This study uses survey data of fund managers' views on prospects for international equity markets to shed light on why investment portfolios are significantly biased towards domestic equities. We find that fund managers from the United States, the United Kingdom, continental Europe, and Japan show a significant relative optimism towards their home equity market. Where institutional factors have largely failed to explain the puzzle, our evidence lends support to behavioral explanations of the bias.

This paper illustrates regression and Kalman filtering methods for estimating the time-varying term structure of volatility expectations revealed by options prices. Short- and long-term expectations are estimated for four currencies using daily PHLX options prices from 1985 to 1989. Throughout this period, there were important differences between shortand long-term expectations. The slope of the term structure changed frequently and there were significant variations in long-term volatility expectations. The expectation estimates can be used to value OTC options, to improve hedging strategies, and to test the hypothesis that the options market overreacts.

There are important organizational and behavioral differences between firms in emerging markets and those in developed markets. We propose a top-down approach to understand how key institutional forces shape the structures and policies of firms in emerging markets. We review a selective set of prior studies as well as papers included in this Special Issue in identifying government quality, state ownership, and financial development as critical institutional forces that shape the financing and governance of firms in emerging markets. We suggest that future research should pay attention to several important but unanswered topics related to informal enforcement, government incentives, family firms, and network organizations.

We compare forecasts of the realized volatility of the pound, mark and yen exchange rates against the dollar, calculated from intraday rates, over horizons ranging from one day to three months. Our forecasts are obtained from a short memory ARMA model, a long memory ARFIMA model, a GARCH model and option implied volatilities. We find intraday rates provide the most accurate forecasts for the one-day and one-week forecast horizons while implied volatilities are at least as accurate as the historical forecasts for the one-month and three-month horizons. The superior accuracy of the historical forecasts, relative to implied volatilities, comes from the use of high frequency returns, and not from a long memory specification. We find significant incremental information in historical forecasts, beyond the implied volatility information, for forecast horizons up to one week.

Risk-neutral and real-world densities are derived from option prices and risk assumptions, and are compared with historical densities obtained from time series. Two parametric risk-transformations are used to convert risk-neutral densities into real-world densities. Both transformations are estimated by maximizing the likelihood of observed index levels, for two parametric density families. Results for the FTSE-100 index show that parametric densities derived from option prices have more explanatory power than historical densities and higher likelihoods than densities estimated by spline methods. A combination of parametric real-world and historical densities provides the preferred predictive densities.