Paul A. Weller

Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach

Using genetic programming techniques to find technical trading rules, we find strong evidence of economically significant out-of-sample excess returns to those rules for each of six exchange rates over the period 1981–1995. Further, when the dollar/Deutsche mark rules are allowed to determine trades in the other markets, there is significant improvement in performance in all cases, except for the Deutsche mark/yen. Betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk. Bootstrapping results on the dollar/Deutsche mark indicate that the trading rules detect patterns in the data that are not captured by standard statistical models.

The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market

We analyze the intertemporal stability of excess returns to technical trading rules in the foreign exchange market by conducting true, out-of-sample tests on previously studied rules. The excess returns of the 1970s and 1980s were genuine and not just the result of data mining. But these profit opportunities had disappeared by the early 1990s for filter and moving average rules. Returns to less-studied rules also have declined but have probably not completely disappeared. High volatility prevents precise estimation of mean returns. These regularities are consistent with the Adaptive Markets Hypothesis (Lo (2004)), but not with the Efficient Markets Hypothesis.

Technical Analysis and Central Bank Intervention

This paper extends the genetic programming techniques developed in Neely, Weller and Dittmar (1997) to show that technical trading rules can make use of information about U.S. foreign exchange intervention to improve their out-of-sample profitability for two of four exchange rates. Rules tend to take positions contrary to official intervention and are unusually profitable on days prior to intervention, indicating that intervention is intended to check or reverse predictable trends. Intervention seems to be more successful in checking predictable trends in the out-of-sample (1981-1996) period than in the in-sample (1975-1980) period. We conjecture that this instability in the intervention process prevents more consistent improvement in the excess returns to rules. We find that the improvement in performance results solely from more efficient use of the information in the past exchange rate series rather than from information about contemporaneous intervention.

Technical Trading Rules in the European Monetary System

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EXCHANGE RATE BANDS WITH PRICE INERTIA

We formulate a stochastic rational-expectations model of exchange rate determination in which there are random shocks to the process of sluggish price adjustment. We examine the effects of imposing limits upon the range of variation of both nominal and real exchange rates, and describe the intervention policies needed to defend the bands in each case. We consider the possibility that commitment to defend a particular nominal band may be less than fully credible, and analyze the implications of operating certain rules for realignment. We contrast our results with those which arise in the Krugman model of a nominal band.

Technical Analysis in the Foreign Exchange Market

This article introduces the subject of technical analysis in the foreign exchange market, with emphasis on its importance for questions of market efficiency. Technicians view their craft, the study of price patterns, as exploiting traders’ psychological regularities. The literature on technical analysis has established that simple technical trading rules on dollar exchange rates provided 15 years of positive, risk-adjusted returns during the 1970s and 80s before those returns were extinguished. More recently, more complex and less studied rules have produced more modest returns for a similar length of time. Conventional explanations that rely on risk adjustment and/or central bank intervention are not plausible justifications for the observed excess returns from following simple technical trading rules. Psychological biases, however, could contribute to the profitability of these rules. We view the observed pattern of excess returns to technical trading rules as being consistent with an adaptive markets view of the world.

Lessons from the Evolution of Foreign Exchange Trading Strategies

The adaptive markets hypothesis posits that trading strategies evolve as traders adapt their behavior to changing circumstances. This paper studies the evolution of trading strategies for a hypothetical trader who chooses portfolios from foreign exchange (forex) technical rules in major and emerging markets, the carry trade, and US equities. The results show that a backtesting procedure to choose optimal portfolios improves upon the performance of nonadaptive rules. We also find that forex trading alone dramatically outperforms the S&P 500, with much larger Sharpe ratios over the whole sample, but there is little gain to coordinating forex and equity strategies, which explains why practitioners consider these tools separately. Forex trading returns dip significantly in the 1990s but recover by the end of the decade and have been markedly superior to an equity position since 1998. Overall, trading rule returns still exist in forex markets—with substantial stability in the types of rules—though they have migrated to emerging markets to a considerable degree.

Currency Bands, Target Zones, and Price Flexibility

Exchange rate behavior is analyzed in the context of a stochastic rational expectations model in which there are random shocks to the price-setting mechanism and in which the authorities choose to impose either nominal or real exchange rate bands. The effects of rules for realignment of the band are also examined. Results are compared with those that emerge from a simple monetary model subject to velocity shocks.

Using a Genetic Program to Predict Exchange Rate Volatility

This article illustrates the strengths and weaknesses of genetic programming in the context of forecasting out-of-sample volatility in the DEM/USD and JPY/USD markets. GARCH(1,1) models serve used as a benchmark. While the GARCH model outperforms the genetic program at short horizons using the mean-squared-error (MSE) criterion, the genetic program often outperforms the GARCH at longer horizons and consistently returns lower mean absolute forecast errors (MAE).

Currency Bands, Target Zones, and Cash Limits; Thresholds for Monetary and Fiscal Policy

Exchange rate behavior is analyzed in the context of a stochastic rational expectations model in which there are random shocks to the price setting mechanism and in which the authorities choose to impose either nominal or real exchange rate bands. Results are compared to those that emerge from a simple monetary model subject to velocity shocks. The effects of a realignment of the band, and of fiscal policy used in conjunction with monetary policy to defend the band, are also examined.