Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

Asset Pricing in a Production Economy with Chew–Dekel Preferences

In this paper we provide a thorough characterization of the asset returns implied by a simple general equilibrium production economy with Chew–Dekel risk preferences and convex capital adjustment costs. When households display levels of disappointment aversion consistent with the experimental evidence, a version of the model parameterized to match the volatility of output and consumption growth generates unconditional expected asset returns and price of risk in line with the historical data. For the model with Epstein–Zin preferences to generate similar statistics, the relative risk aversion coefficient needs to be about 55, two orders of magnitude higher than the available estimates. We argue that this is not surprising, given the limited risk imposed on agents by a reasonably calibrated stochastic growth model.

Three essays in empirical asset pricing

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

An examination of conditional asset pricing models in the Australian equities market

This article examines the link between macroeconomic variables and equity returns in Australia by testing conditional asset pricing models. We find that conditioning the Fama-French model with a series of macroeconomic variables does not considerably improve its performance. However, we do find that the Fama-French factors, SMB and HML, retain their ability to explain equity returns even after the model is conditioned on macroeconomic variables. Our findings suggest that investors do not adjust their risk premiums according to the changes in the macroeconomic variables we employ.

Tests of conditional asset pricing models in the brazilian stock market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

A stochastic discount factor approach to asset pricing using panel data

Using the Pricing Equation, in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) mimicking portfolio which relies on the fact that its logarithm is the ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences, making it suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles.

Testes de validade do capital asset pricing model no mercado acionário de São Paulo : um estudo indicativo do poder de teste da metodologia de Fama e Macbeth

Utiliza a técnica de simulação para estimar a "eficiência" de se testar o modelo Capital Asset Pricing Model (CAPM) num mercado com características do mercado acionário paulista, marcado por elevado retorno e alta volatilidade.

Exact arbitrage, well-diversified portfolios and asset pricing in large markets

: In a model of a nancial market with an atomless continuum of assets, we give a precise and rigorous meaning to the intuitive idea of a \well-diversi ed" portfolio and to a notion of \exact arbitrage". We show this notion to be necessary and su cient for an APT pricing formula to hold, to be strictly weaker than the more conventional notion of \asymptotic arbitrage", and to have novel implications for the continuity of the cost functional as well as for various versions of APT asset pricing. We further justify the idealized measure-theoretic setting in terms of a pricing formula based on \essential" risk, one of the three components of a tri-variate decomposition of an asset's rate of return, and based on a speci c index portfolio constructed from endogenously extracted factors and factor loadings. Our choice of factors is also shown to satisfy an optimality property that the rst m factors always provide the best approximation. We illustrate how the concepts and results translate to markets with a large but nite number of assets, and relate to previous work.

A stochastic discount factor approach to asset pricing using panel data asymptotics

Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the "common feature" in every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences. The techniques discussed in this paper were applied to two relevant issues in macroeconomics and finance: the first asks what type of parametric preference-representation could be validated by asset-return data, and the second asks whether or not our SDF estimator can price returns in an out-of-sample forecasting exercise. In formal testing, we cannot reject standard preference specifications used in the macro/finance literature. Estimates of the relative risk-aversion coefficient are between 1 and 2, and statistically equal to unity. We also show that our SDF proxy can price reasonably well the returns of stocks with a higher capitalization level, whereas it shows some difficulty in pricing stocks with a lower level of capitalization.

O modelo de avaliação de ativos: (Capital asset pricing model)

Examina o modelo de seleção de portfólios desenvolvido por Markowitz, principalmente no que concerne: as suas relações com a teoria da utilidade de Von Neumann-Morgenstern; aos algo ritmos de solução do problema de Programação Quadrática paramétrica dele decorrente; a simplificação proporcionada pelo Modelo Diagonal de Sharpe. Mostra que a existência de um título sem risco permite a especificação do Teorema da Separação e a simplificação do problema de seleção de portfólios. Analisa o modelo denominado por CAPM, de equilíbrio no Mercado de Capitais sob condições de incerteza, comparando os processos dedutivos empregados por Lintner e Mossin. Examina as implicações decorrentes do relaxamento dos pressupostos subjacentes ã esse modelo de equilíbrio geral, principalmente a teoria do portfólio Zero-Beta desenvolvida por Black.

CAPM "Capital Asset Pricing Model": o modelo de avaliação de ativos: uma revisão da literatura e dos testes empíricos

Levantamento bibliográfico abrangendo os principais trabalhos relativos ao "CAPM - Capital Asset Pricing Model" que se acham esparsos em vasta literatura. Aborda desde a teoria de seleção de carteira, o desenvolvimento e testes do modelo, suas implicações para a teoria financeira. Inclui também considerações sobre o relaxamento dos pressupostos básicos e "sobre a influência do fator inflacionário na forma e validade do modelo.