ASSET PRICING IN THE ASIAN REGION

In this asset pricing study, three questions are addressed. First, does the multifactor model of Fama and French (1993) capture returns in Asian stock markets in a meaningful manner? Second, do small firms and high book-to-market equity firms carry a risk premia? Third, can competing hypotheses (such as survivorship bias, data-snooping and irrationality) explain the multifactor model results? The answers from this study are as follows: The multifactor model of Fama and French (1993) provides a parsimonious description of the cross-section of returns, with the relationship between firm size, book-to-market equity and average stock returns being robust for Asian markets over the 1990s. We find that small firms and high book-to-market equity firms carry a risk premia, providing opportunities for mean-variance efficient investors. Finally, our findings reject the claim that the results of multifactor model can be explained by competing hypotheses for the Asian experience.Multifactor asset pricing models, Asian region, size effect, book-to-market equity effect.

Multifactor consumption based asset pricing model of the UK stock market: The US stock market as a wealth reference

Copyright @ 2011 University of BirminghamHere a multifactor model of UK stock returns is developed, replac- ingHere a multifactor model of UK stock returns is developed, replacing the conventional consumption habit reference by a relation that depends on US wealth. Two step Instrumental Variables and Generalized Method of Moments estimators are applied to reduce the impact of weak instruments. The standard errors are corrected for the generated regressor problem and the model is found to explain UK excess returns by UK consumption growth and expected US excess returns. Hence, controlling for nominal effects by subtracting a risk free rate and conditioning on real US excess returns provides an appealing explanation of the equity premium puzzle. US excess returns. Hence, controlling for nominal e¤ects by subtracting a risk free rate and conditioning on real US excess returns provides an appealing explanation of the equity premium puzzle

Consistent Re-Calibration of the Discrete-Time Multifactor Vasi\v{c}ek Model

The discrete-time multifactor Vasi\v{c}ek model is a tractable Gaussian spot rate model. Typically, two- or three-factor versions allow one to capture the dependence structure between yields with different times to maturity in an appropriate way. In practice, re-calibration of the model to the prevailing market conditions leads to model parameters that change over time. Therefore, the model parameters should be understood as being time-dependent or even stochastic. Following the consistent re-calibration (CRC) approach, we construct models as concatenations of yield curve increments of Hull-White extended multifactor Vasi\v{c}ek models with different parameters. The CRC approach provides attractive tractable models that preserve the no-arbitrage premise. As a numerical example, we fit Swiss interest rates using CRC multifactor Vasi\v{c}ek models.Comment: 29 pages, 16 figures, 2 table

Estimation of continuous-time interest rate models: a nonparametric approach

This paper presents a general, nonlinear model for term structure interest rate. The approach is the same of Stanton (1997) but it has been extended to a multifactor model. The novel aspect is that rather than choosing the functional specification of the model, the process is generated from the data using approximation methods for multifactor continuous-time Markov processes. In applying this technique to the short and long end of the term structure for a general two-factor diffusion process for interest rates is possible to find some interesting nonlinearity in the interest rate data that are not considered in almost all parametric specifications of term structure interest rate model of the financial literature.continuous-time models, nonparametric estimation, multi-factor interest rate model

Autoregressive multifactor APT model for U.S. Equity Markets

Arbitrage Pricing Theory is a one period asset pricing model used to predict equity returns based on a multivariate linear regression. We choose three sets of factors – Market specific, firm specific, and an autoregressive return term to explain returns on twenty U.S. stocks, using monthly data over the period 2000-2005. Our findings indicate that, apart from the CAPM beta factor, at least five other factors are significant in determining time series and cross sectional variations in returns. The times series regression establishes factor loadings and the cross sectional regression gives the risk premiums associated with these factors.Equity Pricing; APT; Arbitrage pricing theory; Multifactor model; Security; Pricing; CAPM

Keeping up with the Joneses: An international asset pricing model

We derive an international asset pricing model that assumes local investors have preferences of the type "keeping up with the Joneses." In an international setting investors compare their current wealth with that of their peers who live in the same country. In the process of inferring the country's average wealth, investors incorporate information from the domestic market portfolio. In equilibrium, this gives rise to a multifactor CAPM where, together with the world market price of risk, there exists country-speciffic prices of risk associated with deviations from the country's average wealth level. The model performs signifficantly better, in terms of explaining cross-section of returns, than the international CAPM. Moreover, the results are robust, both for conditional and unconditional tests, to the inclusion of currency risk, macroeconomic sources of risk and the Fama and French HML factor.Consumption externalities, multifactor asset pricing model

The Volatility Structure of the Fixed Income Market under the HJM Framework: A Nonlinear Filtering Approach

This paper seeks to estimate a multifactor volatility model so as to describe the dynamics of interest rate markets, using data from the highly liquid but short term futures markets. The difficult problem of estimating such multifactor models is resolved by using a genetic algorithm to carry out the optimization procedure. The ability to successfully estimate a multifactor volatility model also eliminates the need to include a jump component, the existence of which would create difficulties in the practical use of interest rate models, such as pricing options or producing forecasts.term structure; volatility; mutlifactor; jump; eurodollar futures; genetic algorithm

A survey on risk-return analysis

This paper provides a review of the main features of asset pricing models. The review includes single-factor and multifactor models, extended forms of the Capital Asset Pricing Model with higher order co- moments, and asset pricing models conditional on time-varying volatility.Asset pricing, CAPM