Quantile forecasts of daily exchange rate returns from forecasts of realized volatility

Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk. A quantile forecast is the product of two factors: the model used to forecast volatility, and the method of computing quantiles from the volatility forecasts. In this paper we calculate and evaluate quantile forecasts of the daily exchange rate returns of five currencies. The forecasting models that have been used in recent analyses of the predictability of daily realized volatility permit a comparison of the predictive power of different measures of intraday variation and intraday returns in forecasting exchange rate variability. The methods of computing quantile forecasts include making distributional assumptions for future daily returns as well as using the empirical distribution of predicted standardized returns with both rolling and recursive samples. Our main findings are that the Heterogenous Autoregressive model provides more accurate volatility and quantile forecasts for currencies which experience shifts in volatility, such as the Canadian dollar, and that the use of the empirical distribution to calculate quantiles can improve forecasts when there are shifts.     

Financial crisis and stock market efficiency: Empirical evidence from Asian countries

This paper empirically investigates the effects of the 1997 financial crisis on the efficiency of eight Asian stock markets, applying the rolling bicorrelation test statistics for the three sub-periods of pre-crisis, crisis, and post-crisis. On a country-by-country basis, the results demonstrate that the crisis adversely affected the efficiency of most Asian stock markets, with Hong Kong being the hardest hit, followed by the Philippines, Malaysia, Singapore, Thailand and Korea. However, most of these markets recovered in the post-crisis period in terms of improved market efficiency. Given that the evidence of nonlinear serial dependencies indicates equilibrium deviation resulted from external shocks, the present findings of higher inefficiency during the crisis are not surprising as in the chaotic financial environment at that time, investors would overreact not only to local news, but also to news originating in the other markets, especially when the news events were adverse.     

Building capabilities via suppliers' effective management of relationships

This paper is an empirical study identifying the role of a relationship-specific capability of building capabilities through relationships (CBC) when suppliers put efforts into increasing their perceived market effectiveness by managing the effects of relationship quality. The relationship between relationship quality and effectiveness is mediated by CBC. Suppliers in a supply chain form different levels of relationship quality with partners in response to market conditions and industry characteristics. Relationship marketing by suppliers requires a deep understanding of the role of CBC that is developed by a supplier and an effective utilization of CBC to lead an effective relationship to better outcomes. This leads to maximizing of the competitive advantages for suppliers and will help maintain effective relationships.     

Asymptotic and bootstrap prediction regions for vector autoregression

Small sample properties of asymptotic and bootstrap prediction regions for VAR models are evaluated and compared. Monte Carlo simulations reveal that the bootstrap prediction region based on the percentile-t method outperforms its asymptotic and other bootstrap alternatives in small samples. It provides the most accurate assessment of future uncertainty under both normal and non-normal innovations. The use of an asymptotic prediction region may result in a serious under-estimation of future uncertainty when the sample size is small. When the model is near non-stationary, the use of the bootstrap region based on the percentile-t method is recommended, although extreme care should be taken when it is used for medium to long-term forecasting.     

Strategic Choice and Performance in Late Movers: Influence of the Top Management Team's External Ties

This work examines how the strategic choice and performance of late movers are influenced by the top management team's external ties, inside and outside the firm's industry. Using a multiyear sample of firms from the computer industry, we found that intra-industry trade-association ties of top managers led to the adoption of a resource-imitation strategy by late movers while extra-industry importation and professional-association ties led to the adoption of a resource-substitution strategy. We also found that trade association ties had a negative effect on the performance of late movers using resource-substitution, while top managers' service on other firms' boards had a positive influence on the performance of those firms. Our findings not only confirm the importance of the role of fit in strategy and performance, but they also highlight the importance of the management and control of boundary-spanning activities.