM betas. This paper shows it is possible to qualitatively explain this anomaly using a consumption-based asset pricing model related to the literature on long-run risks. Apart from the usual assumptions of time varying, persistent conditional mean and volatility of consumption and dividend growth rates, I assume a natural cointegration between the levels of consumption and aggregate dividends. To model distress, I employ a simple intensity-based model of default. Distressed firms have short expected lifetimes, so they do not covary with the long-run risk factors, and thus earn low expected returns. Healthy firms are long-lived in expectation, and in the presence of the cointegrating relation, their prices do not respond strongly to the innovations in aggregate dividends, which lowers their betas. The model is calibrated to match the standard set of stock market moments and reproduces them well.
4 citations
TL;DR: The authors empirically verified that the relation is robustly positive and examined a battery of applicable channels from the literature and found the return predictability to be a surrogate for either the accruals and profitability effects or the net operating assets effect.
Abstract: The literature has proposed a positive relation and a negative relation between cash holdings and future stock returns We empirically verify that the relation is robustly positive We examine a battery of applicable channels from the literature and find the return predictability to be a surrogate for either the accruals and profitability effects or the net operating assets effect We further find that the relation depends on limits to arbitrage and hence the mispricing channel seems to be more appropriate After all, the relation does not present a new asset pricing regularity or anomaly
4 citations
TL;DR: In this article, the authors show that institutional and retail investors demand a risk premium from stocks and bonds with higher social media betas, and that social media risk carries an annual risk premium of 7.2% in stocks and 3.3% in bonds.
Abstract: Social media has become a real part of Main Street and Wall Street. Social media risk is hard to diversify, since it is a catalyst for contagion, causing an issue to `go viral' and affect a wide cross-section of firms. We show that institutional and retail investors demand a risk premium from stocks and bonds with higher social media betas. Unlike other risk factors whose origin is hard to pin down, social media risk is linked exclusively to the age of social media and did not exist prior to the rise of today's social media giants. Social media risk carries an annual risk premium of 7.2% in stocks and 3.3% in bonds.
4 citations
TL;DR: In this paper, the authors focused on determining the combination of the most significant variables that determine portfolio stock returns in Indonesia, using the standard of beta estimates, and also using an estimate of volatility models.
Abstract: In determining the rate of return of stocks, many models have been introduced. Equilibrium models like APT and multifactor models have been used in calculating the level of risk and returns through portfolio formation. Since the development initiated by Markowitz, the empirical results of many researchers have produced different points of view related to stock return and risk relationship. This study aims to look at what factors that can be used as a basis to determine returns and at the same time to minimize the risk. As in previous research studies using the CAPM, APT and multifactor models, this study focuses on determining the combination of the most significant variables that determine portfolio stock returns in Indonesia. In addition to using the standard of beta estimates, this study also uses an estimate of volatility models. To obtain the best model, the first group of variables was selected through several test models of equilibrium. This allows the best model to only include several valid variables. The results show that the CAPM is not valid and that market capitalization variable can explain changes in the portfolio yield more than do other variables. The model of the APT shows that macroeconomic and market risk premium are significant in explaining changes in portfolio returns, except for the production index. Several fundamental factors of the multifactor models are also found to be significant variables, including rating, and that liquidity factor is still an investment benchmark in Indonesia. It is proven that the volume and frequency of trades are consistently significant in all test models. Apart from that, it is also found that investors in Indonesia are still passive and not comfortable with risk, and follow traditional pattern. The simulation results of this study indicate that beta is estimated using a standard similar to that estimated using ARCH beta (volatility modeling), and that both methods show the same conclusion. In addition, the portfolio simulation indicates that there is an effect of market capitalization.
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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.
Abstract: Considerable attention has recently been given to general equilibrium models of the pricing of capital assets Of these, perhaps the best known is the mean-variance formulation originally developed by Sharpe (1964) and Treynor (1961), and extended and clarified by Lintner (1965a; 1965b), Mossin (1966), Fama (1968a; 1968b), and Long (1972) In addition Treynor (1965), Sharpe (1966), and Jensen (1968; 1969) have developed portfolio evaluation models which are either based on this asset pricing model or bear a close relation to it In the development of the asset pricing model it is assumed that (1) all investors are single period risk-averse utility of terminal wealth maximizers and can choose among portfolios solely on the basis of mean and variance, (2) there are no taxes or transactions costs, (3) all investors have homogeneous views regarding the parameters of the joint probability distribution of all security returns, and (4) all investors can borrow and lend at a given riskless rate of interest The main result of the model is a statement of the relation between the expected risk premiums on individual assets and their "systematic risk" Our main purpose is to present some additional tests of this asset pricing model which avoid some of the problems of earlier studies and which, we believe, provide additional insights into the nature of the structure of security returns The evidence presented in Section II indicates the expected excess return on an asset is not strictly proportional to its B, and we believe that this evidence, coupled with that given in Section IV, is sufficiently strong to warrant rejection of the traditional form of the model given by (1) We then show in Section III how the cross-sectional tests are subject to measurement error bias, provide a solution to this problem through grouping procedures, and show how cross-sectional methods are relevant to testing the expanded two-factor form of the model We show in Section IV that the mean of the beta factor has had a positive trend over the period 1931-65 and was on the order of 10 to 13% per month in the two sample intervals we examined in the period 1948-65 This seems to have been significantly different from the average risk-free rate and indeed is roughly the same size as the average market return of 13 and 12% per month over the two sample intervals in this period This evidence seems to be sufficiently strong enough to warrant rejection of the traditional form of the model given by (1) In addition, the standard deviation of the beta factor over these two sample intervals was 20 and 22% per month, as compared with the standard deviation of the market factor of 36 and 38% per month Thus the beta factor seems to be an important determinant of security returns
2,899 citations
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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.
Abstract: It is sometimes argued that an increase in stock market volatility raises required stock returns, and thus lowers stock prices. This paper modifies the generalized autoregressive conditionally heteroskedastic (GARCH) model of returns to allow for this volatility feedback effect. The resulting model is asymmetric, because volatility feedback amplifies large negative stock returns and dampens large positive returns, making stock returns negatively skewed and increasing the potential for large crashes. The model also implies that volatility feedback is more important when volatility is high. In U.S. monthly and daily data in the period 1926-88, the asymmetric model fits the data better than the standard GARCH model, accounting for almost half the skewness and excess kurtosis of standard monthly GARCH residuals. Estimated volatility discounts on the stock market range from 1% in normal times to 13% after the stock market crash of October 1987 and 25% in the early 1930's. However volatility feedback has little effect on the unconditional variance of stock returns.
1,793 citations
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.
Abstract: This paper examines a class of continuous-time models that incorporate jumps in returns and volatility, in addition to diffusive stochastic volatility. We develop a likelihood-based estimation strategy and provide estimates of model parameters, spot volatility, jump times and jump sizes using both S&P 500 and Nasdaq 100 index returns. Estimates of jumps times, jump sizes and volatility are particularly useful for disentangling the dynamic effects of these factors during periods of market stress, such as those in 1987, 1997 and 1998. Using both formal and informal diagnostics, we find strong evidence for jumps in volatility, even after accounting for jumps in returns. We use implied volatility curves computed from option prices to judge the economic differences between the models. Finally, we evaluate the impact of estimation risk on option prices and find that the uncertainty in estimating the parameters and the spot volatility has important, though very different, effects on option prices.
1,040 citations
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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.
Abstract: This paper proposes a new way to generalize the insights of static asset pricing theory to a multi-period setting. The paper uses a loglinear approximation to the budget constraint to substitute out consumption from a standard intertemporal asset pricing model. In a homoskedastic lognormal selling, the consumption-wealth ratio is shown to depend on the elasticity of intertemporal substitution in consumption, while asset risk premia are determined by the coefficient of relative risk aversion. Risk premia are related to the covariances of asset returns with the market return and with news about the discounted value of all future market returns.
805 citations
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.
Abstract: This study investigates whether market-wide liquidity is a state variable important for asset pricing. We find that expected stock returns are related cross-sectionally to the sensitivities of returns to fluctuations in aggregate liquidity. Our monthly liquidity measure, an average of individual-stock measures estimated with daily data, relies on the principle that order flow induces greater return reversals when liquidity is lower. Over a 34-year period, the average return on stocks with high sensitivities to liquidity exceeds that for stocks with low sensitivities by 7.5% annually, adjusted for exposures to the market return as well as size, value, and momentum factors.
789 citations