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Forecasting is central to economic and financial decision-making. Government institutions and\ud agents in the private sector often base their decisions on forecasts of financial and economic variables.\ud Forecasting has therefore been a primary concern for practitioners and financial econometricians\ud alike, and the relevant literature has witnessed a renaissance in recent years. This\ud thesis contributes to this literature by investigating three topical issues related to financial and\ud economic forecasting.\ud The first chapter finds its rationale in the large literature suggesting that standard exchange\ud rate models cannot outperform a random walk forecast and that the forward rate is not an optimal\ud predictor of the spot rate. However, there is some evidence that the term structure of forward\ud premia contains valuable information for forecasting future spot exchange rates and that exchange\ud rate dynamics display nonlinearities. This chapter proposes a term-structure forecasting model\ud of exchange rates based on a regime-switching vector equilibrium correction model which is novel\ud in this context. Our model significantly outperforms both a random walk and, to a lesser extent,\ud a linear term-structure vector equilibrium correction model for four major dollar exchange rates\ud across a range of horizons.\ud The second chapter proposes a vector equilibrium correction model of stock returns that\ud exploits the information in the futures market, while also allowing for regime-switching behavior\ud and international spillovers across stock market indices. Using data for three major stock market\ud indices since 1989, we find that: (i) in sample, the model outperforms several alternative models\ud on the basis of standard statistical criteria; (ii) in out-of-sample forecasting, the model does not\ud produce significant gains in terms of point forecasts relative to more parsimonious alternative\ud specifications, but it does so both in terms of market timing ability and in density forecasting\ud performance. The importance of these gains is illustrated with a simple application to a risk\ud management problem.\ud The third chapter re-examines a major puzzle in international finance that is the inability of\ud exchange rate models based on monetary fundamentals to produce better out-of-sample forecasts\ud of the nominal exchange rate than a naive random walk. While prior research has generally\ud evaluated exchange rate forecasts using conventional statistical measures of forecast accuracy,\ud this chapter investigates whether there is any economic value to the predictive power of monetary\ud fundamentals for the exchange rate. We estimate, using a framework that allows for parameter\ud uncertainty, the economic and utility gains to an investor who manages her portfolio based on\ud exchange rate forecasts from a monetary fundamentals model. In contrast to much previous\ud research, we find that the economic value of the exchange rate forecasts implied by monetary\ud fundamentals can be substantially greater than the economic value of forecasts obtained using a\ud random walk across a range of horizons.\ud In sum this thesis adds to the relevant literature on forecasting financial variables by providing\ud insights and evidence to researchers and indicating potential avenues for futures research

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