We investigate the relation between volatility and volume in 22 developed markets and 27 emerging markets. Compared to developed markets, emerging markets show a greater response to large information shocks and exhibit greater sensitivity to unexpected volume. We find a negative relation between expected volume and volatility in several emerging markets, which can be attributed to the relative inefficiency in those markets. Previous research reports that the persistence in volatility is not eliminated when lagged or contemporaneous trading volume is considered. Our findings show that, when volume is decomposed into expected and unexpected components, volatility persistence decreases. Copyright 2007, The Eastern Finance Association.

Multi-criteria decision-making is an increasingly accepted tool for decision-making in management. In this work, we highlight the application of a novel multi-objective evolutionary algorithm, NSGA-II, to the risk-return tradeoff for a bank-loan portfolio manager. The manager of a bank operating in a competitive environment faces the standard goal of maximizing shareholder wealth. Specifically, this attempts to maximize the net worth of the bank, which in turn involves maximizing the net interest margin of the bank (among other factors, such as noninterest income). At the same time, there are significant regulatory constraints placed on the bank, such as the maintenance of adequate capital, interest-rate risk exposure, etc. The genetic algorithm-based technique used here obtains an approximation to the set of Pareto-optimal solutions which increases the decision flexibility available to the bank manager, and provides a visualization tool for one of the trade-offs involved. The algorithm is also computationally efficient and is contrasted with a traditional multi-objective function -the epsilonconstraint method.

We respecify the uncovered interest rate parity (UIP) conditions by inverting the market price of the risk (Sharpe ratio) formula. Our empirical model provides new insight indicating that violations to the UIP stem from the existence of a risk premium in the exchange rates and from observed market return differentials being a noisy statistic of the markets’ expected return differentials in our respecified model. Using an integrated macro‐micro structure framework for expected market return differentials improves our model fit and the validity of UIP.

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