Market Efficiency and Returns to Simple Technical Trading Rules: Further Evidence from U.S., U.K., Asian and Chinese Stock Markets

Tian, Wan and Guo (2002) explored the predictability and profitability of technical trading rules in markets with different efficiency levels; namely, the U.S. and China. In the case of the U.S. they found rules to have no predictability after 1975, whereas their results give support to technical trading rules having both predictability and profitability for the Chinese markets across the 1990's. The purpose of this paper is to extend the analysis of Tian et al. in two ways. First, to see if the conclusions extend to other markets – namely, the U.K., Hong Kong and Japan. Second, in the case of China, to examine whether the predictability and profitability of technical trading rules changed across the 1990's. On the basis of daily data Tian et al's results for the U.S. market are supported by the results for a number of the main developed markets where the technical trading rules had predictive ability during the 1970's that disappeared by the 1990's. Furthermore, the results suggest that while technical trading rules had short term predictive ability and profitability in the Chinese stock markets during the 1990's, this lessened as the decade progressed. JEL Classification: G14, G15     

Can channel pattern trading be profitably automated?

Financial markets, such as the global foreign exchange (FX) market, often exhibit trending behaviour. Within such trends, the market level oscillates with changes in market consensus. Continued oscillations of this type result in the formation of wave patterns within the underlying trend known as channels, which are used by technical analysts as trade entry signals. A sample space of such channels has been constructed from a set of US dollar/British pound Spot FX tick data from 1989–1997 using pattern recognition algorithms and the profitability of trading using such patterns has been estimated. A number of attributes of the resulting collection of channels has been subjected to statistical analysis with the aim of classifying patterns that can be traded profitably using a number of simple trading rules. Results of this analysis show that there exist statistically significant links between the channels' attributes and profitability.     

Can technical trading beat the foreign exchange market in times of crisis?

I examine the profitability of three simple foreign exchange technical trading rules (moving average, momentum, and relative strength index) before, during, and after the 2007–2008 global financial crisis. These rules significantly improve profitability during the crisis (as opposed to before and after it). The moving average rule significantly increases profitability for exchange rate changes during the crisis. The momentum and relative strength index rules generate significant positive excess currency returns (defined as the difference between the forward premium and spot rate changes), but this profitability is not visible in spot rate changes. These findings are robust for portfolios of developed and emerging market currencies as well as for bilateral exchange rates.     

Trading the foreign exchange market with technical analysis and Bayesian Statistics

In this study, the profitability of technical analysis and Bayesian Statistics in trading the EUR/USD, GBP/USD, and USD/JPY exchange rates are examined. For this purpose, seven thousand eight hundred forty-six technical rules are generated, and their profitability is assessed through a data snooping procedure. Then, the most promising rules are combined with a Naïve Bayes, a Relevance Vector Machine, a Dynamic Model Averaging, a Dynamic Model Selection and a Bayesian regularized Neural Network model. The findings show that technical analysis has value in foreign exchange trading, but the profit margins are small. On the other hand, Bayesian Statistics seems to increase the profitability of technical rules up to five times.     

Fuzzy logic,trading uncertainty and technical trading

From the market microstructure perspective, technical analysis can be profitable when informed traders make systematic mistakes or when uninformed traders have predictable impacts on price. However, chartists face a considerable degree of trading uncertainty because technical indicators such as moving averages are essentially imperfect filters with a nonzero phase shift. Consequently, technical trading may result in erroneous trading recommendations and substantial losses. This paper presents an uncertainty reduction approach based on fuzzy logic that addresses two problems related to the uncertainty embedded in technical trading strategies: market timing and order size. The results of our high-frequency exercises show that ‘fuzzy technical indicators’ dominate standard moving average technical indicators and filter rules for the Euro-US dollar (EUR-USD) exchange rates, especially on high-volatility days.     

An analysis of trading strategies in eleven European stock markets

Abstract

In recent years, the validity of the weak form efficient market hypothesis (EMH) has been called into question as several studies have uncovered evidence that technical trading rules have predictive ability with respect to both developed and emerging stock market indices. This study analyses the forecasting power of 2 of the most popular trading rules using index data for a selection of 11 European stock markets over the January 1991 to December 2000 period. The findings indicate that the emerging markets included in this paper are informationally inefficient; these markets displayed some degree of predictability in their share returns, although the developed markets did not. Furthermore, the results point to large differences in the performance of the rules examined; while small size filters consistently outperformed the buy-and-hold strategy in the emerging markets examined even after the consideration of transaction costs, the performance of the moving average rules was erratic and varied dramatically from market to market.     

Tests of technical trading strategies in the emerging equity markets of Latin America and Asia

This study examines the potential profit of ten Variable Length Moving Average (VMA) technical trading rules in ten emerging equity markets in Latin America and Asia from January 1982 through April 1995. The average difference in buy − sell returns after trading costs for each rule and country are compared to a buy and hold strategy. Taiwan, Thailand and Mexico emerge as markets where technical trading strategies may be profitable. We find no strong evidence of profitability for the other markets. However, we find that 82 out of the 100 country–trading rule combinations tested in ten emerging markets, disregarding their statistical significance, correctly predict the direction of changes in the return series. These findings may provide investors with important asset allocation information.     

How profitable are FX technical trading rules?

This paper provides a comprehensive empirical investigation of the profitability of foreign exchange technical trading rules over the 1996:10–2015:06 period for 22 currencies quoted in US dollars. It reports evidence of profitability across a universe of 113,148 rules that include traditional moving average rules and those constructed on the basis of technical indicators such as Bollinger bands and the relative strength index. The best trading rules achieve annualised returns of up to 30%. The Step-SPA test (Hsu, Hsu, & Kuan, 2010) results show a sharp fall in the total number of rules that are robust to data snooping bias. Virtually no traditional rule is significant in the 2006–2015 sub-sample, in line with the adaptive market hypothesis. By contrast, rules based on new technical indicator such as Bollinger band and relative strength index rules remain robustly profitable across all currencies over the more recent sub-sample.     

FX technical trading rules can be profitable sometimes!

This paper investigates the profitability of technical trading rules in the foreign exchange market taking into account data snooping bias and transaction costs. A universe of 7650 trading rules is applied to six currencies quoted in U.S. dollars over the 1994:3–2014:12 period. The Barras, Scaillet, and Wermers (2010) false discovery rate method is employed to deal with data snooping and it detects almost all outperforming trading rules while keeping the proportion of false discoveries to a pre-specified level. The out-of-sample results reveal a large number of outperforming rules that are profitable over short periods based on the Sharpe ratio. However, they are not consistently profitable and so the overall results are more consistent with the adaptive markets hypothesis.     

Adaptive Learning in an Expectational Difference Equation with Several Lags: Selecting among Learnable REE

It is demonstrated that adaptive learning in the least squares sense may be incapable of satisfactorily reducing the number of attainable equilibria in a rational expectations model when focusing on the forward‐solutions to the model. The model examined, as an illustration, is a basic asset pricing model for exchange rate determination that is augmented with technical trading in the currency market in the form of moving averages since it is the most commonly used technique according to questionnaire surveys. The forward‐solutions to such a model are preferable to the backward‐solutions that are normally utilized since announcement effects is an important feature in currency trade. Because of technical trading in foreign exchange, the current exchange rate depends on j _max lags of the exchange rate, meaning that the model has j _max+1 rational expectations equilibria, where several of them are adaptively learnable in the least squares sense. However, since past exchange rates should not affect the current exchange rate when technical trading is absent, it is possible to single out a unique equilibrium among the adaptively learnable equilibria that is economically meaningful. It is worth noting that the model examined can also be viewed as a model for stock price determination in which the forward‐solutions to the model are preferable to the backward‐solutions since the importance of announcement effects is a common characteristic for currency and stock markets.     

Dynamic characteristics of the daily yen–dollar exchange rate

This paper explores various dynamic properties of daily data for the yen–dollar exchange rate. This empirical study shows that quantitative information articulated with technical trading acts as market-based indicators, thus contributing to the modelling of daily fluctuations in the exchange rate. Value-at-Risk analysis is also performed to demonstrate that allowing for data properties such as skewness is essential for representing the underlying volatility of the yen–dollar rate.     

Are chartists artists? The determinants and profitability of recommendations based on technical analysis

The value of technical analysis (TA) has been debated for decades; however, limited evidence exists on the profitability of investment recommendations issued by technical analysts. These ‘chartists’ sometimes claim that TA is an art rather than a science. We evaluated > 5000 TA-based buy and sell recommendations for stocks and a market index in the Netherlands issued during the period 2004–2010. The sign of a recommendation was generally in line with trading signals resulting from technical trading rules. While recommendation levels were positively associated with price trends prior to the recommendation, we did not find evidence of (abnormal) stock returns after the publication of these recommendations. In addition, stop-loss levels did not contain informational value as no meaningful returns were detected after these trigger levels were met. Given that technical recommendations follow well-known trading rules and that these recommendations are not associated with future abnormal returns, we conclude that technical analysts do not exhibit ‘artistic’ skills.     

The Effectiveness of Technical Trading for Arab Stocks

In this paper, we examine the profitability of technical analysis for a cross section of individual Arab stocks. Our analysis, undertaken from the perspective of an Islamic investor, reveals that technical trading rules do not yield economically or statistically significant returns. While our results uncover some scant statistical evidence of technical trading rule profitability, risk adjusting the returns weakens the evidence in favor of predictability. Furthermore, break-even transaction costs do not exceed estimated transaction costs or bid-ask spreads in the markets examined.     

Is the Swedish stock market efficient? Evidence from some simple trading rules

In this paper we examine the profitability of some technical trading rules in the Swedish stock market over the 1986-2004 periods. The results indicate that moving average rules do indeed have predictive power and could discern recurring-price patterns for profitable trading, even after accounting for the effects of data snooping biases. To assess the profitability of different technical trading rules and strategies, we adopt White's [White, H. (2000). A Reality Check for data snooping, Econometrica, 68, 1097-1126.] Reality Check test that quantifies the data snooping bias adjusting for its effects. Our results also support the hypothesis that technical trading rules can outperform the buy-and-hold strategy even considering transaction costs.     

Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did by Brock, Lakonishok and LeBaron (1992) and later by Bessembinder and Chan (1998), this paper examines predictive power and profitability of simple trading rules by expanding their universe of 26 rules to 412 rules. In order to find out the relationship between market efficiency and excess return by applying trading rules, we examine excess return over periods in U.S. markets and also compare the excess returns between U.S. market and Chinese markets. Our results found that there is no evidence at all supporting technical forecast power by these trading rules in U.S. equity index after 1975. During the 1990s break-even costs turned to be negative, –0.06%, even failing to beat a buy-holding strategyin U.S. equity market. In comparison, our results provide support for the technical strategies even in the presence of trading cost in Chinese stock markets.     

Performance of technical trading rules: evidence from the crude oil market

ABSTRACT

This study investigates the debatable success of technical trading rules, through the years, on the trending energy market of crude oil. In particular, the large universe of 7846 trading rules proposed by Sullivan, Timmermann, and White (1999. “Data-Snooping, Technical Trading Rule Performance, and the Bootstrap.” The Journal of Finance 54 (5): 1647–1691. doi:10.1111/0022-1082.00163), divided into five families (filter rules, moving averages, support and resistance rules, channel breakouts, and on-balance volume averages), is applied to the daily prices of West Texas Intermediate (WTI) light, sweet crude oil futures as well as the United States Oil (USO) fund, from 2006 onwards. We employ the k-familywise error rate (k-FWER) and false discovery rate (FDR) techniques proposed by Romano, J. P., and M. Wolf. (2007. “Control of Generalized Error Rates in Multiple Testing.” The Annals of Statistics 35 (4): 1378–1408. doi:10.1214/009053606000001622) and Bajgrowicz, P., and O. Scaillet. (2012. “Technical Trading Revisited: False Discoveries, Persistence Tests, and Transaction Costs.” Journal of Financial Economics 106 (3): 473–491. doi:10.1016/j.jfineco.2012.06.001) respectively, accounting for data snooping in order to identify significantly profitable trading strategies. Our findings explain that there is no persistent nature in rules performance, contrary to the in-sample outstanding results, although tiny profits can be achieved in some periods. Overall, our results seem to be in favor of interim market inefficiencies.     

Do momentum-based strategies work in emerging currency markets?

Existing studies on the profitability of trading rules in the currency market focus mainly on the currencies of developed countries. The profitability of technical trading rules on the currencies of emerging economies is surprisingly understudied. This paper evaluates the profitability of technical trading rules in emerging currency markets. Similar to Okunev and White [Okunev, J. and White, D., (2003) “Do Momentum-based Strategies Still Work in Foreign Currency Markets?” Journal of Financial and Quantitative Analysis 38, 425–447.], 354 long/short moving average rules for six currencies are investigated. It is found that investing in emerging currencies can generate a considerable annual return of over 20%, even after a 5% annual transaction cost is imposed. The trading-rule profits are relatively stable across the 20 year sample period. Furthermore, the impact of financial crises on the trading-rule returns is also examined. It is found that the profitability of the trading rules is improved after the crises.     

Heuristic learning in intraday trading under uncertainty

Until recently economists focused on structural models that were constrained by a lack of high-frequency data and theoretical deficiencies. Little academic research has been invested in actually trying to build successful real-time trading models for the high-frequency foreign exchange market, which is characterized by inherent complexity and heterogeneity. The present work opens new directions for inference on market efficiency in an attempt to account for the use of technical analysis by practitioners over many years now. This paper presents a heuristic model that efficiently emulates the dynamic learning of intraday traders. The proposed setup incorporates agent beliefs, preferences and expectations while it integrates the calibration of technical rules by means of adaptive training. The study focuses on EUR/USD which is the most liquid and widely traded currency pair. The data consist of a very large tick-by-tick sample of bid and ask prices covering many trading periods to enhance robustness in the results. The efficiency of a technical trading strategy based on the proposed model is investigated in terms of directional predictability. The heuristic learning system is compared against many non-linear models, a random walk and a buy & hold strategy. Based on statistical testing it is shown that, with the inclusion of transaction costs, the profitability of the new model is consistently superior. These findings provide evidence of technical predictability under incomplete information and can be justified by invoking the existence of heterogeneity caused by many factors affecting market microstructure. Overall, the results suggest that the proposed model can be used to improve upon traditional technical analysis approaches.     

Exchange traded currency derivatives markets in India: the road ahead

Indian exchanges have recently been permitted to offer currency futures on their platforms to the market participants. The paper outlines the contract, and charts the development and growth of currency futures in India since their inception in 2008. It emphasizes the existing close connectivity between commodity and currency markets. It highlights the increased exchange rate volatility of Indian exchange rate against US dollar (INRUSD) during conventional and non conventional trading hours and argues for the ability of the market to quickly adapt to extended trading hours. The paper recommends some new products and an alternative mechanism to settle the contracts.     

Discount rate changes and the foreign exchange market

Changes in the discount rate can have associated announcement effects on the foreign exchange value of the dollar only if these changes are not anticipated by the market. This paper provides evidence to support this contention. Specifically, discount rate changes made for reasons other than technical adjustments have not been anticipated fully and, consequently, their announcements have had a significant impact on the dollar's exchange rate. Furthermore, results are obtained that support the hypothesis that unanticipated discount rate changes alter inflationary expectations.