The Significance Of Technical Trading Rule Profits In The Foreign Exchange Market

There is reliable evidence that simple rules used by traders have some predictive value over the future movement of foreign exchange prices. This paper will review some of this evidence and discuss the economic magnitude of this predictability. The profitability of these trading rules will then be analyzed in connection with central bank activity using intervention data from the Federal Reserve. The objective is to find out to what extent foreign exchange predictability can be confined to periods of central bank activity in the foreign exchange market. The results indicate that after removing periods in which the Federal Reserve is active, exchange rate predictability is dramatically reduced.

We report evidence on the profitability and statistical significance among 2,127 technical trading rules. The best rules are found to be significantly profitable based on standard tests. We then employ White's (2000) Reality Check to evaluate these rules and find that data-snooping biases do not change the basic conclusions for the full sample. A sub-sample analysis indicates that the data-snooping problem is more serious in the second half of the sample. Profitability becomes much weaker in the more recent period, suggesting that the foreign exchange market becomes more efficient over time. Evidence from cross exchange rates confirms the basic findings.

" During the last decades, the international financial markets saw enormous developments. Today, every newspaper offers advice on investment strategies and analysts seemingly earn money by drawing magic lines through prices series. Even though more and more traders rely on technical analysis, economists remain sceptical. How can the apparent success of technical trading strategies be reconciled with efficient market theories? This book mainly consists of three parts. The first part critically reviews the empirical literature on technical analysis and suggests to leave behind profitability calculations in favor of a systematic approach to analyzing trading rules, where special attention is given to the evaluation of the rules' forecasts. The second part presents the results of an empirical analysis that covers 5 exchange rates series spanning more than 20 years. In the third part, the theoretical background as well as the implications of a widespread use of technical analysis are critically discussed. The thorough overview presented here lays a foundation for further discussions of technical analyses and its effects on markets. "

Technical analysis is not supposed consistently to beat financial markets. In this book, however, Professors Surajaras and Sweeney seek to establish that carefully chosen rules can produce substantial and consistent measured profits over time. The authors also call into question the traditional academic wisdom that markets in general are efficient.

There is reliable evidence that simple rules used by traders have some predictive value over the future movement of foreign exchange prices. This paper will review some of this evidence and discuss the economic magnitude of this predictability. The profitability of these trading rules will then be analyzed in connection with central bank activity using intervention data from the Federal Reserve. The objective is to find out to what extent foreign exchange predictability can be confined to periods of central bank activity in the foreign exchange market. The results indicate that after removing periods in which the Federal Reserve is active, exchange rate predictability is dramatically reduced

Master's Thesis from the year 2005 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: A, Sophia Antipolis Campus (France); SKEMA Business School (Global Finance Chair), language: English, abstract: Most banks and the recently upcoming hedge fund industry rely to a different extent on technical trading rules and technical analysis. The fact that these technical trading rules yield superior returns in practice raises several questions that will be examined in the thesis. First, one of the most crucial questions is in which assets technical trading rules perform extraordinarily well. This analysis is based on a risk-return approach with an assessment of the negative standard deviation of each asset as a risk indicator. Second, the statistical significance of technical trading is examined by using a simulation method known as bootstrap. Third, null models are simulated to answer the question to what extent autoregressive models and GARCH models are able to capture the dependencies in the time series. Finally, a rule optimizer is used to assess if any rule parameters yield superior returns over a wide range of assets. We find that under a risk-return perspective trading rules look very attractive as most rules are able to significantly reduce the negative standard deviation compared to a buy-and-hold strategy. However, not all rules are able to outperform a simple buy-and-hold strategy in terms of absolute return. Statistical significance is generally weak and only some rules can be qualified as highly statistically significant. We do not find much evidence that autoregressive and GARCH null models perform well in capturing the dependencies that lead to superior returns of technical trading rules. With respect to trading rule parameters we find that shorter rules generally perform better when trading costs are not considered and that currencies benefited from a larger standard deviation trading band.