† † We thank the editor, Christian C. P. Wolff, and two anonymous referees for their useful comments and suggestions. We are grateful for the comments on early versions of this paper by Zongwu Cai, Stephen

Foreign exchange (forex) market trading using evolutionary algorithms is an active and controversial area of research. We investigate the use of a linear genetic programming (LGP) system for automated forex trading of four major currency pairs. Fitness functions with varying degrees of conservatism through the incorporation of maximum drawdown are considered. The use of the fitness types in the LGP system for different currency value trends are examined in terms of performance over time, underlying trading strategies, and overall profitability. An analysis of trade profitability shows that the LGP system is very accurate at both buying to achieve profit and selling to prevent loss, with moderate levels of trading activity.

seminars for helpful comments and suggestions. We are very grateful to Gareth Berry, Geoffrey Kendrick and UBS for providing us with the proprietary data used in this study, and for numerous conversations on the institutional details of foreign exchange trading at UBS. Sarno acknowledges financial support from the Economic and Social Research Council (No. RES-062-23-2340) and Menkhoff and Schmeling gratefully acknowledge financial support by the German Research Foundation (DFG). The views expressed in this paper are those of the authors and do not necessarily reflect those of the Bank for International Settlements.

Abstract This study sought to investigate if exchange rate arbitrage existed in the Mombasa spot market. The study was conducted in a background of gains in information efficiencies, drastic reductions in information costs

Copyright belongs to the author. Small sections of the text, not exceeding three paragraphs, can be used provided proper acknowledgement is given. The Rimini Centre for Economic Analysis (RCEA) was established in March 2007. RCEA is a private, nonprofit organization dedicated to independent research in Applied and Theoretical Economics and related fields. RCEA organizes seminars and workshops, sponsors a general interest journal The Review of Economic Analysis, and organizes a biennial conference: The Rimini Conference in Economics and Finance (RCEF). The RCEA has a Canadian branch: The Rimini Centre for Economic Analysis in Canada (RCEA-

iii My thesis consists of three essays investigating sources of profits to price momentum and related trading strategies in financial markets. Although each essay can stand independently, the methods used in them overlap and their concepts are closely interrelated. My first essay (Chapter 2) examines price momentum in emerging currency markets. I find that long-short momentum strategies gain about 1–3 % per annum after actual transaction costs. These results are similar to, but more volatile than, those already published for major currencies. My findings contrast starkly with those of the only other comprehensive paper published in the very limited literature in this area. Contrary to published results in major currencies, I find that emerging market currency momentum strategies typically borrow in high interest rate currencies and invest in low interest rate currencies. Also, as the domestic interest rates of the base currency rise in the cross section, momentum profits fall and the return attribution shifts from the short position to

This paper studies predictability of currency returns over time and the extent to which it is captured by trading rules commonly used in currency markets. We consider the strategies that an investor endowed with rational expectations could have pursued to exploit out-of-sample currency predictability and generate abnormal returns. We find a close relation between these strategies and indices that track popular technical trading rules, namely moving average cross-over rules and the carry trade, implying that the technical rules represent heuristics by which professional market participants exploit currency mispricing. We find evidence that such mispricing reflects initially wrong investors' beliefs (wrong priors), but information is efficiently processed as it becomes available. Predictability is highest in the mid '90, subsequently decreases sharply, but increases again in the final part of the sample period, especially for the Euro and other emerging currencies. Technical Trading, Predictability and Learning in Currency Markets This paper studies predictability of currency returns over time and the extent to which it is captured by trading rules commonly used in currency markets. We consider the strategies that an investor endowed with rational expectations could have pursued to exploit out-of-sample currency predictability and generate abnormal returns. We find a close relation between these strategies and indices that track popular technical trading rules, namely moving average cross-over rules and the carry trade, implying that the technical rules represent heuristics by which professional market participants exploit currency mispricing. We find evidence that such mispricing reflects initially wrong investors' beliefs (wrong priors), but information is efficiently processed as it becomes available. Predictability is highest in the mid '90, subsequently decreases sharply, but increases again in the final part of the sample period, especially for the Euro and other emerging currencies.

The crude oil futures market plays a critical role in energy finance. To gain greater investment return, scholars and traders use technical indicators when selecting trading strategies in oil futures market. In this paper, the authors used moving average prices of oil futures with genetic algorithms to generate profitable trading rules. We defined individuals with different combinations of period lengths and calculation methods as moving average trading rules and used genetic algorithms to search for the suitable lengths of moving average periods and the appropriate calculation methods. The authors used daily crude oil prices of NYMEX futures from 1983 to 2013 to evaluate and select moving average rules. We compared the generated trading rules with the buy-and-hold (BH) strategy to determine whether generated moving average trading rules can obtain excess returns in the crude oil futures market. Through 420 experiments, we determine that the generated trading rules help traders make profits when there are obvious price fluctuations. Generated trading rules can realize excess returns when price falls and experiences significant fluctuations, while BH strategy is better when price increases or is smooth with few fluctuations. The results can help traders choose better strategies in different circumstances.

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