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This chapter investigates the determinants of the volatility of spread in the over-the-counter foreign exchange market and examines whether the relationships differ in the crisis periods. We compute the measures for the volatility of liquidity by using bid-ask spread data sampled at a high frequency of five minutes. By examining 11 currencies over a 13-year sample period, we utilize a balanced dynamic panel regression to investigate whether the risk associated with the currencies quoted or trading activity affects the variability of liquidity provision in the FX market and examine whether the crisis periods have any effect. We find that both the level of spread and volatility of spread increases during the crisis periods for the currencies of emerging countries. In addition, we find increases in risks associated with the currencies proxied by realized volatility during the crisis periods. We also show risks associated with the currency are the major determinants of the variability of liquidity and that these relationships strengthen during periods of uncertainty. First, we develop measures to capture the variability of liquidity. Our measures to capture the variability of liquidity are non-parametric and model-free variable. Second, we contribute to the debate of whether variability of liquidity is adverse to market participants by examining what drives the variability of liquidity. Finally, we analyze seven crisis periods, allowing us to document the effect of the crises on determinants of variability of liquidity over time.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

We address an interesting case – the predictability of excess US asset returns from macroeconomic factors within a flexible regime-switching VAR framework – in which the presence of regimes may lead to superior forecasting performance from forecast combinations. After documenting that forecast combinations provide gains in predictive accuracy and that these gains are statistically significant, we show that forecast combinations may substantially improve portfolio selection. We find that the best-performing forecast combinations are those that either avoid estimating the pooling weights or that minimize the need for estimation. In practice, we report that the best-performing combination schemes are based on the principle of relative past forecasting performance. The economic gains from combining forecasts in portfolio management applications appear to be large, stable over time, and robust to the introduction of realistic transaction costs.

In view of a disruptive environment, the authors consider theories that explain left-skewed performance outcomes and inverse risk–return relationships where some rationales imply causal dependencies with slightly differing outcomes while others refer to spurious artifacts. These literatures are briefly outlined and dynamic response capabilities introduced as an alternative perspective expressed as strategic responsiveness where commonly observed performance outcomes derive from heterogeneous response capabilities among firms that compete in dynamic environments. Financial performance outcomes are analyzed empirically based on a comprehensive corporate dataset where computational simulations of adaptive strategy making among firms generate comparable outcomes from a simple strategic responsiveness model. The findings demonstrate how diverse adaptive strategy-making processes can generate a substantial part, if not all, of the commonly observed artifacts of firm financial performance. The implications of these results are discussed pointing to propitious approaches of analyzing the impact of dynamic adaptive strategies.

This paper analyzes the roles of idiosyncratic risk and firm-level conditional skewness in determining cross-sectional returns. It is shown that the traditional EGARCH estimates of conditional idiosyncratic volatility may bring significant finite sample estimation bias in the presence of non-Gaussianity. We propose a new estimator that has more robust sampling performance than the EGARCH MLE in the presence of heavy-tail or skewed innovations. Our cross-sectional portfolio analysis demonstrates that the idiosyncratic volatility puzzle documented by Ang, Hodrick, Xiang, and Zhang (2006) exists intertemporally. We conduct further analysis to solve the puzzle. We show that two factors idiosyncratic variance and individual conditional skewness play important roles in determining cross-sectional returns. A new concept, the “expected windfall,” is introduced as an alternate measure of conditional return skewness. After controlling for these two additional factors, we solve the major piece of this puzzle: Our cross-sectional regression tests identify a positive relationship between conditional idiosyncratic volatility and expected returns for over 99% of the total market capitalization of the NYSE, NASDAQ, and AMEX stock exchanges.

Without short-sales constraints, mean-variance (MV) and power-utility portfolios generated from historical data are often characterized by extreme expected returns, standard deviations, and weights. The result is usually attributed to estimation error. I argue that modeling error, that is, modeling the portfolio problem with just a budget constraint, plays a more fundamental role in determining the extreme solutions and that a more complete analysis of MV problems should include realistic constraints, estimates of the means based on predictive variables, and specific values of investors’ risk tolerances. Empirical evidence shows that investors who utilize MV analysis without imposing short-sales constraints, without employing estimates of the means based on predictive variables, and without specifying their risk tolerance miss out on remarkably remunerative investment opportunities.

The paper uses 101 years of Chilean and international financial assets returns to investigate mean-variance optimal portfolio allocations. The key conclusion is that the share of international unhedged investments is substantial even in minimum risk portfolios (20%), unless the period 1980–2002 is assumed to be drawn from a different distribution and previous history is disregarded. In addition to that, the paper finds that mean-variance optimal investors would have generated substantial demand for an asset replicating the return profile of an efficient pay-as-you-go pension scheme. Labour income and departures from log-normality of returns might, however, affect the latter conclusion.

We investigate global competitors’ reaction to the Citicorp–Travelers mega merger announcement and find that global competitors, especially banks in Europe and the US, reacted positively to the Citicorp and Travelers’ merger announcement. The uncertainties created by the investigations into the merger proposal had significant impact on the competitors’ stock price. The announcement that the merger had been consummated also elicited a significantly positive reaction from the rivals following the resolution of uncertainties emanating from the regulatory challenges. The positive reaction by competitors suggests that the merger was a wealth-creating event for the large firms in the financial services industry. The expected benefits outweighed any competitive effects resulting from the merger. The competitors’ reaction was, however, not homogenous. Our cross-sectional analysis shows that the abnormal returns earned by the competitors were higher the larger the competitor. In addition, the abnormal returns were greater for the US rivals. That the global competitors reacted positively to the Citicorp–Travelers mega merger announcement is consistent with our assertion that the merger had ramifications that go beyond regulatory concerns in the US.

There are few studies of take over effects in emerging stock markets and of whether such events result in value-increasing or value-decreasing effects for the successful targets and bidders. This study analyses the impact of successful takeovers on the Stock Exchange of Thailand (SET). Both target and bidding firms’ performances during a period of 12 months before and after the takeover are investigated. Abnormal returns are measured using an event study approach; applying two models and three parametric test statistics. The results suggest that Thai takeover effects are wealth-creating for both offeree and offeror shareholders.

This study examines share price reaction to the enrollment by companies in the Children’s Food and Beverage Advertising Initiative. We find that, on average, in the month of enrollment, shareholders of companies that join the CFBAI experience abnormal return of −3% and so do the shareholders of the immediate competitors that do not join the initiative. However, over the subsequent five years, while the shareholders of companies enrolled in the initiative experience an average abnormal return of +16.6%, that of non-enrolled competitors experience a further abnormal return of −34%. The abnormal returns for the two groups (at the time of enrollment and over the subsequent five years) are uncorrelated and so benefitting at the expense of competitors does not appear to be the motive for enrolling in the CFBAI. The study also provides comparison of number of employees and other important financial ratios before and after enrollment in the CFBAI for the two groups.