Hossein Asgharian

Cross-sectional analysis of Swedish stock returns with time-varying beta: the Swedish stock market 1983-96

This paper analyses the ability of beta and other factors, like firm size and book-to-market, to explain cross‐sectional variation in average stock returns on the Swedish stock market for the period 1983–96. We use a bivariate GARCH(1,1) process to estimate time-varying betas for asset returns. The estimated variances of these betas, derived from a Taylor series approximation, are used for correcting errors in variables. An extreme bound analysis is utilized for testing the sensitivity of the estimated coefficients to changes in the set of included explanatory variables. Our results show that the estimated conditional beta is a more accurate measure of the true market beta than the beta estimated by OLS. The coefficient for beta is not significantly different from zero, while the variables book-to-market and leverage have significant coefficients, and the latter coefficients are also robust to model specification. Excluding the down turn 1990–92 from the sample shows that the significance of the risk premium for leverage might be considered as an industry effect during this extreme (Less)

An event study of price movements following realized jumps

Price jumps are mostly related to investor reactions to unexpected extreme news. We perform an event study of price movements after jumps to analyse if investors’ reactions are affected by psychological biases. We employ recent non-parametric methods based on intraday returns to separate large price movements that are related to unexpected news from those merely caused by periods of high volatility. In general, we find evidence for irrational pricing, which can be associated with investors’ optimistic behavior in a bull market and the pessimism prevailing in a bear market. Furthermore, our analysis confirms the conjecture that small firms are more subject to speculative trading than large firms.

A Critical Investigation of the Explanatory Role of Factor Mimicking Portfolios

The common approach for constructing factor mimicking portfolios is to go long in assets with high loadings and to short-sell those with low loadings on some background factors. As a result portfolios containing stocks with low loading on the background factor receive negative betas against the corresponding mimicking portfolio. Thus, such portfolios appear as hedges against the background risk and may in tests of asset pricing models receive significant positive intercepts. The final result regarding acceptance or rejection of an asset pricing model may therefore to some extent be understood as a random outcome.

Financial and Economic Integration's Impact on Asian Equity Markets’ Sensitivity to External Shocks

This paper investigates the spillover effects from U.S. and regional stock markets on local stock markets in the Pacific Basin region and China. We also analyze if the spillover depends on countries’ financial and economic integration. We apply a stochastic volatility model with jumps in order to separate the spillover of extreme shocks from those of normal shocks. We find that the spillovers of both normal and extreme shocks are significant for almost all Asian countries except China. We also find that the time‐variation in stock market interdependence can largely be associated with economic integration.

Book-to-Market and Size Effect: Compensations for risks or outcomes of market inefficiencies

We employ the optimal orthogonal portfolio approach to investigate if the size and book-to-market effects in US data are related to risk factors beside the market risk. This method enables us to estimate the upper limit of the risk premium, due to observed as well as all possible unobserved factors, which can be derived from a linear asset pricing model. As a corollary, it is possible to divide the observed average asset return into three parts: one explained by the market factor, one due to the unobserved factors, and finally the non-risk-based (NRB) component. Our empirical results confirm the existence of latent risk factors, which cannot be captured by the market index. In particular, the size effect is related to some other background risk factors than the market portfolio, but a large part of observed book-to-market effect has a NRB explanation.

A Comparative Analysis of Ability of Mimicking Portfolios in Representing the Background Factors

Our aim is to give a comparative analysis of ability of different factor mimicking portfolios in representing the background factors. Our analysis contains a cross-sectional regression approach, a time-series regression approach and a portfolio approach for constructing factor mimicking portfolios. The focus of the analysis is the power of mimicking portfolios in the asset pricing models. We conclude that the time series regression approach, with the book-to-market sorted portfolios as the base assets, is the most proper alternative to construct mimicking portfolios for factors for which a time-series of factor realisation is available. To construct mimicking portfolios based on the firm characteristics we suggest a loading weighted portfolio approach.

The explanatory role of factor portfolios for industries exposed to foreign competition: evidence from the Swedish stock market

The purpose is to find factors that are important for explaining expected returns of the Swedish industrial portfolios for the period 1980 to 1997 and to analyse the factor exposures of these portfolios. We have chosen factors that are important for a small open economy. In addition to considering the small sample problem we apply an extreme bounds analysis to investigate robustness of the estimated parameters to the changes in model specification. Our overall conclusion is that the market portfolio is more or less the only factor for explaining expected returns and covariances of the industrial portfolios but some of the other factors are important for explaining the variances of individual industries. JEL Classification:.

The Explanatory Role of Factor Portfolios for Industries Exposed to Foreign Competition

Our purpose is to find factors that are important for expected returns and risk of Swedish industrial portfolios during 1980–1997. The tested factors are supposed to be essential for a small open economy. We take into account the small sample problem that surfaces in the form of firms dominating the value weighted test portfolios. An extreme bound analysis (EBA) investigates the robustness of the estimated parameters. Principal component analysis is used to assess the importance of the factors in explaining return covariances. Our overall conclusion is that the market portfolio, which refers to the world as well as the Swedish market portfolio, is almost sufficient for explaining expected returns and risk.

Economic Policy Uncertainty and Long-Run Stock Market Volatility and Correlation

We use Baker, Bloom, and Davis’s (2016) economic policy uncertainty indices in combination with the mixed data sampling (MIDAS) approach to investigate long-run stock market volatility and correlation, primarily for the US and UK. Long-run US–UK stock market correlation depends positively on US economic policy uncertainty shocks. The dependence is asymmetric, with only positive shocks - increasing uncertainty - being of importance. The US long-run stock market volatility depends significantly on US economic policy uncertainty shocks but not on UK shocks, while the UK long-run stock market volatility depends significantly on both. Allowing for US economic policy uncertainty shocks improves the out-of-sample forecasting of US–UK stock market correlation and enhances portfolio performance. Similar results apply to the long-run correlation between the US and Canada, China, and Germany.

Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing

We suggest a bivariate component GARCH model that simultaneously obtains factor betas’ long- and short-run components. We apply this new model to industry portfolios using market, small-minus-big, and high-minus-low portfolios as risk factors and find that the cross-sectional average and dispersion of the betas’ short-run component increase in bad states of the economy. Our analysis of the risk premium highlights the importance of decomposing risk across horizons: The risk premium associated with the short-run market beta is significantly positive. This is robust to the portfolio-set choice.