tailieunhanh - Predictability of foreign exchange rates with the AR(1) mode

Many authors have investigated the possibility of predictability in asset returns, but very little supportive evidence has so far been found in exchange rate returns. This empirical study uses the econometric model ARIMA (1,0,0) to study three different foreign exchange rates, namely the euro and the dollar, the euro and the Hungarian forint and the euro and the Korean won. It is worth mentioning that ARIMA (1,0,0) model is the same as the autoregressive model AR(1), as both of them are made up of one autoregressive parameter and no moving average parameters. The results show that it is not possible to explain and predict all three foreign exchange rates using the autoregressive model. Specifically, the technical rule on transactions ARIMA(1,0,0) is not effective in the case of euro vs dollar but it is effective in the case of euro vs the Hungarian forint and euro v-s the Korean won. Fairly accurate predictions can be made regarding the last two foreign exchange relationships. | Journal of Applied Finance Banking vol. 7 no. 4 2017 39-58 ISSN 1792-6580 print version 1792-6599 online Scienpress Ltd 2017 Predictability of Foreign Exchange Rates with the AR 1 Model Andreas Hadjixenophontos1 and Christos Christodoulou-Volos2 Abstract Many authors have investigated the possibility of predictability in asset returns but very little supportive evidence has so far been found in exchange rate returns. This empirical study uses the econometric model ARIMA 1 0 0 to study three different foreign exchange rates namely the euro and the dollar the euro and the Hungarian forint and the euro and the Korean won. It is worth mentioning that ARIMA 1 0 0 model is the same as the autoregressive model AR 1 as both of them are made up of one autoregressive parameter and no moving average parameters. The results show that it is not possible to explain and predict all three foreign exchange rates using the autoregressive model. Specifically the technical rule on transactions ARIMA 1 0 0 is not effective in the case of euro vs dollar but it is effective in the case of euro vs the Hungarian forint and euro v-s the Korean won. Fairly accurate predictions can be made regarding the last two foreign exchange relationships. JEL classification numbers F31 F37 G14 Keywords Foreign exchange market Exchange Rate Technical Trading Speculation forecasting 1 Introduction During recent years volatility predictions of time series like for example on foreign exchange have been the subject of extensive discussions and research. Volatility is a very important aspect of financial markets as it reflects uncertainty and therefore currency or investment portfolio risk. The greater the volatility the greater the currency exchange risk between a pair of currencies. Investors fund managers and investment analysts use different volatility models in order to predict maximum returns on foreign currency exchange 5 . Currency exchanges are largely influenced by interrelationships of economic .

• Ngân hàng - Tín dụng
• Foreign exchange market
• Exchange rate
• Technical trading
• The AR mode
• Foreign exchange rates