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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: The authors used both panel and cross-sectional models for 28 industrialized countries observed from 2001 to 2009 and reported a number of findings regarding the determinants of the volatility of returns on cross-border asset holdings (i.e., equity and debt).
Abstract: Using both panel and cross-sectional models for 28 industrialized countries observed from 2001 to 2009, we report a number of findings regarding the determinants of the volatility of returns on cross-border asset holdings (i.e., equity and debt). Greater portfolio concentration and an increase in assets held in emerging markets lead to an elevation in earning volatility, whereas more financial integration and a greater share held in Organization for Economic Cooperation and Development countries and by the household sector cause a reduction in the return volatility. Larger asset holdings by offshore financial corporations and non-bank financial institutions cause higher market volatility, although they affect volatility in the equity and bond markets in the opposite way. Overall, both panel and cross-sectional estimations provide very similar results (albeit of different magnitude) and are robust to the endogeneity problem.
9 citations
TL;DR: In this paper, the authors study the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model (International ICAPM).
Abstract: We study risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model (International ICAPM). The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns, proxied by US stock index returns. We also incorporate own country variances as additional determinants of Frontier country returns. Our model allows for the covariance risk to be time-varying. Time-varying correlations are captured by utilizing the Dynamic Conditional Correlations (DCC) model. The premium per unit of covariance risk is allowed to vary over time as well. Thus, both the risk and risk premium on Frontier country market returns are time-varying in our model. We find the conditional correlations, although modest on average, to vary over time, and suggestive of substantial diversification benefits from investing in Frontier markets versus a portfolio holding just US stocks. These correlations display no time trend, suggesting that diversification benefits have not diminished with recent globalization. Our results suggest statistically significant impact of both US covariance risk and own country variance risk in explaining Frontier country returns. Time-variation in the price of covariance risk is also found to be statistically significant for most Frontier market returns. However, own country variance risk is found to be quantitatively more important.
9 citations
TL;DR: In this paper, the authors use returns of actively managed mutual funds to estimate risk premiums associated with stock characteristics and find that when characteristics are associated with adverse news, fund returns reflect expected premiums better than stock returns.
Abstract: We use returns of actively managed mutual funds to estimate risk premiums associated with stock characteristics. Skilled fund managers can avoid stocks with deteriorating future fundamentals. As a result, when characteristics are associated with adverse news, fund returns reflect expected premiums better than stock returns. We use the pricing of accrual quality (AQ) as a setting to demonstrate the benefits of our approach. Prior research finds no significant AQ premiums in stock returns. In contrast, we document a significantly positive AQ premium in fund returns. This premium is especially large in portfolios selected by highly skilled managers. The premium is also present in a broad sample of individual stocks. Specifically, the loadings on the mutual-fund-based AQ factor explain the cross-section of stock returns. In additional tests, we document significant positive premiums for other characteristics that are “anomalously” negatively correlated with individual stock returns, including forecast dispersion and idiosyncratic return volatility.
9 citations
TL;DR: In this paper, the authors investigate whether the cross-sectional dispersion of stock returns represents a priced state variable and find that stocks with high sensitivities to dispersion offer low expected returns.
Abstract: This study investigates whether the cross-sectional dispersion of stock returns, which reflects the aggregate level of idiosyncratic risk in the market, represents a priced state variable. We find that stocks with high sensitivities to dispersion offer low expected returns. Furthermore, a zero-cost spread portfolio that is long (short) in stocks with low (high) dispersion betas produces a statistically and economically significant return, after accounting for its exposure to other systematic risk factors. Dispersion is associated with a significantly negative risk premium in the cross-section (-1.32% per annum) which is distinct from premia commanded by a set of alternative systematic factors. These results are robust to a wide set of stock characteristics, market conditions, and industry groupings.
9 citations
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TL;DR: This article showed that high-beta portfolios dramatically outperform low-beta in low volatility environments and underperform in high-volatility environments, when combining the two market environments, the inevitable result shows no relationship between beta and return.
Abstract: Previous research indicates that long-term investors are not compensated for beta or volatility risk. This study shows these two results are at least partly due to the mathematics of compounding exacerbated in high volatility markets. Theoretical beta portfolios defined to perform exactly as the Capital Asset Pricing Model (CAPM) would predict on a monthly basis, show that high beta portfolios dramatically outperform in low volatility environments and underperform in high volatility environments. Empirically sorted beta portfolios confirm the results and show in a low volatility environment, high beta portfolios outperform low beta portfolios by 0.42% a month and underperform by 0.51% in high volatility environments. When combining the two market environments, the inevitable result shows no relationship between beta and return.
9 citations
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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