Forecasting exchange rates with linear and nonlinear models

In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore, the parameters are chosen according to what the researcher considers to be the best. Such an approach, however,implies that the risk of making bad decisions is extremely high, which could explain why in many studies, neural network models do not consistently perform better than their time series counterparts. In this paper, through extensive experimentation, the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of Forecasting exchange rates with linear and nonlinear models 415 performing well. The results show that in general, neural network models perform better than the traditionally used time series models in forecasting exchange rates.

Monetary models of exchange rates and sweep programs

Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this article, we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweep-adjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates, but the success of such models depends on the stability of money demand functions and the specifications of the models.

Volatility changes in drachma exchange rates

In January 2001 Greece joined the eurozone. The aim of this article is to examine whether an intention to join the eurozone had any impact on exchange rate volatility. We apply the Iterated Cumulative Sum of Squares (ICSS) algorithm of Inclan and Tiao (1994) to a set of Greek drachma exchange rate changes. We find evidence to suggest that the unconditional volatility of the drachma exchange rate against the dollar, British pound, yen, German mark and ECU/Euro was nonstationary, exhibiting a large number of volatility changes prior to European Monetary Union (EMU) membership. We then use a news archive service to identify the events that might have caused exchange rate volatility to shift. We find that devaluation of the drachma increased exchange rate volatility but ERM membership and a commitment to joining the eurozone led to lower volatility. Our findings therefore suggest that a strong commitment to join the eurozone may be sufficient to reduce some exchange rate volatility which has implications for countries intending to join the eurozone in the future.

Model specification and forecasting foreign exchange rates with vector autoregressions

This study examines the forecasting accuracy of alternative vector autoregressive models each in a seven-variable system that comprises in turn of daily, weekly and monthly foreign exchange (FX) spot rates. The vector autoregressions (VARs) are in non-stationary, stationary and error-correction forms and are estimated using OLS. The imposition of Bayesian priors in the OLS estimations also allowed us to obtain another set of results. We find that there is some tendency for the Bayesian estimation method to generate superior forecast measures relatively to the OLS method. This result holds whether or not the data sets contain outliers. Also, the best forecasts under the non-stationary specification outperformed those of the stationary and error-correction specifications, particularly at long forecast horizons, while the best forecasts under the stationary and error-correction specifications are generally similar. The findings for the OLS forecasts are consistent with recent simulation results. The predictive ability of the VARs is very weak.

Trade balance and real exchange rate:new evidence from Mauritius-UK trade

In this study we investigate whether there exists a relationship between the exchange rate and the trade balance using bilateral data for the Mauritius/UK trade. We also investigate whether following depreciation or a devaluation the trade balance initially worsens due to contractual agreements and subsequently improves when new contracts for international trade are signed. Using a variety of econometric techniques we are able to establish that there exists a long-run relationship between the trade balance and the real exchange rate. The existence of such a relationship signifies that the authorities would be able to use the exchange rate to steer the trade balance. We also find following a depreciation or devaluation the trade balance initially worsens due to contractual agreements but the trade balance subsequently improves when new contracts are signed. This signifies that if the authorities want to devalue their currency to improve the trade balance, the desired effect does not occur immediately but it occurs with a lag, in this particular case after approximately a year.

Forecasting exchange rates with linear and nonlinear models

In this paper the exchange rate forecasting performance of neural network models are evaluated against random walk and a range of time series models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore the parameters are chosen according to what the researcher considers to be the best. Such an approach, however, implies that the risk of making bad decisions is extremely high which could explain why in many studies neural network models do not consistently perform better than their time series counterparts. In this paper through extensive experimentation the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of performing well. Our results show that in general neural network models perform better than traditionally used time series models in forecasting exchange rates.

Exchange rate economic exposure and hedging:the significance of currency options

This thesis focuses on the theoretical examination of the exchange rate economic (operating) exposure within the context of the theory of the firm, and proposes some hedging solutions using currency options. The examination of economic exposure is based on such parameters as firms' objectives, industry structure and production cost efficiency. In particular, it examines an hypothetical exporting firm with costs in domestic currency, which faces competition from foreign firms in overseas markets and has a market share expansion objective. Within this framework, the hypothesis is established that economic exposure, portrayed in a diagram connecting export prices and real exchange rates, is asymmetric (i.e. the negative effects depreciation are higher than the positive effects of a currency depreciation). In this case, export business can be seen as a real option, given by exporting firms to overseas customer. Different scenarios about the asymmetry hypothesis can be derived for different assumptions about the determinants of economic exposure. Having established the asymmetry hypothesis, the hedging against this exposure is analysed. The hypothesis is established, that a currency call option should be used in hedging against asymmetric economic exposure. Further, some advanced currency options stategies are discussed, and their use in hedging several scenarios of exposure is indicated, establishing the hypothesis that, the optimal options strategy is a function of the determinants of exposure. Some extensions on the theoretical analysis are examined. These include the hedging of multicurrency exposure using options, and the exposure of a purely domestic firm facing import competition. The empirical work addresses two issues: the empirical validity of the asymmetry hypothesis and the examination of the hedging effectiveness of currency options.

Trade balance and real exchange rate:new evidence from Mauritius-UK trade

Two main questions are addressed here: is there a long-run relationship between trade balance and real exchange rate for the bilateral trade between Mauritius and UK? Does a J-curve exist for this bilateral trade? Our findings suggest that the real exchange rate is cointegrated with the trade balance and we find evidence of a J-curve effect. We also find bidirectional causality between the trade balance and the real exchange rate in the long-run. The real exchange rate also causes the trade balance in the short-run. In an out-of-sample forecasting experiment, we also find that real exchange rate contains useful information that can explain future movements in the trade balance.

Monetary models of exchange rates and sweep programs

Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this paper we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweepadjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates but the success of such models depends on the stability of money demand functions and the specifications of the models.

Leading edge forecasting techniques for exchange rate prediction

This paper describes how modern machine learning techniques can be used in conjunction with statistical methods to forecast short term movements in exchange rates, producing models suitable for use in trading. It compares the results achieved by two different techniques, and shows how they can be used in a complementary fashion. The paper draws on experience of both inter- and intra-day forecasting taken from earlier studies conducted by Logica and Chemical Bank Quantitative Research and Trading (QRT) group's experience in developing trading models.

Exchange rate exposure : do size and foreign operations matter?

Purpose – The purpose of this paper is to examine the effect of firm size and foreign operations on the exchange rate exposure of UK non-financial companies from January 1981 to December 2001. Design/methodology/approach – The impact of the unexpected changes in exchange rates on firms’ stock returns is examined. In addition, the movements in bilateral, equally weighted (EQW) and trade-weighted and exchange rate indices are considered. The sample is classified according to firm size and the extent of firms’ foreign operations. In addition, structural changes on the relationship between exchange rate changes and individual firms’ stock returns are examined over three sub-periods: before joining the exchange rate mechanism (pre-ERM), during joining the ERM (in-ERM), and after departure from the ERM (post-ERM). Findings – The findings indicate that a higher percentage of UK firms are exposed to contemporaneous exchange rate changes than those reported in previous studies. UK firms’ stock returns are more affected by changes in the EQW, and US$ European currency unit exchange rate, and respond less significantly to the basket of 20 countries’ currencies relative to the UK pound exchange rate. It is found that exchange rate exposure has a more significant impact on stock returns of the large firms compared with the small and medium-sized companies. The evidence is consistent across all specifications using different exchange rate. The results provide evidence that the proportion of significant foreign exchange rate exposure is higher for firms which generate a higher percentage of revenues from abroad. The sensitivities of firms’ stock returns to exchange rate fluctuations are most evident in the pre-ERM and post-ERM periods. Practical implications – This study provides important implications for public policymakers, financial managers and investors on how common stock returns of various sectors react to exchange rate fluctuations. Originality/value – The empirical evidence supports the view that UK firms’ stock returns are affected by foreign exchange rate exposure.

The exchange rate exposure of UK non-financial companies

Purpose – The purpose of this paper is to investigate the exchange rate exposure of UK nonfinancial companies from January 1981 to December 2001. Design/methodology/approach – The study employs different exchange rate measures and adopts an equally weighted exchange rate. The analyses are conducted at the firm level. All analyses are conducted by regressing the firm’s exchange rate exposure coefficients on its size, foreign activity variables and financial hedging proxies over the whole sample period. Findings – The findings show that a higher percentage of UK non-financial companies are exposed to exchange rate changes than those reported in previous studies. Generally, the results provide a stronger support for the suggested equally weighted rate as an economic variable, which affects firms’ stock returns. The results also show a high proportion of positive exposure coefficients among firms with significant exchange rate exposure, indicating a higher proportion of firms benefiting from an appreciation of the pound. Finally, the results also indicate evidence that firms’ foreign operations and hedging variables affect their sensitivity to exchange rate exposure. Practical implications – This study provides important implications for public policymakers who wish to understand links between policies that affect exchange rates and relative wealth effects. Originality/value – The empirical results of this study should help investors to examine how common stock returns react to exchange rate fluctuations when making financial decisions, and prove useful for financial managers when measuring exposure to foreign exchange rate changes.

Post-Bretton Woods evidence on PPP under different exchange rate regimes

This article investigates the behaviour of exchange rates across different regimes for a post-Bretton Woods period. The exchange rate regime classification is based on the classification of Frankel et al. (2004) who condensed the 10 categories of exchange rate regimes reported by the International Monetary Fund (IMF) into three categories. Panel unitroot tests and panel cointegration are used to examine the Purchasing Power Parity (PPP) hypothesis. The latter test is used to check for both the weak and strong forms of PPP. The panel unit-root tests show no evidence of PPP and suggest there is no difference in the behaviour of exchange rates across different regimes. However, failure to detect PPP across any of the regimes could be due to structural breaks. This assumption is reinforced by the results of cointegration tests, which suggest that there exists at least a weak form of PPP for the different regimes. The evidence for strong PPP decreases as the exchange rate regime moves away from a flexible exchange rate regime.

Exchange rate exposure:do size and foreign operations matter?

Purpose – The purpose of this paper is to examine the effect of firm size and foreign operations on the exchange rate exposure of UK non-financial companies from January 1981 to December 2001. Design/methodology/approach – The impact of the unexpected changes in exchange rates on firms’ stock returns is examined. In addition, the movements in bilateral, equally weighted (EQW) and trade-weighted and exchange rate indices are considered. The sample is classified according to firm size and the extent of firms’ foreign operations. In addition, structural changes on the relationship between exchange rate changes and individual firms’ stock returns are examined over three sub-periods: before joining the exchange rate mechanism (pre-ERM), during joining the ERM (in-ERM), and after departure from the ERM (post-ERM). Findings – The findings indicate that a higher percentage of UK firms are exposed to contemporaneous exchange rate changes than those reported in previous studies. UK firms’ stock returns are more affected by changes in the EQW, and US$ European currency unit exchange rate, and respond less significantly to the basket of 20 countries’ currencies relative to the UK pound exchange rate. It is found that exchange rate exposure has a more significant impact on stock returns of the large firms compared with the small and medium-sized companies. The evidence is consistent across all specifications using different exchange rate. The results provide evidence that the proportion of significant foreign exchange rate exposure is higher for firms which generate a higher percentage of revenues from abroad. The sensitivities of firms’ stock returns to exchange rate fluctuations are most evident in the pre-ERM and post-ERM periods. Practical implications – This study provides important implications for public policymakers, financial managers and investors on how common stock returns of various sectors react to exchange rate fluctuations. Originality/value – The empirical evidence supports the view that UK firms’ stock returns are affected by foreign exchange rate exposure.