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The main goal of this paper is an application of Bayesian inference intesting the relation between risk and return on the financial instruments. Onthe basis of the Intertemporal CAPM model we built a general sampling modelsuitable in analysing such a relationship. The most important feature of ourassumptions is that the skewness of the conditional distribution of returns isused as an alternative source of relation between risk and return. This generalspecification relates to GARCH-In-Mean model. In order to make conditionaldistribution of financial returns skewed we considered a constructive approachbased on the inverse probability integral transformation. In particular, weapply the hidden truncation mechanism, two equivalent approaches of the inversescale factors, order statistics concept, Beta and Bernstein distributiontransformations, and also the constructive method. Based on the daily excessreturns on the Warsaw Stock Exchange Index we checked the empirical importanceof the conditional skewness assumption on the relation between risk and returnon the Warsaw Stock Market. We present posterior probabilities of all competingspecifications as well as the posterior analysis of positive sign of the testedrelationship.

On the Empirical Importance of the Conditional Skewness Assumption in Modelling the Relationship Between Risk and Return