Currency Trading

Are there technical trading rules that persist in profitability, or does the market adapt to extinguish them? In their January 2011 paper entitled “Technical Analysis in the Foreign Exchange Market”, Christopher Neely and Paul Weller review research on technical trading returns in the foreign exchange market during the era of floating exchange rates. They focus on trends in profitability of technical trading rules and examine whether data snooping/mining biases may have been the sources of past findings of profitability. Based on a survey of academic research on technical trading in the foreign exchange market since the early 1970s, they conclude that: Keep Reading

Is the aggregate effect of technical trading visible and exploitable in currency exchange rate trading? In his 2008 paper entitled “Aggregate Trading Behaviour of Technical Models and the Yen/Dollar Exchange Rate 1976-2007”, Stephan Schulmeister investigates the interaction between the aggregate signaling of 1,024 moving average and momentum rules and the behavior of the yen/dollar exchange rate. Using daily yen/dollar exchange rate data over the period 1976-2007, he finds that: Keep Reading

A reader asked: “Does a combination of rotation by relative strength (momentum) and moving averages, similar to that described in Mebane Faber’s Ivy Portfolio, work for the main currencies?” Keep Reading

Are “proven” technical trading rules reliable profit-makers, or artifacts of data snooping bias? In their April 2010 paper entitled “Illusory Profitability of Technical Analysis in Emerging Foreign Exchange Markets”, Pei Kuang, Michael Schröder and Qingwei Wang apply several tests to evaluate the decisiveness of data snooping bias in the past profitability of technical trading rules for ten emerging foreign exchange markets. These environments are arguably less intensively mined than many other financial markets. Using spot exchange rates in the selected markets over the period January 1994 to July 2007 to test 25,998 commonly used simple, pattern and complex trading rules (see the table below), they find that: Keep Reading

Can people reliably distinguish between actual financial markets time series and randomized data? In the February 2010 draft of their paper entitled “Is It Real, or Is It Randomized?: A Financial Turing Test”, Jasmina Hasanhodzic, Andrew Lo and Emanuele Viola report the results of a web-based experiment designed to test the ability of people to distinguish between time series of returns for eight commonly traded financial assets (including stock indexes, a bond index, currencies and commodities, all given names of animals) and randomized data. Using a sample of 8015 guesses from 78 participants over eight contests conducted during 2009, they conclude that: Keep Reading

A reader suggested: “You might test the Bollinger Band- Keltner Channel breakout detection model on the euro. Equity indexes generally have performed anti-trend (reversion to the mean) whereas currencies have trended.” Keep Reading

Do Commodity Trading Advisors (CTAs), generally associated with the “managed futures” hedge fund style, successfully time their chosen markets? These traders take long or short positions in investment vehicles with low transaction cost (such as futures contracts) to exploit trends in commodity prices, exchanges rates, interest rates and equity prices. In the February 2008 version of their paper entitled “Market Timing of CTAs: An Examination of Systematic CTAs vs. Discretionary CTAs”, Hossein Kazemi and Ying Li investigate the return and volatility timing ability of CTAs and examine whether there is a difference in market timing abilities between systematic and discretionary traders. To this end, they develop a set of risk factors based on returns from the most heavily traded futures contracts. Using monthly, net-of-fees return data for 1994-2004 (encompassing 278 live and 622 defunct CTA funds), they conclude that: Keep Reading

Triumph of the Optimists: 101 Years of Global Investment Returns by Dimson, Marsh and Staunton (2002) is thorough, logical and concise. With scores of illustrative graphs and figures, its statistics are accessible and its style straightforward. Its message, however, is somewhat at odds with the title. Below is a chapter-by-chapter review of the insights in this book: Keep Reading