scispace - formally typeset
Search or ask a question
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
Journal ArticleDOI
TL;DR: In this article, the authors show that the pricing of idiosyncratic volatility is beyond its function as a limit of arbitrage, and they consider evidence at odds with explanations based on difference of investor opinion and investor sentiment.
Abstract: Recent evidence (Stambaugh, Yu, and Yuan, 2015) indicates that the most promising explanation for the negative price of idiosyncratic volatility is from its function as a limit arbitrage. Our evidence incorporating firm specific news is inconsistent with the limited arbitrage explanation. Since mispricing is most likely to occur during news announcements, the pricing of news volatility (volatility contemporaneous to news announcements) should be stronger than that of non-news volatility (volatility without an identified news announcement). We find the opposite. Non-news volatility has robust negative price and lacks some of the key features expected from the limited arbitrage explanation. We conclude that the pricing of idiosyncratic volatility is beyond its function as a limit of arbitrage. In addition, we consider evidence at odds with explanations based on difference of investor opinion and investor sentiment. Hence the pricing of idiosyncratic volatility is a deeper puzzle.

3 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the effects of value relevance of earnings and incremental value of cash flows on net external, net debt and net equity financings on idiosyncratic risk.
Abstract: This paper first examines the effects of value relevance of earnings and incremental value relevance of cash flows on net external financing, net equity financing and net debt financing. The investors, in general, suffer beta risk and idiosyncratic risk of a firm. The former is the main determinant of risk premium, and the latter can be controlled by the manager. If the firm has better control of idiosyncratic risk, it implies the manager has larger influence on stock returns. Under control accruals, value relevance of earnings and incremental value relevance of cash flows, we also examine the effects of net external, net debt and net equity financings on idiosyncratic risk. To test whether the external financing policy of a firm is consistent with over-investment hypothesis, this study investigate the effects of net external, net debt and net equity financings on future stock returns under controlling for value relevance of earnings and cash flows. This paper further analyzes the relation between current idiosyncratic risk and future stock returns following financing activities. We find that external financing activities are positively related to value relevance of earnings but are unrelated to incremental value relevance of operating cash flows, and external financing is unrelated to value relevance of operating cash flows but is positively related to incremental value relevance of earnings. Moreover, debt financing is unrelated to value relevance of cash flows but is positively correlated to incremental value relevance of earnings, and equity financing is unrelated to value or incremental value relevance of earnings but is positively correlated to value relevance and incremental value relevance of cash flows. We also find that both value relevance of earnings and cash flows are positively correlated to idiosyncratic risk, and current idiosyncratic risk and equity financing are negatively correlated to future returns after controlling value relevance of earnings and cash flows.

3 citations

Journal ArticleDOI
TL;DR: In this article, Obrimah et al. find that oil prices affect market or portfolio expected returns on the NSE only via changes induced in the risk preferences of the "representative agent" that has exposure to both stock market return volatility risk and oil price risk.
Abstract: I find oil prices affect market or portfolio expected returns on the NSE only via changes induced in the risk preferences of the "representative agent" that has exposure to both stock market return volatility risk and oil price risk. This finding indicates oil prices do not affect portfolio returns on the NSE independent of their effects on the representative agent's risk preferences. In so far as the risk preference of the representative agent is concerned, empirical results characterize this agent as an hedging agent; that is, an agent who at the margin accepts negative risk premiums for market volatility risk. In empirical tests that substitute a portfolio subset of the NSE (the "OAH portfolio") whose pricing is shown to be characterized by risk aversion and skewness preference in Obrimah et al. (2015), the representative agent who holds the OAH portfolio and has exposure to oil price risk is a risk averse agent who at the margin demands positive risk premiums for market volatility risk. Combined, empirical findings imply the presence of multiple representative agents that have exposure to both stock market return volatility risk and oil price risk within the Nigerian Stock Exchange.

3 citations

Journal ArticleDOI
TL;DR: This article investigated the robustness of the Fama and French three-factor model in the context of the Shanghai and Shenzhen stock exchanges spanning the period 1995-2008 and found that high book-to-market (B/M) stocks outperform in both rising and falling markets.
Abstract: This study investigates the robustness of the Fama and French three-factor model in the context of the Shanghai and Shenzhen stock exchanges spanning the period 1995–2008. We show that the three-factor model does a meaningful job in describing the cross-section of stock returns in this developing market. However, whereas the stocks of small firms attract higher market risk (outperforming on average, but underperforming when the market declines), high book-to-market (B/M) stocks outperform in both rising and falling markets. Neither are we able to provide a risk-return based explanation for B/M stocks in terms of either higher leverage or volatility (the correlations being in the opposite direction). Overall, our findings are that B/M captures “value-for-money” firms (proxied by high earnings-to-price and cash-flow-to-price ratios) that are associated with lower levels of debt, and hence lower volatility.

3 citations

Posted Content
TL;DR: In this paper, a 3-period theoretical model was proposed to explain why market makers' compensation for supplying liquidity depends on short-term price reversal, and the model showed that market makers charge a higher premium for liquidity provision when the VIX is high.
Abstract: Market makers' compensation for supplying liquidity depends on short-term price reversal. Previous empirical studies show that when the VIX is high, the short-term price reversal effect is stronger, i.e. market makers charge a higher premium for liquidity provision. The 3-period theoretical model of this paper explains that this is the case for three reasons; when the VIX is high (1) market makers are more risk averse, (2) asset variances are higher, and thereby, an identical asset-specific liquidity shock creates a stronger short-term price reversal effect in an individual asset, and (3) asset correlations are higher, and thus, there is a higher risk of spillover of liquidity shocks among assets. Consequently, an escalated level of the VIX index rises market makers' required return for liquidity provision. Our empirical analyses robustly confirm these theoretical findings.

3 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

Journal ArticleDOI
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

Journal ArticleDOI
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