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Does Subjective Evaluation of Probability Impact Asset Prices? The Nobel Prize–winning capital asset pricing model (CAPM) predicts that expected excess return of any asset is positively proportional to its exposure to the overall market: the beta, leading to an upward-sloping security market line. However, this prediction is contradicted by empirical studies that the return–beta slope is often flat or even downward-sloping, a puzzle called the “beta anomaly.” The CAPM is premised upon the notion that market participants are all rational, including that they are able to objectively evaluate probabilities. However, evidence abounds that individuals are often unable to do so, examples being purchase of lottery tickets and insurance products, in which the extremely small probabilities of winning or losing big are exaggerated. This phenomenon of distorting probabilities at both tails is called “probability weighting” (PW), which is a key component of modern behavioral finance. The paper “Beta and Coskewness Pricing: Perspective from Probability Weighting” approaches the beta anomaly through PW. It offers an explanation of the beta anomaly via a new theoretical CAPM involving PW and an extensive empirical study.

We study the impact of dependence uncertainty on the expectation of the product of $d$ random variables, $\mathbb{E}(X_1X_2\cdots X_d)$ when $X_i \sim F_i$ for all~$i$. Under some conditions on the $F_i$, explicit sharp bounds are obtained and a numerical method is provided to approximate them for arbitrary choices of the $F_i$. The results are applied to assess the impact of dependence uncertainty on coskewness. In this regard, we introduce a novel notion of "standardized rank coskewness," which is invariant under strictly increasing transformations and takes values in $[-1,\ 1]$.

The paper uses Coskewness as risk measure, average return and gives detail of efficient skewness (gamma) of a diversity of currency portfolios. This paper also applies ARCH-GARCH model, significant properties of GARCH allow to efficient modeling financial time series having obese conclusions. Then, we connect Coskewness with ARCH-GARCH models to optimize currency portfolio. To conclude, an empirical study of ten currency portfolios from Pakistan currency exchange market is performed and all the results suggest that Coskewness can better characterized the risk-adjustment and average variance and the performance of ARCH-GARCH model is better than that of ARIMA model in portfolio optimization.

We show that the prices of risk for factors that are nonlinear in the market return can be obtained using index option prices. The price of coskewness risk corresponds to the market variance risk premium, and the price of cokurtosis risk corresponds to the market skewness risk premium. Option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An analysis of factor models with coskewness risk indicates that the new estimates of the price of risk improve the models’ performance compared with regression-based estimates.

We offer a new perspective on the low-beta anomaly by acknowledging the omitted-variable problem in the correlation component of beta: Correlation is “plagued” by firm size (the omitted variable) to exhibit a negative price. Once isolating the size impact, a hidden positive price emerges for the size-orthogonalized component of correlation. Further analyses suggest that i). The positive price of the size-orthogonalized component is not due to mispricing, supporting the return comovement-based pricing channel. ii). The negative price of the size-explained component is related to illiquidity and coskewness. iii). The omitted-variable problem also applies to the pricing of beta.

This paper shows that low‐risk anomalies in the capital asset pricing model and in traditional factor models arise when investors require compensation for coskewness risk. Empirically, we find that option‐implied ex ante skewness is strongly related to ex post residual coskewness, which allows us to construct coskewness factor‐mimicking portfolios. Controlling for skewness renders the alphas of betting‐against‐beta and betting‐against‐volatility insignificant. We also show that the returns of beta‐ and volatility‐sorted portfolios are driven largely by a single principal component, which in turn is explained largely by skewness.

In this paper, we build on a concept of self-supervision by taking RGB frames as input to learn to predict both action concepts and auxiliary descriptors e.g., object descriptors. So-called hallucination streams are trained to predict auxiliary cues, simultaneously fed into classification layers, and then hallucinated at the testing stage to aid network. We design and hallucinate two descriptors, one leveraging four popular object detectors applied to training videos, and the other leveraging image- and video-level saliency detectors. The first descriptor encodes the detector- and ImageNet-wise class prediction scores, confidence scores, and spatial locations of bounding boxes and frame indexes to capture the spatio-temporal distribution of features per video. Another descriptor encodes spatio-angular gradient distributions of saliency maps and intensity patterns. Inspired by the characteristic function of the probability distribution, we capture four statistical moments on the above intermediate descriptors. As numbers of coefficients in the mean, covariance, coskewness and cokurtotsis grow linearly, quadratically, cubically and quartically w.r.t. the dimension of feature vectors, we describe the covariance matrix by its leading n' eigenvectors (so-called subspace) and we capture skewness/kurtosis rather than costly coskewness/cokurtosis. We obtain state of the art on five popular datasets such as Charades and EPIC-Kitchens., ACM MM'21

We develop an intertemporal asset pricing model where cash-flow news, discount-rate news, and their second moments are priced by the market. This model generalizes the market-return decomposition framework, showing that intertemporal considerations imply a decomposition of squared market returns (coskewness risk). Our model accounts for 68% of the return variation across portfolios sorted by size, book-to-market ratio, momentum, investment, and profitability for a modern U.S. sample period. Further, our findings highlight the importance of covariation risk, that is, the risk of simultaneous unfavorable shocks to cash flows and discount rates, in understanding equity risk premia.

Principal skewness analysis (PSA) has been introduced for feature extraction in hyperspectral imagery. As a thirdorder generalization of principal component analysis (PCA), its solution of searching for the local maximum skewness direction is transformed into the problem of calculating the eigenpairs (the eigenvalues and the corresponding eigenvectors) of a coskewness tensor. By combining a fixed-point method with an orthogonal constraint, the new eigenpairs are prevented from converging to the same previously determined maxima. However, in general, the eigenvectors of the supersymmetric tensor are not inherently orthogonal, which implies that the results obtained by the search strategy used in PSA may unavoidably deviate from the actual eigenpairs. In this paper, we propose a new nonorthogonal search strategy to so lve this problem and the new algorithm is named nonorthogonal principal skewness analysis (NPSA). The contribution of NPSA lies in the finding that the search space of the eigenvector to be determined can be enlarged by using the orthogonal complement of the Kronecker product of the previous eigenvector with itself, instead of its orthogonal complement space. We also give a detailed theoretical proof on why we can obtain the more accurate eigenpairs through the new search strategy by comparison with PSA. In addition, after some algebraic derivations, the complexity of the presented algorithm is also greatly reduced. Experiments with both simulated data and real multi/hyperspectral imagery demonstrate its validity in feature extraction.

This paper uses tests drawn from the literature on financial market contagion measured by changes in higher-order comoments to establish the patterns in the interdependence between equity markets in Shanghai and Shenzhen with Hong Kong as mainland China liberalized their capital market. On the announcement of the opening of the Shanghai market correlations rise, but subside by the launch. Following the launch changes in coskewness, cokurtosis and covolatility emerge. The liberalization process is complete by mid-September 2016.

Financial integration is East Asia and the ASEAN nations is investigated using a new approach based on entropy theory. An important advantage of the proposed framework is that it takes into account changes in integration arising from higher order moments including coskewness and cokurtosis as well as more traditional measures based on second order moments. The analysis focusses on the role of the U.S. in understanding changes in global integration over time, as well as changes in regional integration arising from China. Using daily stock returns from 1997 to 2016, the empirical results show an overall trend to improvements in financial integration over time with deviations from the trend occurring during periods of financial crises in Asia in 1997–98, the U.S. in 2007–10 and the recent European debt crisis. The influence of the Chinese economy mainly through its trading linkages is found to be an important determinant of financial integration over time both regionally as well as globally.

We examine whether investors receive a compensation for holding crash-sensitive stocks. We capture the crash sensitivity of stocks by their lower tail dependence with the market based on copulas. Stocks with strong contemporaneous crash sensitivity clearly outperform stocks with weak crash sensitivity and a trading strategy based on past crash sensitivity delivers positive abnormal returns of about 4% p.a. This effect cannot be explained by traditional risk factors and is different from the impact of beta, downside beta, and coskewness. Our findings are consistent with results from the empirical option pricing literature and support the notion that stock market investors are crash-averse.

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.

A new measure of asymmetry in dependence is proposed that 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.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. We propose new systematic tail risk measures constructed using two different approaches. The first is a nonparametric measure that captures the tendency of a stock to crash at the same time as the market, while the second is based on the sensitivity of stock returns to innovations in market crash risk. Both tail risk measures are associated with a significantly positive risk premium after controlling for other measures of downside risk, including downside beta, coskewness and cokurtosis. Using the new measures, we examine the relevance for investors of the tail risk premium over different horizons.

İktisatçılar devletin ve piyasanın ekonomideki görece rolü hakkında, farklı ideolojik, metodolojik, felsefi yaklaşımlar neticesinde uzlaşma ve uzlaşmazlık içinde olmuşlardır. Bu bağlamda çalışmanın temel amacı, Türk üniversitelerinde çalışan akademisyen iktisatçıların devletin ve piyasaların rolü, iktisat metodolojisi ve iktisat ideolojisi konusundaki görüşlerini incelemektir. Ayrıca çalışma bu görüşlerin akademik unvanlarından, çalıştıkları ülkeden, lisans eğitimi alanından ve cinsiyetten etkilenip etkilenmediğini incelemektedir. Bu amaçla, çalışmanın birinci bölümünde bilimsel disiplin olarak iktisat ve iktisadın bilimsel yöntemine dair görüşler ele alınmaktadır. İkinci bölümde iktisadi düşüncenin ideolojik yanları, iktisadi düşünce okullarında devlet-piyasa ilişkisine dair görüşler ve bu görüşlerdeki çatışmalar ele alınmıştır. Üçüncü bölümde ise iktisatçıların görüşlerini inceleyen ampirik çalışmalar incelenmiş ve tezin çalışmasına dair ampirik araştırmanın tasarımı tanıtılmıştır. Çalışmanın örneklemini, Türkiye merkezli üniversitelerde "iktisat", "ekonomi" ve "ekonomi ve finans" bölümlerinde çalışan ekonomistler oluşturmaktadır Son bölümde toplanan verilerin temel bulguları ve sonuçları sunulmaktadır. Sonuçlar iktisadın temel kabulleri, metodolojisi, devletin ve piyasanın görece rolüne dair görüşler arasındaki farklılıkları açıklamakta akademisyenlerin akademik unvanlarının, eğitim aldıkları ülkenin, lisans eğitimi aldıkları alanın ve cinsiyetlerinin önemli olduğunu göstermektedir., Economists have been in compromise and disagreement about the relative role of the state and the market in the economy as a result of different ideological, methodological and philosophical approaches. In this context, the main purpose of the study is to examine the opinions of academic economists employed in Turkish universities on the relative role of the government and markets, economic methodology and economic ideology. In addition, the study examines if these opinions are influenced by their academic title, the country they study, the field of undergraduate education and gender. For this purpose, in the first chapter of the study, opinions about the scientific method of economics and economics as a scientific discipline were discussed. In the second chapter, the ideological aspects of economic thought, the views on the state-market relationship in economic thought schools and the conflicts in these views were discussed. In the third chapter, the empirical studies examining the attitudes of economists are examined and the design of the empirical research is presented. The sample of the study was drawn from the economists employed in departments of "economics", "economy" and "economics and finance" in Turkey based universities. The last section presents the main findings and results of the data collected. The results show that academic titles, graduate education country, degree of education and gender are important in explaining the differences between the basic assumptions, methodology of economics, and opinions on the relative role of the state and the market.

Bakgrund I snart ett halvt sekel har aktier med lågt beta visat sig generera hög avkastning i förhållande till risk. Denna observation brukar benämnas lågriskanomalin och ända sedan fenomenet uppmärksammades av Black 1972 har olika studier försökt förklara orsaken till dess förekomst. Empiriska resultat har inte bara visat på att lågriskaktier presterat bättre än vad teorin förutspår, utan till och med visat på ett negativt samband mellan risk och avkastning. Detta är i rak motsats till traditionella avkastningsmodeller som exempelvis CAPM, vilken hävdar att avkastning är en direkt funktion av systematisk risk – beta. Syfte Syftet med denna uppsats är att undersöka förekomsten av lågriskanomalin på den svenska aktiemarknaden och analysera huruvida anomalin kan förklaras av den tredje ordningens centralmoment, skevhet. Vidare syftar uppsatsen till att testa och analysera möjligheten att hantera skevhetsrisk genom att inkludera denna som en variabel i en tredimensionell optimeringsmodell. Genomförande Studien bygger på insamlad kurshistorik mellan åren 1998–2018 för samtliga aktier som har ingått i indexet OMXSPI. Totalt har 9650 risksorterade portföljer skapats, där loggning genomförts av portföljegenskaper och analysmått. Sambandet mellan lågriskanomalin och skevhetsrisk har testats genom hypotestester baserat på inkluderandet av en tredimensionell optimeringsmodell samt Three-moment CAPM. Slutsats Resultaten visar att aktier med lägre beta i genomsnitt har presterat signifikant bättre än högbetaaktier sett till både riskjuterad- samt faktiskt avkastning. Förhållandet mellan risk och avkastning har således varit negativt för den undersökta perioden. Vidare påvisas en signifikant riskaversion mot skevhetsrisk, men trots detta tyder samtliga av studiens tester på att skevhet är otillräckligt för att förklara detta fenomen. Genom tredimensionell optimering visas även hur portföljspecifik skevhet kan hanteras utan att ge signifikant försämrad avkastning. Dessa resultat faller i linje med att lågriskanomalin uppstår som en konsekvens av ett ineffektivt utbud- och efterfrågesamband och kan därmed ses som ett argument mot den effektiva marknadshypotesen Background For nearly half a century, stocks with low beta has shown to generate high return relative to risk. This observation is called the low risk anomaly and ever since it was observed by Black in 1972, different studies have tried to find an explanation for its presence. Empirical results have not only found that low risk stocks outperform in terms of riskadjusted returns, but also that the relationship between risk and return seem to have a negative correlation. This is the exact opposite of what is suggested by traditional financial models, such as CAPM, which claim that return on assets is a direct function of the its systematic risk – beta. Purpose The purpose of this study is to investigate the presence of the low risk anomaly on the Stockholm stock exchange and analyse if it can be explained by the third central moment, skewness. Further we intend to test and analyse if it is possible to control skewness risk by including it as a variable in three-dimensional optimization. Methodology The thesis is conducted by acquiring historical stock prices for the years 1998–2018 for all shares included in the index OMXSPI. To answer the underlying research questions, 9650 risk-sorted portfolios are created where portfolio performance indicators are being logged. Furthermore, the relationship between the low risk anomaly and skewness-based risk is examined through hypothesis testing, which depend on a three-dimensional optimization model as well as the Three-moment CAPM. Results The results of this study show that stocks with low beta has significantly outperformed high-beta stocks in terms of both risk-adjusted as well as actual return. This implies that the relationship between risk and return has been negative during the time period investigated. Furthermore, the results show a significant aversion towards skewness risk. However, all of the tests indicate that skewness is insufficient in the explanation of the low risk anomaly. It has been shown by three-dimensional optimization that it is possible to control portfolio skewness, without a significant loss in return. These results are in line with the conclusion that the low risk anomaly is an effect of inefficiency in supply and demand and can therefore be seen as an argument against the efficient market hypothesis.

We report the results of regressing the Sharpe ratios of 72 cryptocurrencies on first, second and third co-moments of their returns. Our general aim is to examine the risk-return trade-off characteristics of cryptocurrencies. In other words, to determine whether the returns of cryptocurrencies justify their huge volatility especially with regard to the higher moment components of their systemic risk? We find that adjusted Sharpe ratios of the cryptocurrencies and traditional indexes do not differ significantly in this respect.

We develop a strategy for testing endogenously contagion within banking sector, stock market indices and Credit Default Swap Spreads. We present evidence of strong contagion in several cases and markets. Contagion seems to be widespread during the Global Financial Crisis and the recent European Sovereign Debt Crisis. Our results are important for a better understanding of contagion and the development of macroprudential tools for financial stability surveillance.

There is ample evidence that stock returns exhibit non-normal distributions with high skewness and excess kurtosis. Experimental evidence has shown that investors like positive skewness, dislike extreme losses and show high levels of prudence. This has motivated the introduction of the four-moment capital asset pricing model (CAPM). This extension, however, has not been able to successfully explain average returns. Our paper argues that a number of pitfalls may have contributed to the weak and conflicting empirical results found in the literature. We investigate whether conditional models, whether models that use individual stocks rather than portfolios and whether models that extend both the moment and factor dimension can improve on more traditional static, portfolio-based, mean–variance models. More importantly, we find that the use of a scaled coskewness measure in cross-section regression is likely to be spurious because of the possibility for the market skewness to be close to zero, at least for some periods. We provide a simple solution to this problem.

This study examines the cross-sectional variation of futures returns from different asset classes. The monthly returns are positively correlated with downside risk and negatively correlated with coskewness. The asymmetric volatility effect generates negatively skewed returns. Assets with high coskewness and low downside betas provide hedges against market downside risk and offer low returns. The high returns offered by assets with low coskewness and high downside betas are a risk premium for bearing downside risk. The asset pricing model that incorporates downside risk partially explains the futures returns. The results indicate a unified risk perspective to jointly price different asset classes.

Este estudo busca identificar o comportamento da assimetria sistemica (coassimetria) e da curtose sistemica (cocurtose) no aprecamento de ativos no mercado acionario brasileiro (na BM&F Bovespa). Foi utilizada a metodologia explorada por Harvey e Siddique (2000) para estimar o grau de coassimetria e cocurtose para as acoes em cada mes t, seguindo a regressao CAPM. O modelo de tres fatores foi utilizado segundo a metodologia de Fama e French (1993) com modificacoes para o calculo dos fatores seguindo a metodologia explorada por Neves (2003). Os resultados demonstram que para o mercado brasileiro, os ativos com coassimetria e cocurtose negativas tendem a render mais do que ativos com coassimetria e cocurtose positivas. Segundo observacoes no mercado americano e londrino, como os investidores esperam maiores retornos por um maior risco, foi constatado preferencia por coassimetria negativa e cocurtose positiva. No Brasil foi constatado que para o caso da coassimetria o mesmo se repete, porem para a cocurtose isso nao acontece, ocorre o inverso, o que pode levar a conclusao de um comportamento tipicamente avesso ao risco.

A flexible multivariate model of a time-varying joint distribution of asset returns is developed which allows for regime switching and a joint skew-normal distribution. A suite of tests for linear and nonlinear financial market contagion is developed within the framework. The model is illustrated through an application to contagion between US and European equity markets during the Global Financial Crisis. The results show that correlation contagion dominates coskewness contagion, but that coskewness contagion is significant for Greece. A flight to safety to the US is also evident in the significance of breaks in the skewness parameter in the crisis regime. Comparison to the Asian crisis shows that similar patterns emerge, with a flight to safety to Japan, and Malaysia affected by coskewnes contagion with Hong Kong.

Many asset pricing studies assume that a stock's coskewness or idiosyncratic skewness is priced because of the characteristic's influence on portfolio skewness. From empirical returns, we show that the number of stocks in a portfolio is the most important determinant of portfolio skewness, while component stocks' coskewness or idiosyncratic skewness has marginal effects. This result indicates that individual stock skewness does not well represent portfolio skewness.

This study presents an improved model for estimating life insurer cost of capital with the inclusion of upside and downside risk factors and controlling for life insurer characteristics. Although various asymmetric measures of market risk have been shown to be priced factors for the broader equity market, life insurer realized equity returns include a much larger premium for bearing downside risk, even after controlling for firm characteristics and other measures of risk. Cross-sectional regression analysis finds a positive (negative) premium for downside (upside) betas, conditional on down and up markets, respectively. Coskewness and cokurtosis are also priced factors.

© 2016 Elsevier Ltd We study a relation between higher order comoments and dependence structure of equity portfolio in the US and UK by relying on a simple portfolio approach where equity portfolios are sorted on the higher order comoments. We find that beta and coskewness are positively related with a copula correlation, whereas cokurtosis is negatively related with it. We also find that beta positively associates with an asymmetric tail dependence whilst coskewness negatively associates with it. Furthermore, two extreme equity portfolios sorted on the higher order comoments are closely correlated and their dependence structure is strongly time-varying and nonlinear. Backtesting results of value-at-risk and expected shortfall demonstrate the importance of dynamic modeling of asymmetric tail dependence in the risk management of extreme events.

Joint tests of contagion are derived which are designed to have power where contagion operates simultaneously through coskewness, cokurtosis and covolatility. Finite sample properties of the new tests are evaluated and compared with existing tests of contagion that focus on a single channel. Applying the tests to daily Eurozone equity returns from 2005 to 2014 shows that contagion operates through higher order moment channels during the GFC and the European debt crisis, which are not necessarily detected by traditional tests based on correlations.

The coskewness–cokurtosis pricing model is equivalent to absence of any positive-alpha return for which the residual risk has positive coskewness and negative cokurtosis with the market. This parallels the CAPM and also the fundamental theorem of asset pricing.

Despite the fact that it is easy to see intuitively why skewness and coskewness should matter for asset pricing, it is difficult to build a model that links analytically skewness premia to deep structural parameters governing preferences and the distribution of shocks. This paper takes up the challenge and studies the effect of skewness and coskewness on asset valuation. To reach this important goal, asset returns skewness is modeled with promising Azzalini’s [1985. Scandinavian Journal of Statistics 12, 171–178] skew-normal distribution. With this assumption, we are now able to derive explicit expressions of assets skewness premiums and to shed a new light on asset valuation.

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

This paper derives a liquidity-adjusted conditional two-moment capital asset pricing model (CAPM) and a liquidity-adjusted conditional three-moment CAPM respectively based on theory of stochastic discount factor. The liquidity-adjusted conditional two-moment CAPM shows that a security's conditional expected excess return consists of three parts: its conditional expected liquidity cost, the systemic risk premium and the liquidity risk premium. The liquidity-adjusted conditional three-moment CAPM shows that a security's conditional expected excess return depends on its conditional expected liquidity cost, the conditional covariance between its return and the market return, the conditional covariance between its liquidity cost and the market liquidity cost, and the conditional coskewness of its return and the market return.

Modelos de apreçamento de ativos têm sido um tema sob constante investigação em finanças. Desde o capital asset pricing model (CAPM) proposto por Sharpe (1964), tais modelos relacionam, geralmente de maneira linear, a taxa de retorno esperada de um ativo ou carteira de ativos com fatores de risco sistêmico. Esta pesquisa apresenta um teste de um modelo de apreçamento, com dados brasileiros, introduzindo em sua formulação fatores de risco baseados em comomentos estatísticos. O modelo proposto é uma extensão do CAPM original acrescido da coassimetria e da cocurtose entre as taxas de retorno das ações das empresas que compõem a amostra e as taxas de retorno da carteira de mercado. Os efeitos de outras variáveis, como o valor de mercado sobre valor contábil, a alavancagem financeira e um índice de negociabilidade em bolsa, serviram de variáveis de controle. A amostra foi composta de 179 empresas brasileiras não financeiras negociadas na BM&FBovespa e com dados disponíveis entre os anos de 2003 a 2007. A metodologia consistiu em calcular os momentos sistêmicos anuais a partir de taxas de retornos semanais e em seguida testá-los em um modelo de apreçamento, a fim de verificar se há um prêmio pelo risco associado a cada uma dessas medidas de risco. Foi empregada a técnica de análise de dados em painel, estimada pelo método dos momentos generalizado (GMM). O emprego do GMM visa lidar com potenciais problemas de determinação simultânea e endogeneidade nos dados, evitando a ocorrência de viés nas estimações. Os resultados das estimações mostram que a relação das taxas de retorno dos ativos com a covariância e a cocurtose são estatisticamente significantes. Os resultados se mostraram robustos a especificações alternativas do modelo. O artigo contribui para a literatura por apresentar evidências empíricas brasileiras de que há um prêmio pelo risco associado aos momentos sistêmicos. Asset pricing models have been a constant theme in finance research. Since the Capital Asset Pricing Model (CAPM) proposed by Sharpe (1964), such models linearly relate the expected rate of returns of an asset or portfolio of assets with systemic risk factors. This research presents a test of a pricing model with risk factors based on statistical comoments and using a Brazilian dataset. The proposed model is an extension of the original CAPM with the addition of coskewness and cokurtosis between stock rates of return and the market portfolio rates of return. The effects of other variables such as market to book value, financial leverage and a negotiability index served as control variables. The sample consisted of 179 non-financial Brazilian companies traded on BM&FBovespa with data available from 2003 to 2007. Annual systemic moments were calculated from weekly rates of return. They were then tested on a pricing model in order to check for the existence of a risk premium associated with each of these risk measures. We employed a Generalized Method of Moments (GMM) panel data analysis. The use of GMM aims to address potential problems of endogeneity and simultaneous determination of the data, avoiding the occurrence of bias in the estimates. The estimation results show that the relationship between rates of return and covariance and cokurtosis are statistically significant. The results were robust to alternative model specifications. This research contributes to the literature by presenting empirical evidence that there is a Brazilian risk premium associated with systemic moments. Modelos de fijación de activos han sido un tema constante en la investigación de finanzas. Desde el modelo de fijación de precios de activos de capital (CAPM) propuesto por Sharpe (1964) se relacionan, generalmente en forma lineal, la tasa de retorno esperada de un activo o cartera de activos con factores de riesgo sistémico. Esta investigación presenta una prueba de un modelo de precios con los datos de Brasil y factores de riesgo com el apoyo de comomentos estadísticos. El modelo propuesto es una extensión del CAPM original más la cocurtose y la coassimetria entre las tasas de rendimiento de las acciones de las empresas que componen la muestra y las tasas de retorno de la cartera de mercado. Los efectos de otras variables como el valor de mercado sobre el valor en libro, el apalancamiento financiero y un índice de comerciabilidad bursátil como variables de control. La muestra estuvo conformada por 179 empresas no financieras brasileñas que cotizan en el BM&FBovespa y con los datos disponibles entre los años 2003 a 2007. La metodología consistió en calcular los momentos sistémicos anuais a partir de las tasas de rendimiento semanais y luego ponerlos a prueba en un modelo de precios con el fin de comprobar si hay una prima de riesgo asociados a cada una de estas medidas de riesgo. Empleamos um técnica de análisis de datos de panel calculada por el método generalizado de momentos (GMM). El uso del método generalizado de momentos tiene como objetivo abordar los posibles problemas de endogeneidad y determinación simultánea de los datos, evitando la aparición de sesgos en las estimaciones. Los resultados de la estimación indican que la relación de las tasas de retorno de los activos y la covarianza y cocurtose son estadísticamente significativas. Los resultados fueron robustos a especificaciones alternativas del modelo. Esta investigación contribuye a la literatura mediante la presentación de evidencia empírica de que hay una prima de riesgo asociado con momentos sistémicos.