A spatial analysis of international stock market linkages

We employ spatial econometrics techniques to investigate to what extent countries’ economic and geographical relations affect their stock market co-movements. Among the relations that we analyze, bilateral trade proves to be best suited to capture co-variations in returns. We find a strong effect of a unit shock to three regionally dominant countries, namely the US, the UK, and Japan, on other countries through the trade linkage. The degree of stock market dependence increases and the importance of proximity decreases over time and during recessions. We also analyze several regional crises and find a large impact of Thailand on its trade neighbors during the Asian crisis.     

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.     

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 period. Finally, we find a close dependence between the risk premium for beta and that for size and book-to-market. The omission of each of these variables may cause statistical bias in the estimated coefficient for beta.     

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.     

Book-to-market and size effects: 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.     

Jump Spillover in International Equity Markets

In this article we study jump spillover effects between a numberof country equity indexes. In order to identify the latent historicaljumps of each index, we use a Bayesian approach to estimatea jump-diffusion model on each index. We look at the simultaneousjump intensities of pairs of countries and the probabilitiesthat jumps in large countries cause jumps or unusually largereturns in other countries. In all cases, we find significantevidence of jump spillover. In addition, we find that jump spilloverseems to be particularly large between countries that belongto the same regions and have similar industry structures, whereas,interestingly, the sample correlations between the countrieshave difficulties in capturing the jump spillover effects.