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forward discount in predicting exchange rate modifications. The conclusion of the literature review is that the forward discount is a biased predictor and that are two possible explanations for this situation. One cause would be the presence of a time varying risk premium, and the other the failure of agents to make rational expectations (the inability to use all available information in an efficient manner).
The forward discount puzzle (as a predictor of exchange rate modifications) is a very discussed puzzle in the international finance literature, since its importance is quite high. As a result, numerous studies have concentrated on this issue, i.e. On the causes on the bias. Some authors (Fama, 1984), believe that this problem is traceable to the existence of a time-varying risk premium. Others connect it to learning effect (Lewis, 1989) or irrationality (Bilson, 1981) the "peso problem" (Krasker, 1980),
The "peso problem term" was introduced into the literature by a researcher who concentrated his attention on the predictibility of the Mexican Peso's evolution, which was traded on large scale on the forward market against thE U.S. Dollar in the 1970's, although it was on a fixed exchange rate. The cause of that situation was that a devaluation was expected - and it indeed took place in 1976.
Testing the rational expectation hypothesis in realtion to the estimation of the Mexican Peso in this time frame is biased beyond doubt. Therefore, applying the standard assumption of normality of the distribution, currently used in statistic tests, will not yeald any valid results. This statistical defect may also be observed in other circumstances, such as the probability (even quite small) of a major modification of the exchange rate in the studied period, a speculative bubble or an important change in fundamentals, especially iF the sample size is not sufficient in order to correct such faults (by applying the central limit theorem).
The first opinion, which attributes the bias to a foreign exchange risk premium, starts from the assumption that agents make rational forecasts. Analyzing the available literature in this area, Engel (1996) arrived to the conclusion that the hypothesis according to which there is no unbiasedness to be attributed to the ability of prediction of the forward rate is false and that the model of the risk premiums haven't been able to reasonably explain the high degree of failure of this solution.
The researchers who have based their theories on the rationality of agents' expectations have empirically tested the concept by using survey data regarding expected exchange rate modifications from various sources. The results are not going in the same direction. The regression technique shows that the degree of rationality among these expectations is not 100%. A more accurate result was obtained by using a cointegration test, which proved that rationality exists for short-term forecasts (one-week, two-week, four-week) but any forecast for a period exceeding this horizon is biased, as a literature review conducted by McDonald in 2000 has evidenced.
Miah, Hassan and Alam have conducted in 2004 a research project on the forward discount puzzle, by starting from the idea that "A direct test of rational expectation using survey data, which is risk premium free, allow us to see whether there is a bias in the expectation formation process by agents. If expectations are found to be rational, then the forward discount bias could be due to the presence of risk premium."
The rationality of survey data in estimating future exchange rate modification is the object of the current study. I have used the conclusions which the literature provides and the collection of data and methodology available to Miah, Hassan and Alam (2004) to check for myself whether their conclusions are consistent with the actual results of the analysis and with the general trend set by the literature.
3. PROBLEM IDENTIFICATION
The authors admit that there has been a myriad of studies and tests of the rationality of survey data in different periods, using various econometric methods and data sources. The conclusion they draw is that the survey data does not appear to be rational, but the results are not always conclusive because of the limited time periods in which the tests were made, which exposed them to the risk of small sample bias. Time series studies are also an inappropriate working material for traditional econometric methods, which has provided extra criticism.
Another factor that makes its influence felt in this field is that of government intervention in the foreign exchange market. Although this intervention could prove ineffective, should the agents make rational forecasts (Dominguez and Frankel,1993), this is not often the case. Normally, studies of the issue do not use more than five years of data, usually after 1991. Miah, Hassan and Alam (2004) have used a monthly data survey stretched on twelve years, in order to observe the modifications of forecasters perfomance over time. Their methods include unit root tests and the restricted cointegration test, and their purpose is to help practitioners improve their exchange rate estimation techniques.
Reconducting the tests and analyzing the conclusions should provide a clearer picture of the accuracy of estimation of exchange rate modification, in relation to the rationality of the collected survey data. Starting from the hypothesis, the series of tests should either confirm or contradict the initial statement, therefore facilitating the arrival to a valid scientific conclusion.
The hypothesis of the test is that the collected survey data prove rational. The Rational Expectation Hypothesis refers to the fact that, should an agent use all available information when forming an expectation on future exchange rate modifications, the estimated rate will be an unbiased predictor of the actual spot rate. The equations used in this case show that any difference between the actual rate and the expected rate will be nothing more than a random error (a situation commonly referred to by the literature as the "the test of unbiasedness."
Another test, referred to as the test of orthogonality, may also be applied, although not making the object of this study. Rationality of expectations leads to uncorrelation of the forecast errors with the variables in an information set (e.g. exchange and forward rates, money supply and others.
6. METHODOLOGY have used the data collected by Miah, Hassan and Alam (2004) and remade their calculations.Analysis and testing of the survey data collected required, in order for the date to be rational, that the residual be a white noise process. The serial corellation is the residual series was tested using Q-statistics. The conclusion to which the researchers could have arrived at depended on whether the residual series showed any trace of serial correlation or not. No evidence of such a fact pointer to the fact the rational expectation hypothesis was correct.
The studied forecast periods were finer than the forecast used, which lead to the conclusion that the residual series had to follow a moving average process. Although the forecast may have been rational, a W-test would have showed a serial correlation. The actual residuals of the 3-month, 6-month and 12-month forecast were estimated and then the Q-test was applied on the residual series obtained from this estimation. The residuals series are stationary (cointegrated). The lag lentghts chosem for the Q-test were 4, 8, 12, 24 and 36 and signify the correlation after both short and long time periods.
The data used by the study was collected from the Financial Times' Currency Forecaster for the German Mark / U.S. Dollar, GB Pound / U.S. Dollar and Japanese Yen / U.S. Dollar exchange rates, during the February 1988 - May 1999 period. The studied survey horizons were one, three, six and twelve months.
The Financial Times' Currency Forecaster is a specialized in forecasting the evolution of excahnge rate modfication and which publishes exchange rates estimations for the monetary units of more than 45 countries, based on data available from February 1988. The data sample is collected from a group of thirty multinational companies and fifteen forecasting service providers. The time horizons for which forecasts are performed are one, three, six and twelve months, all which were used in the study.
This particular study used various statistical methods in order to determine the rationality of the data. For the first exchange rate - German Mark / U.S. Dollar, the ADF and DFGLS tests weren't able to reject the null for the spot rate and one-month ahead forecasts at the 10% level. However, heterogenous results have been obtained for the other series.
Several tests were applied on the data: the Augumented Dickey Fuller test; in this case, the statistics do not have the normal t distribution. Fuller's study from 1986 and the joint study of Fuller and Dickey from 1981 tabulated the critical values using the test statistics. The test may use a either a constant or a constant and a trend. Miah et all. (2004) used both versions.
There is also a controversy regarding the appropriate lag for this test. The choice of leg length was…[continue]
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