Evaluating Asset-Pricing Models in International Financial Markets
Abstract: This thesis consists of three empirical studies on asset-prices in international financial markets. The purpose is three-fold. First, to evaluate whether good predictions of economic variables may be obtained by pooling information from a broad group of financial variables. Second, to formulate asset-pricing models from seven established stock markets. Third, to evaluate the asset-pricing models in the presence of short-sales.Chapter 2 applies a large data set, consisting of 167 monthly time series for the UK, both economic and financial, to simulate out-of-sample predictions of industrial production, inflation, three-month Treasury-Bills and other variables. Fifteen dynamic factor models that allow forecasting based on large panels of time series are considered. The performances of these factor models are then compared to the following competing models: a simple univariate autoregressive, a vector autoregressive, a leading indicator, and a non-expectational Phillips curve models. The results show that the dynamic factor models outperform the competing models in forecasting at 6-, 12-, and 24-month horizons. Two main findings are highlighted. First, the financial markets have a predictive power in terms of economic activity. Second, for some variables, the dynamic factor model appears to be more reliable than other competing models.In an attempt to analyze the equity premium puzzle and the risk-free rate puzzle, Chapter 3 compares different asset-pricing models within an international framework. To do so, it evaluates the performance of the following models: time separable-constant relative risk aversion, internal habit, external habit with externality, external habits which yield a constant risk-free rate, adaptive learning with constant gain, and state non-separability. The data are from seven industrialized countries, namely the United States, Canada, Japan, the United Kingdom, France, Denmark, and Sweden. Regarding empirical evidence, this thesis uses the Hansen-Jagannathan approaches to impose volatility restrictions on the asset-pricing models. The time-separable, adaptive learning and external habit models fail, and the evidence favors the internal habit persistence model. However, success is limited to some countries and to the equity premium puzzle rather than the risk-free rate puzzle. Finally, the state-non-separable specification consistently resolves the equity premium puzzle for all the countries.Chapter 4 analyzes the effect of market frictions on the equity premium puzzle. Indeed, in the standard asset-pricing model with time-separable preferences, the volatility of the intertemporal marginal rate of substitution is too low for plausible values of risk aversion to be consistent with consumption and asset return data. Following this, the Hansen-Jagannathan method is applied to evaluate the equity premium puzzle for the UK in two directions. First, the time-separable model, the internal and the external habit formation models and the state non-separable model are examined under the assumptions of both frictionless markets and market frictions. Second, a bootstrap experiment is conducted to show that these asset-pricing models violate the Hansen-Jagannathan bound in almost all the samples. Indeed, because of the changes in the sample means in consumption growth and asset returns, all the models appear to be weak under frictionless markets. By contrast, asset-pricing models with market frictions are much more successful in the bootstrap experiment.
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