The exchange rate is one of the most vital components in any economic and investment decision. With the increase in globalisation, there is a concomitant increase in the exchange rate risk in any global investment decision. This Ph.D. thesis examines asset pricing in the foreign exchange market in various dimensions, introduces new techniques for performance measurement and information flow, and attempts to explain the carry trade in the foreign exchange market. The economic significance of empirical exchange rates models in a portfolio-based framework was examined, using a thirty-year time series of five exchange rates. The forecast performances were evaluated in mean-variance and performance index (indices of acceptability) to compare the fundamental exchange rate models with a benchmark random walk model. The parameters were computed using advanced computational finance and econometric techniques. The performance measurements obtained from mean-variance by various models were compared using the Sharpe ratio. It was concluded that the structural model, although unable to beat the random walk model, did not perform worse than the forecasts obtained from the benchmark model. The results from the indices of acceptability evaluation indicate that one-month ahead forecasts obtained from the monetary model of the exchange rate performed better than the benchmark model.Furthermore, the information flow in the foreign exchange market was examined by evaluating the relationship between volatility and the customers' trading activity. An attempt was made to explain the relationship between volatility and customer order flows in a portfolio-based framework with unique aggregate and disaggregate customer order-flow data from the Union Bank of Switzerland (UBS). This was the largest private dataset used to-date in a study of the foreign exchange market. The relationship was found to be robust; that is, the order flow is one of the main sources for transmitting private information to the foreign exchange market. This relationship holds across all the currencies and in various volatility estimates. This study is the first in the foreign exchange market in the aforementioned setup, and robustly elucidates the cited relationship in the foreign exchange market. The results give significant support to information being asymmetric across classes of customers and that private information is transmitted to the foreign exchange market by the trading behaviour of informed customers. Moreover, the volatility patterns in the foreign exchange market are significantly and substantially affected by the customer order flows. The size of the trade impact on volatility in a portfolio-based approach was also examined and it was found that the large sales are more influential trades on volatility in the foreign exchange market. In addition, to study the subsequent volatility, there was an examination of two existing hypotheses; i.e., the liquidity-driven-trade-hypothesis (positive subsequent relationship), and the information-driven-trade-hypothesis (negative subsequent relationship.) Both phenomena were found to exist, depending on the economic condition of the market.Finally, an explanation was given for the existence and identification of the carry trade in the foreign exchange market. When an investor borrows from a low interest-rate currency and invests in a higher interest-rate currency, zero-investment portfolio, this trading strategy is called carry trade strategy. Again, a novel data set provided by the UBS was examined to establish a relationship between the ordering patterns of informed customers and the carry trade. The forward discount bias and the carry trade were studied using theories of microstructure finance and the consumption-based asset-pricing model in a portfolio-based framework. The microstructure approach is the standard model of Evans and Lyons (2002). It was found that the order flow significantly explained the excess return in the carry trade, implying that informed customers knew about the carry trade opportunities in the market and reorganised their portfolios in order to realise these gains. Volatility and customer order flows were also examined, using a GMM approach, as a global innovation factor, and it was found that both variables significantly explained the cross-section of carry returns in the foreign exchange market.
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