Posted Content•
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
Citations
More filters
TL;DR: In this paper, a zero-cost strategy that is long in low VOL and short in high VOL commodities yields an annualized return of 12.66% and a Sharpe ratio of 0.69.
Abstract: The detrended implied volatility of commodity options (VOL) forecasts the cross section of the commodity futures returns significantly. A zero-cost strategy that is long in low VOL and short in high VOL commodities yields an annualized return of 12.66% and a Sharpe ratio of 0.69. Notably, the excess returns based on the volatility strategy emanate mainly from its forecasting power for the future spot component, different from the other commodity strategies examined so far in the literature which are all driven by roll returns. This strategy demonstrates low correlations (below 10%) with the other strategies such as momentum or basis and performs especially well in recessions. Our results are robust after controlling for illiquidity, other commodity pricing factors, and exposure to the aggregate commodity market volatility. The VOL measure is associated with hedging pressure on the futures and especially on the options market. News media also helps amplify the uncertainty impact. Variables related to investors’ lottery preferences and market frictions are able to explain part of the predictive relationship.
6 citations
TL;DR: This article examined the effect of volatility persistence in explaining excess returns in conjunction with established factors and found that volatility persistence is significant in explaining the excess returns for medium to high turnover portfolios for portfolios sorted on size, and that not only volatility itself but also its persistence is important in explaining returns.
Abstract: In this paper, we examine the effect of volatility persistence in explaining excess returns in conjunction with established factors. We use an I-GARCH model to estimate volatility persistence for each company on the NYSE for each year between 1989 and 2014. We find that volatility persistence is significant in explaining excess returns for medium to high turnover portfolios. We also find a similar relationship for portfolios sorted on size. This study tries to disentangle the effects of various information asymmetry aspects in asset pricing and show that not only volatility itself but also its persistence is important in explaining returns.
6 citations
TL;DR: In this paper, the authors investigate two potential explanations: (1) each cohort adopts and retains operating innovations that are associated with higher risks and (2) increasing numbers of younger and less-experienced firms are represented in each new cohort.
Abstract: Prior studies show that the risk level of each new cohort of listed firms is higher than its predecessor’s. We find that these risk differences are persistent and investigate two potential explanations: (1) Each cohort adopts and retains operating innovations that are associated with higher risks and (2) increasing numbers of younger and less-experienced firms are represented in each new cohort. Our results support the first explanation. Each new cohort uses riskier production technologies and operates in more competitive product markets than its predecessor.
6 citations
TL;DR: In this article, the authors show that the cross-section of the German stock market re-effects a negative premium for idiosyncratic risk, even after controlling for the three Fama-French factors, and they estimate a signi ficant risk premium of -0.8% per month.
Abstract: Although most of the empirical and theoretical asset pricing literature predicts a positive or no signi ficant relationship between idiosyncratic volatility and returns, Ang et al. (2006, 2009) find that high idiosyncratic volatility stocks have low returns and vice versa. We deliver further evidence and show that the cross-section of the German stock market re effects a negative premium for idiosyncratic risk. Even after controlling for the three Fama-French factors we estimate a signi ficant risk premium of -0.8% per month. In addition, we undertake further robustness checks like the differentiation between upside and downside idiosyncratic volatility, the application of the (E)GARCH approach to estimate idiosyncratic risk and the use of monthly instead of daily data. However, the puzzle still prevails.
6 citations
TL;DR: This article found that short sellers' trades play an important role in the price discovery of competing firms, beyond their direct effects documented previously, and that trading cost reductions are an important driver for trading a firm's competitors rather than the firm's own stocks.
Abstract: Firm-level monthly short interest is positively and significantly related to the returns of firms that compete in the same product markets. This finding is robust to standard controls and cannot be explained by industry momentum, industry lead-lag relationships, or industry information spillover effects. Short interest also contains information about the fundamentals of competing firms. Trading cost reductions are an important driver for trading a firm’s competitors rather than the firm’s own stocks. Our findings suggest that short sellers’ trades play an important role in the price discovery of competing firms, beyond their direct effects documented previously.
6 citations
References
More filters
Posted Content•
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
Posted Content•
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
Posted Content•
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