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I use Stochastic Discount Factors to examine the sources of the idiosyncratic volatility premium. I find that non-zero risk aversion and firms’ non-systematic coskewness determine the premium on idiosyncratic volatility risk. The firm’s non-systematic coskewness measures the comovement of the asset’s volatility with the market return. When I control for the non-systematic coskewness factor, I find no significant relation between idiosyncratic volatility and stock expected returns. My results are robust across different sample periods and firm characteristics.

The Capital Asset Pricing Model (CAPM) is one of the most used model in finance during the last five decades. This is despite heavy criticism against it along with an ongoing debate among academia about the empirical validity of the model. Three major extensions to the conventional model have been suggested; higher-moment CAPM, multi-factor model and conditional CAPM. All these models have shown mixed results in empirical studies. In the recent past, these extensions are integrated and tested for empirical validity and show some positive results (Vendrame, Tucker & Guermat, 2016). In this study, the empirical validity of conditional four-moment CAPM is tested on the Colombo Stock Exchange (CSE) of Sri Lanka. Individual stock returns on 74 listed companies covering a 17-year period from 2000 to 2016 are used. A two step procedure is followed with the estimation of the short window time series regressions in the first step, while cross-sectional regressions are estimated in the second step. Test results show inconclusive evidence about the conditional four-moment CAPM. Risk of coskewness is significant though risk of covariance and co-kurtosis are not significant explaining the average return on individual stocks on the CSE during the period under study.

The previous studies on coskewness and cokurtosis between assets concentrate on the effects of coskewness and cokurtosis on the returns and prices of financial assets. This paper explores the default correlation in the presence of coskewness and cokurtosis between two firm values. In doing so, we extend the structural model of Merton (1974) to incorporate coskewness and cokurtosis. We can observe some findings as follows. First, there are no significant effects of skewness and kurtosis associated with each individual firm return on default correlation. Second, the lower coskewness (or the higher cokurtosis) is, the larger default correlations are. But we can observe the opposite result for the firms with low credit rating as the maturity gets longer.

In the context of a three-moment intertemporal capital asset pricing model specification, we characterize conditional coskewness between stock and bond excess returns using a bivariate regime-switching model. We find that both conditional U.S. stock coskewness (the relation between stock return and bond volatility) and bond coskewness (the relation between bond return and stock volatility) command statistically and economically significant negative ex ante risk premiums. The impacts of stock and bond coskewness on the conditional stock and bond premiums are quite robust to various model specifications and various sample periods, and also hold in another major developed country (the United Kingdom). The findings also carry important implications for portfolio management.

This paper examines whether additional risk factors such as the variance, skewness, and coskewness of returns offer an appropriate explanation of company returns in less developed capital markets. Arguments for considering some additional factors in pricing models to better deal with such situations are presented. Using individual company returns from a range of developing Asian capital markets, empirical tests examine the importance of these extra risk factors. Results indicate that both individually and when in combination, variance and coskewness are significantly related to returns in these markets. Skewness is less consistently important. Robustness tests confirm that these measures tend not to capture size or book to market factors.

A new class of tests of contagion is proposed identifying transmission channels of financial market crises through changes in higher order moments of the distribution of returns such as coskewness. Applying the framework to test for contagion in real estate and equity markets following the Hong Kong crisis in 1997–1998 and the U.S. subprime crisis in 2007 shows that the coskewness-based tests of contagion detect additional channels not identified by the correlation-based tests. Implications of contagion in pricing exchange options where there is a change in higher order comoments of returns on the underlying assets are also investigated.

In the presence of nonnormally distributed asset returns, optimal portfolio selection techniques require estimates for variance-covariance parameters, along with estimates for higher-order moments and comoments of the return distribution. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean-variance analysis. This article extends the existing literature, which has mostly focused on the covariance matrix, by introducing improved estimators for the coskewness and cokurtosis parameters. We find that the use of these enhanced estimates generates a significant improvement in investors' welfare. We also find that it is only when improved estimators are used that portfolio selection with higher-order moments dominates mean-variance analysis from an out-of-sample perspective. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

This paper develops exact distribution-free tests of unconditional mean-variance efficiency. These new tests allow for unknown forms of non-normalities, conditional heteroskedasticity, and other non-linear temporal dependencies among the absolute values of the error terms in the asset pricing model. Exactness here rests on the assumption that the joint temporal error density is symmetric around zero. This still leaves open the possibility of return distribution asymmetry via coskewness with the benchmark portfolio. A simulation study shows that the new tests have very good power relative to that of many commonly used tests. The inference procedures developed are further illustrated by tests of the mean-variance efficiency of a market index using a 42-year sample of monthly returns on ten U.S. equity portfolios.

We investigate the impact of coskewness on the variation of portfolio excess returns in Istanbul Stock Exchange (ISE) over the period July 1999 to December 2005. We form portfolios according to size, industry, size and book-to-market ratio, momentum and coskewness and compare alternative asset pricing models. The traditional capital asset pricing model (CAPM) and the three-factor model of Fama and French are tested in the multivariate testing procedure of Gibbons–Ross–Shanken (1989). Coskewness is introduced as a fourth factor and its incremental effect over CAPM and Fama–French factors is examined both in multivariate tests and in cross-sectional regressions. The findings reveal that coskewness is able to explain the size premium in ISE. Hence, the basic two-moment CAPM without the coskewness factor would underestimate the expected return of size portfolios. Multivariate test results indicate that coskewness reduces the pricing bias, albeit insignificantly. Cross-sectional analysis uncovers that coskewne...

This study examines the incentives in fund management due to the adoption of specific performance measures. A mean–variance measure such as Jensen's alpha incentivizes fund managers to load negative coskewness risk. This risk is shown to be priced in the UK stock market during the period January 1991– December 2005, bearing a premium of 2.09% p.a. Hence, a new performance measure, the intercept of the Harvey–Siddique two-factor asset pricing model is proposed to be more appropriate for prudent investors. Using this model, the performance of UK equity unit trusts is examined for the same period. Though most of the managers significantly underperformed their benchmark, they correctly responded to their incentives, loading negative coskewness and reaping part of the corresponding premium.

The Margrabe formula is used extensively by theorists and practitioners not only on exchange options, but also on executive compensation schemes, real options, weather and commodity derivatives, etc. However, the crucial assumption of a bivariate normal distribution is not fully satisfied in almost all applications. The impact of nonnormality on exchange options is studied by using a bivariate Gram-Charlier approximation. For near-the-money exchange options, skewness and coskewness induce price corrections which are linear in moneyness, while kurtosis and cokurtosis induce quadratic price corrections. The nonnormality helps to explain the implied correlation smile observed in practice.

The coskewness matrix is a (p)x(p^2) parameter matrix useful for studying the third-order interactions between variables and computing the skewness of linear combinations of variables. The classical sample estimator of the coskewness matrix performs poorly in terms of mean squared error (MSE) when the sample size is small, even in moderate dimensions. A possible approach to improve estimation is to use shrinkage estimators that offer a compromise between the (unbiased) sample coskewness matrix and a (possibly biased) target matrix (with lower estimation variance) with the aim of minimizing the MSE. We improve upon the existing literature by proposing unbiased estimators, using multivariate k-statistics and polykays, for the MSE loss function and by including the possibility of having multiple target matrices. Simulations show the superiority of our estimators in both the single-target and the multi-target setting for skewed data. Accurate coskewness estimation is highly valued in the field of portfolio optimization (among others) where we show that the out-of-sample skewness of the maximum skewness optimized portfolio is higher when using the proposed shrinkage coskewness matrix estimates.

A new measure of asymmetry in dependence is proposed which is based on taking the difference between the margin-free coskewness parameters of the underlying copula. The new measure and a related test are applied to both a hydrological and a financial market data sample and we show that both samples exhibit systematic asymmetric dependence., Discussion Paper / SFB823;22, 2016

Javier Estrada has argued that differences attributable to the bifurcation of beta on either side of mean returns, at least in emerging markets, are too substantial to ignore.1 We should likewise expect to find considerable differences in financial performance arising from the deployment of a four-moment CAPM, the proper specification of this augmented CAPM according to cross moments, and the bifurcation of coskewness and cokurtosis along the upside and downside of mean returns.

We present hedge fund performance estimates that adjust for stale prices, Fama-French risk factors and skewness. We contrast these new performance estimates with traditional performance measures. Using three-factor models to adjust for staleness in prices and to incorporate Fama-French factors along with the Harvey-Siddique (2000) two-factor model that incorporates skewness, we find that for the period 1990–2003, all hedge fund categories achieve above average performance when measured against an aggregate market index. More significantly, however, when we estimate performance at the individual hedge fund level, we discover that only 40 to 47% of the funds are shown to achieve an above average performance over that time period depending on the model used. These results have important implications for investors, endowments and pensions when they choose hedge fund managers.

We develop a one-period model of investor asset holdings where investors have heterogeneous preference for skewness. Introducing heterogeneous preference for skewness allows the model's investors, in equilibrium, to underdiversify. We find suppport for our model's three key implications using a dataset of 60,000 individual investor accounts. First, we document that the portfolio returns of underdiversified investors are substantially more positively skewed than those of diversified investors. Second, we show that the apparent mean-variance inefficiency of underdiversified investors can be largely explained by the fact that investors sacrifice mean-variance efficiency for higher skewness exposure. Furthermore, contrary to the asset-pricing predictions of models that incorporate return skewness in the context of full diversification, we show that idiosyncratic skewness, and not just coskewness, can impact equilibrium prices. Third, the underdiversification of investors does not appear to be coincidentally related to skewness. Stocks most often selected by underdiversified investors have substantially higher average skewness -- especially idiosyncratic skewness -- than stocks most often selected by diversified investors.

We explore the empirical usefulness of conditional coskewness to explain the cross-section of equity returns. We find that coskewness is an important determinant of the returns to equity, and that the pricing relationship varies through time. In particular we find that when the conditional market skewness is positive investors are willing to sacrifice 7.87% annually per unit of gamma (a standardized measure of coskewness risk) while they only demand a premium of 1.80% when the market is negatively skewed. A similar picture emerges from the coskewness factor of Harvey and Siddique (Harvey, C., Siddique, A., 2000a. Conditional skewness in asset pricing models tests. Journal of Finance 65, 1263–1295.) (a portfolio that is long stocks with small coskewness with the market and short high coskewness stocks) which earns 5.00% annually when the market is positively skewed but only 2.81% when the market is negatively skewed. The conditional two-moment CAPM and a conditional Fama and French (Fama, E., French, K., 1992. The cross-section of expected returns. Journal of Finance 47,427465.) three-factor model are rejected, but a model which includes coskewness is not rejected by the data. The model also passes a structural break test which many existing asset pricing models fail.

We derive computationally simple and intuitive expressions for score tests of Gaussian copulas against generalized hyperbolic alternatives, including symmetric and asymmetric Student t, and many other examples. We decompose our tests into third and fourth moment components, and obtain one-sided Likelihood Ratio analogs, whose standard asymptotic distribution we provide. Our Monte Carlo exercises confirm the reliable size of parametric bootstrap versions of our tests, and their substantial power gains over alternative procedures. In an empirical application to CRSP stocks, we find that short-term reversals and momentum effects are better captured by non-Gaussian copulas, whose parameters we estimate by indirect inference. Supplementary materials for this article are available online.

We consider the robustness of the least-squares inference of linear asset pricing models. We evaluate the asymptotic covariance matrices of the least-squares estimator of alphas and betas when the joint distribution of factors and error terms is independently and identically distributed without making any specific distributional assumptions. When the standard assumption of conditional homoskedasticity for the conditional covariance matrix of error terms given factors does not hold, we show the asymptotic covariance matrix for betas depends only on cokurtosis of factors and error terms while the asymptotic covariance matrix for alphas depends on cokurtosis as well as coskewness of factors and error terms. This implies the inference of betas is not affected by skewness of the underlying joint distribution. Numerical examples are provided using Fama and French's benchmark portfolio returns and factors.

A growing literature contends that, since returns are not normal, higher‐order comoments matter to risk‐averse investors. Fama and French (1993, 1995) find that nonmarket risk factors based on size and book‐to‐market ratio are priced by investors. We test the hypothesis that the Fama‐French factors simply proxy for the pricing of higher‐order comoments. Using portfolio returns over various time horizons, we show that adding a set of systematic comoments (but not standard moments) of order 3–10 reduces the explanatory power of the Fama‐French factors to insignificance in almost every case.

This article shows how the market coskewness model of Rubinstein (1973) and Kraus and Litzenberger (1976) is altered when a nonredundant call option is optimally traded. Owing to the option's nonredundancy, the economy's stochastic discount factor (SDF) depends not only on the market return and the square of the market return but also on the option return, the square of the option return, and the product of the market and option returns. This leads to an asset pricing model in which the expected return on any risky asset depends explicitly on the asset's coskewness with option returns. The empirical results show that the option coskewness model outperforms several competing benchmark models. Furthermore, option coskewness captures some of the same risks as the Fama--French factors small minus big (SMB) and high minus low (HML). These results suggest that the factors that drive the pricing of nonredundant options are also important for pricing risky equities.(JEL G11, G12, D61) Copyright 2006, Oxford University Press.

In this article we investigate portfolio coskewness using a quadratic market model as a return-generating process. We show that the portfolios of small (large) firms have negative (positive) coskewness with the market. We test an asset pricing model including coskewness by checking the validity of the restrictions that it imposes on the return-generating process. We find evidence of an additional component in expected excess returns, which is not explained by either covariance or coskewness with the market. However, this unexplained component is homogeneous across portfolios in our sample and modest in magnitude. Finally, we investigate the implications of erroneously neglecting coskewness for testing asset pricing models, with particular attention to the empirically detected explanatory power of firm size.

In this paper we examine the variables that explain the cross-section of UK stock returns. Previous studies have found that the CAPM beta has moderate or even insignificant explanatory power once the Fama French factors are included. However, we control for different realised risk premia in up and down markets by using the same methodology as Pettengill, Sundaram and Mathur (1995). Unlike previous work, we find that beta is highly significant in explaining the cross-section of UK stock returns and more importantly remains significant even when the Fama French factors are included in the cross-sectional regressions. We also investigate whether higher co-moments (co-skewness and co-kurtosis) have any explanatory power but find that empirical support is weaker.

This paper is an empirical study of asset pricing with the systematic skewness in the pricing model. We adopt the Fama-French three-factor model, which incorporates the firm-size and book-to-market ratio in asset pricing as the base case, and then includes the skewness factor used by Harvey and Siddique in the pricing model. The evidence shows that systematic skewness is significant and might be important in asset pricing when portfolios are formed by industry, firm-size, book-to-market, or momentum strategies. When portfolios are constructed by momentum or coskewness strategies, lower momentum, or lower coskewness portfolios exhibit higher skewness and higher kurtosis. When portfolios are grouped by excess returns, it is seen that the average excess return is positively correlated with size and coskewness. Thus the systematic skewness is closely related to firm size. And the relationship between systematic skewness and excess return is obscured by the reverse firm-size effect.

This research adds cokurtosis risk factor as a new factor into Moreno and Rodriguez (2009) five-factor model to be six-factor model to evaluate the equity mutual fund performance of three selected countries in Asia - China, Singapore and Thailand as representatives of fast growing Asian countries. To my knowledge, this is the first research to incorporate both coskewness and cokurtosis risk factors into Carhart (1997) four-factor model, to become a six-factor model, to explain the equity mutual fund returns. The result shows that coskewness risk factor show significance in Singapore for mutual fund evaluation. There are some little sign of mild support for the pricing of cokurtosis in Singapore and Thailand too. In China, even coskewness is not statistically but shows economically significantly difference at 2.7% per month. Adding coskewness and cokurtosis risk factors in CAPM or Carhart (1997), four-factor model show little increment in the explanatory power of the models.

This study investigates whether contagion occurred during the global financial crisis among EU and US financial markets. The methodology used to test for contagion is the Forbes and Rigobon cross-correlation test, the Li and Zhu non-parametric test, the Fry et al. coskewness test and the Hsiao cokurtosis and covolatility tests. These tests are applied to a set of bank sector CDS, insurance sector CDS, sovereign bond, equity and volatility indices for the time period from 2004 to 2012. The findings indicate significant evidence of contagion especially through the channels of higher order moments.

We measure risk preferences for decisions that involve more than a single monetary attribute. According to theory, the multivariate risk preferences correlation aversion, cross-prudence (coskewness preference) and cross-temperance (cokurtosis aversion) determine how univariate risk preferences over attributes co-vary and interact. We obtain model-free measurements of these multivariate risk preferences in three economic domains, viz., time preferences, social preferences, and preferences over waiting time. This first systematic empirical exploration of multivariate risk preferences provides evidence for assumptions made in economic models on inequality, labor, time preferences, saving, and insurance.

This research adds cokurtosis risk factor as a new factor into Moreno and Rodriguez (2009) five-factor model to be six-factor model to evaluate the equity mutual fund performance both unconditionally and conditionally, and between up and down market of three selected countries in Asia - China, Singapore, and Thailand as representatives of fast growing Asian countries. The result shows some empirical evidence for the difference in the performance of mutual funds between the positive excess market return period and negative excess market return period. The higher moment six factor model fits better and shows more explanation power in negative excess return market period. The predetermined public information variables used in conditional model do not help explain the equity mutual fund return in these countries. The bootstrap technique shows that many of the significance alphas that are shown in least square method are from sampling variability.

This research adds cokurtosis risk factor as a new factor into Moreno and Rodriguez (2009) five-factor model to be six-factor model to evaluate the equity mutual fund performance of three selected countries in Asia — China, Singapore, and Thailand as representatives of fast growing Asian countries. To my knowledge, this is the first research to incorporate both coskewness and cokurtosis risk factors into Carhart (1997) four-factor model, to become a six-factor model, to explain the equity mutual fund returns. The result shows that coskewness and cokurtosis risk factors show some significance in some countries in Asia. Adding coskewness and cokurtosis risk factors in both CAPM and four-factor model, show some increment in the explanatory power of the models.

Mutual funds seek alpha, but residual coskewness is also an important performance attribute. Alpha and residual coskewness relative to the market are negatively correlated in theory, so funds may generate undesirable residual coskewness in the pursuit of alpha. Empirically, the trade-off exists for mutual funds and is driven by both fund composition and actions of managers. Sorting funds by proxies for active management generates positive alpha, but also undesirable coskewness. Investment styles also carry skewness consequences, but only partially explain the trade-off in funds. A minority of funds overcome the trade-off. Thus, seeking alpha generally comes at a skewness cost.

Heteroskedasticity biases tests for contagion based on correlation coefficients. When contagion is defined as a significant increase in market comovement after a shock to one country, previous work suggests contagion occurred during recent crises. This paper shows that correlation coefficients are conditional on market volatility. Under certain assumptions, it is possible to adjust for this bias. Using this adjustment, there was virtually no increase in unconditional correlation coefficients (i.e., no contagion) during the 1997 Asian crisis, 1994 Mexican devaluation, and 1987 U.S. market crash. There is a high level of market comovement in all periods, however, which we call interdependence.

Spot power prices are volatile and since electricity cannot be economically stored, familiar arbitrage-based methods are not applicable for pricing power derivative contracts. This paper presents an equilibrium model implying that the forward power price is a downward biased predictor of the future spot price if expected power demand is low and demand risk is moderate. However, the equilibrium forward premium increases when either expected demand or demand variance is high, because of positive skewness in the spot power price distribution. Preliminary empirical evidence indicates that the premium in forward power prices is greatest during the summer months. WHOLESALE POWER MARKETS, where producers trade electricity among themselves and with power-marketing and power-distribution companies, have grown rapidly in recent years. 1 The U.S. Department of Energy ~2000! reports that U.S. wholesale power transactions during 1999 amounted to approximately 2.6 billion megawatt hours ~MWh!, or about $85 billion. The U.S. wholesale power market is soon likely to comprise the world’s largest commodity market. Electricity as a commodity has many interesting characteristics, most of which stem from the fact that it cannot be economically stored. 2 Market

This paper investigates nonlinear pricing kernels in which the risk factor is endogenously determined and preferences restrict the definition of the pricing kernel. These kernels potentially generate the empirical performance of nonlinear and multifactor models, while maintaining empirical power and avoiding ad hoc specifications of factors or functional form. Our test results indicate that preferencerestricted nonlinear pricing kernels are both admissible for the cross section of returns and are able to significantly improve upon linear single- and multifactor kernels. Further, the nonlinearities in the pricing kernel drive out the importance of the factors in the linear multi-factor model.

If asset returns have systematic skewness, expected returns should include rewards for accepting this risk. We formalize this intuition with an asset pricing model that incorporates conditional skewness. Our results show that conditional skewness helps explain the cross-sectional variation of expected returns across assets and is significant even when factors based on size and book-to-market are included. Systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent per year. Our results suggest that the momentum effect is related to systematic skewness. The low expected return momentum portfolios have higher skewness than high expected return portfolios.

Ang, Chen and Xing have shown in "Downside Risk" that stocks that covary strongly with the market during market declines have high average returns. The reward for bearing downside risk is not simply compensation for regular market beta, nor is it explained by coskewness or liquidity risk, or by size, value, and momentum characteristics. The downside beta premium is not for free. The drawdown is considerable amplified in times of market troubles. This working paper combines the results of Ang, Chen and Xing with a signal based approach developed in a previous working-paper. The implied-volatility-term-structure (IVTS) classifies market regimes. One invests only in the favorable regime fully into stocks with high downside beta. Due to this classification the downside beta premium is (almost) a free lunch.

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct "high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From backtesting, we find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.

This paper examines the empirical performance of a global conditional three-moment CAPM. We employ monthly Finnish stock market data for 1987–1995. To explore the robustness of the three-moment model, we also examine whether local equity market returns, exchange rate fluctuations and movements in overall stock market turnover come into play after accounting for global market portfolio risk exposures. Our findings indicate that these additional factors are not generally able to detect deviations from the three-moment CAPM and time-varying global coskewness affects the cross-section of expected returns on local size portfolios even after accounting for other factors.

I derive an equilibrium asset pricing model incorporating both systematic and idiosyncratic return asymmetries, and show their respective impact on expected returns. With systematic return asymmetry, investors allocate their wealth between the risk-free security, the market portfolio, and a factor which overweights assets with high systematic asymmetry. Investors who prefer positive asymmetry remain underdiversified from a mean-variance perspective to preserve skewness in their portfolio, and idiosyncratic asymmetry therefore is priced in equilibrium. I find that a systematic asymmetry factor and a factor capturing idiosyncratic asymmetry help explain the cross-sectional variation of expected returns across U.S. equities, international equity markets, government bonds, currencies, and commodities. My results offer a risk-based explanation of expected returns that contributes to our understanding of asset pricing across multiple markets.

This paper applies the methodology of Lambert and Hübner (2009) for creating fundamental risk factors and factor systematic variance, skewness, and kurtosis into returns from March 1989 to June 2008. The coskewness and cokurtosis premiums present significant monthly average returns of respectively 0.2% and 0.4% over the period. First, we show that our set of moment-related premiums consistently price 2 sets of 2x3 covariance/coskewness and of 2x3 covariance/cokurtosis portfolios. The model delivers for all portfolios low levels of specification errors, high levels of R2, and beta loadings consistent with the portfolio rankings. Second, we perform Fama and MacBeth (1973) cross-sectional regressions made of higher-moment market premiums and/or Fama and French (1993) factors on 25 and 100 two-dimensional portfolios sorted on size and bookto- market. Used separately, a four-moment factor model and a four-factor Fama and French (1993) and Carhart (1997) model have been shown to deliver similar model specification errors (alphas) for the size/BTM portfolios. The Four-Moment Asset Pricing Model captures however a higher proportion of the portfolio variability of size/BTM portfolios than an empirical Capital Asset Pricing Model. Finally, our study demonstrates that moment and empirical premiums present complementary significance over the period.

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we confirm recent results for US data and find evidence of a negative cross-sectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and short term return reversal. We argue that this is the case because these stocks have lottery-like characteristics, which is attractive to certain investors. Also, these stocks tend to be very volatile so that arbitrageurs are discouraged from correcting potential mispricing. As a consequence, these stocks are often overpriced and hence face lower expected returns. Second, when we control for extreme returns, the recently found negative relationship between idiosyncratic risk and future returns is less robust. In our models, after adding maximum returns, the relationship is insignificant and sometimes even positive. We also find that idiosyncratic skewness and coskewness play an important role for asset pricing, as predicted by several theoretical models.

This paper focuses on portfolio selection with a systematic skewness constraint within the mean-variance framework. We derive the composition of efficient portfolios in our model, and analyze the properties of these efficient portfolios. We show that the required systematic skewness is achieved at the expense of mean-variance efficiency, and find that the more stringent the constraint, the greater the loss in efficiency. Our numerical analysis indicates that the systematic skewness constraint helps enhance the skewness of efficient portfolios over the skewness of traditional efficient portfolios. In addition, investors with a greater skewness preference impose a more stringent coskewness constraint, and at the same time are willing to accept a higher risk. Finally, we establish the relationship between our model and the three-moment asset pricing model, and analyze the determinants of market prices of systematic variance and skewness implied by our model.

The aim of this paper is to investigate the contagion across real estate markets of four countries: Hong Kong, China, U.S. and U.K., during the financial tsunami in 2008. We use the Forbes-Rigobon test, the coskewness test and the cokurtosis test. We propose a new cokurtosis test constructed by extending the method of constructing the coskewness test to further higher order moments. It can show additional channels of contagion that other tests fail to show, and hence can provide more information on the direction of contagion, and reflect a more complete picture of the contagion pattern. The coskewness and cokurtosis tests show that contagion exists between the four countries, and the contagion effect is stronger between Hong Kong and China, and between U.S. and U.K. This provides clues for investors on how to diversify their investment to reduce their risk. This paper bridges the gap that previous works on contagion across real estate markets give mixed results, and gives a first insight into the contagion pattern of global real estate markets during the financial tsunami. First Publish Online: 2 Oct 2012

In this paper, we study stock market skewness/coskewness for seven Latin American emerging markets including Argentina, Brazil, Chile, Mexico, Colombia, Peru and Venezuela. Unlike the US, skewness in these countries is normally positive and driven by fundamentals. We find, however, that the skewness/coskewness of these emerging markets is time-varying and declines sharply during economic and political crises. During crises, panicked investors sell their securities producing sharp price declines that reduce skewness below its normal levels. This is the essence of our behavioral account. The result of the panic selling is also to produce increases in firms’ risks of default and illiquidity, both being factors that seem to be priced. We also find that firms with low skewness/coskewness command a risk premium, even when we control for other factors such as size, price-to-book ratio, liquidity risk and default risk. The pricing power of skewness and coskewness is consistent with the findings from developed countries such as U.S., but the statistical significance is only marginal probably because of small sample problems. Overall, our evidence provides support for both fundamental and behavioral explanations for skewness and coskewness and their changes in Latin America but stops short of being able to disentangle them.

This paper examines whether investors receive compensation for holding crash-sensitive stocks. We capture the crash sensitivity of stocks by their lower tail dependence (LTD) with the market based on copulas. We find that stocks with weak LTD serve as a hedge during crises, but, overall, stocks with strong LTD have higher average future returns. This effect cannot be explained by traditional risk factors and is different from the impact of beta, downside beta, coskewness, and cokurtosis. Our findings are consistent with results from the empirical option pricing literature and support the notion that investors are crash-averse.

Since hedge fund returns are not normally distributed, mean–variance optimization techniques are not appropriate and should be replaced by optimization procedures incorporating higher-order moments of portfolio returns. In this context, optimal portfolio decisions involving hedge funds require not only estimates for covariance parameters but also estimates for coskewness and cokurtosis parameters. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean–variance analysis. This article presents an application of the improved estimators for higher-order co-moment parameters, in the context of hedge fund portfolio optimization. The authors find that the use of these enhanced estimates generates a significant improvement for investors in hedge funds. The authors also find that it is only when improved estimators are used and the sample size is sufficiently large that portfolio selection with higher-order moments consistently dominates mean–variance analysis from an out-of-sample perspective. Their results have important potential implications for hedge fund investors and hedge fund of funds managers who routinely use portfolio optimization procedures incorporating higher moments.

In an intertemporal equilibrium asset pricing model featuring disappointment aversion and changing macroeconomic uncertainty, we show that besides the market return and market volatility, three disappointment related factors are also priced. They can be interpreted as a disappointment, a market downside, and a volatility downside factor, respectively. We find that stock returns reflect premiums for bearing undesirable exposures to these factors. The signs of estimated risk premiums are consistent with the theoretical predictions. Economic magnitudes suggest that long/short strategies on associated exposures earn more than 5% per annum, and these rewards are not explained by the coskewness, size, value, and momentum factors.

Bond skewness and coskewness (i.e., bond return comovement with market volatility) are both time varying, with cross-sectional variation driven by maturity and credit rating. Other things being equal, longer maturity bonds have lower skewness, and lower coskewness with respect to the bond market index; lower quality bonds have lower skewness, and higher coskewness with respect to the bond market index. Three-moment bond alphas (which account for coskewness effects) are time varying and predictable by market default spread. They are significantly different from, and often are closer to zero than, two-moment alphas (which ignore coskewness effects).

This study explores the impact of systematic risk (beta) and systematic coskewness on EREIT returns. The test uses the Skewness Preference CAPM, which includes the impact of the third moment on ret...

Episodes of extraordinary turbulence in global financial markets are examined during eight crises ranging from Asia in 1997-98 to the recent great recession of 2008-10. The analysis focuses on changes in the dependence structures of equity markets through correlation and coskewness to answer the question of whether the great recession is different to other crises in terms of shock transmission through contagion. The results show that ‘this time is different’ and that the great recession is truly a global financial crisis. Other US sourced crises do not affect other markets through contagion, and emerging market crises transmit unexpectedly.

We show theoretically that lower tail dependence ( χ ), a measure of the probability that a portfolio will suffer large losses given that the market does, contains important information for risk-averse investors. We then estimate χ for a sample of DJIA stocks and show that it differs systematically from other risk measures including variance, semi-variance, skewness, kurtosis, beta, and coskewness. In out-of-sample tests, portfolios constructed to have low values of χ outperform the market index, the mean return of the stocks in our sample, and portfolios with high values of χ . Our results indicate that χ is conceptually important for risk-averse investors, differs substantially from other risk measures, and provides useful information for portfolio selection.