Regime Switching Model: Foreign Exchange Rate

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Foreign exchange is significant in many different parts of the economy. It is mainly used in international trade and debt servicing. It is also important in the insurance industry because there are plans, such as multi-currency plans, which are designed with benefits and premiums define in terms of different currencies. Also, investment banks and multinational companies loan and/or invest part of their capital in terms of the foreign currency (BSP, 2008). Foreign exchange rate is complex and hence it is heavily studied in international macroeconomics.

Foreign exchange rate may also be defined as the relationship between the term structures of interest rates of several national currencies. This relationship changes continuously because of
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Moreover, sudden changes are also a prevalent feature of financial data, and regime-switching models are quite amenable to theoretical calculations showing abrupt changes in fundamentals which should show up in asset prices (Ang and Bekaert, 2003; Garcia, Luger, and Renault, 2003; Dai, Singleton, and Wei, 2003, as cited in Hamilton, 2005).

II. Statement of the Problem

This study aims to develop a regime-switching model that will capture the general trend and volatility of the European Dollar currency with respect to Philippine Peso.

III. Objectives of the Study

The objectives of this study are:
1. to develop a Markov regime-switching model for Peso/Dollar exchange rates, given a set of statistical
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Because of the accuracy and efficiency of these models in analyzing financial time series data, it is applied commonly in stock returns, as well as to other financial derivatives. It is also used in examining the trends of foreign currency rates. In 2004, Kóbor and Székely assessed the feasibility of Euro adoption of four central EU accession countries by examining their foreign exchange market volatilities using regime-switching models. Ismail and Isa (2006) also derived various regime-switching models and fitted in the Malaysian, Thai, and Singaporean exchange rates. Both papers had established that Markov regime-switching models provide better in-sample fitting than linear models and single regime models, and it can detect structural breaks and mean reversion in the

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