Trend following with momentum versus moving averages: a tale of differences

Despite the ever-growing interest in trend following and a series of publications in academic journals, there is a dearth of theoretical results on the properties of trend-following rules. Our paper fills this gap by comparing and contrasting the two most popular trend-following rules, the momentum (MOM) and moving average (MA) rules, from a theoretical perspective. We provide theoretical results on the similarity between different trend-following rules and the forecast accuracy of trading rules. Our results show that the similarity between the MOM and MA rules is high and increases with the strength of the trend. However, compared to the MOM rule, the MA rules exhibit more robust forecast accuracy for the future direction of price trends. In this paper, we also develop a hypothesis about uncertain market dynamics. We show that this hypothesis, coupled with our analytical results, has far-reaching practical implications and can explain a number of empirical observations. Among other things, our hypothesis explains why the empirical performance of the MA rules is better than that of the MOM rule. We broaden the appeal and practical importance of our theoretical results by offering various illustrations and real-world examples.     

Tests of technical trading rules and the 52-week high strategy in the corporate bond market

This article presents the first tests of technical trend-following rules (TTRs) and the 52-week high strategy in individual corporate bonds, along with comparisons to corresponding stocks. Over the 2002–2015 period, TTR and the 52-week strategy are unprofitable in both bonds and stocks. Short legs of these trend-following strategies lead to significant losses in corporate bonds, which can be interpreted as evidence of bond investors' overreaction to bad news. Thus, short-term contrarian strategies, the profitability of which is viewed as the reward to liquidity provision, are more rewarding in corporate bonds. TTR buy signals can predict lower-volatility days in bonds as in stocks, despite the low/negative return correlations between the two.     

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.     

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.     

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.     

Have trend-following signals in commodity futures markets become less reliable in recent years?

Financial Markets and Portfolio Management - Various trend-following trading rules have been shown to be valuable for predicting market directions and thus the formulation of investment strategies....     

Performance of Currency Trading Strategies in Developed and Emerging Markets: Some Striking Differences

Expanding the currency investment universe makes a lot of sense from a diversification point of view. Nevertheless, 60% of the total foreign exchange turnover is still only traded in three currency pairs (USD/EUR, USD/JPY and USD/GBP). The share of trading in local currencies in emerging markets is only around 5%. This can be explained by the fact that some currency managers fear investing in emerging market currencies. Many believe that political risk is the most dominant driver in these markets and that traditional investment rules do not work. In this paper, I apply four technical trading strategies for the developed market currencies and for the most traded emerging market currencies. The empirical results show some striking differences. They suggest that trend-following rules work better for emerging market currencies, while carry trading strategies perform better across developed market currencies. Nevertheless, it seems that conventional techniques could be successfully applied to both developed and emerging market currencies. I conclude that currency managers should not be afraid to diversify into emerging market currencies. They should, however, adjust their trading style accordingly.     

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     

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.     

Are all Central Bank interventions created equal? An empirical investigation

This study investigates the relationship between Central Bank interventions and technical trading rule profitability in the spot foreign exchange market. Because interventions are not necessarily exogenous events, we analyze the relationships between interventions by the G-3 Central Banks, financial market conditions, changes in monetary policy and technical trading profitability. By considering announced, unannounced, unilateral and coordinated interventions separately, we provide more insight into the interrelationships between these factors than previous studies. We find that the level of technical trading profits and market uncertainty increase preceding and remain high during interventions, especially announced and coordinated, but decrease afterward. A preliminary investigation of the possible role of a time-varying risk premium around interventions cannot be rejected.     

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.     

Unifying Rule Induction and Rule Refinement—Towards Discovering Anomaly from Granville's Law in a Stock Market Technical Analysis

This paper discusses a framework for refining an initial object-level rule base with a rule induction to learn meta-level rules which find a data set applicable to an object-level rule. A rule induction process such as ID3 tries to learn meta-level rules and classifies given training data sets into positive data sets and negative ones. The rule refinement process tries to refine an initial object-level rule base on classified data sets by using four refinement strategies. Unifying these two processes, one can obtain a refined object-level rule base with high performance where a meta-level rule selects a data set applicable to it. In order to evaluate the framework, an experiment on real Japanese stock price data shows that a refined object-level rule base, which comes from the initial object-level rule base for representing Granville's Law, has a performance beyond that of the average stock price. The performance is difficult for human technical analysts in a stock market to achieve. The result implies that the framework could create an anomaly from Granville's Law in a stock market technical analysis.     

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.     

Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.     

The intertemporal risk-Return relation,investor behavior,and technical trading profits: evidence from the G-7 countries

The intertemporal risk-return relation and investor behavior are both important pricing factors that jointly determine the expected market risk premium. Using the price adjustment process as a control variable, we find that the intertemporal risk-return relation is positive conditional on bad market news, but is non-positive conditional on good market news. This implies that good (bad) market news weakens (strengthens) the positive risk-return relation. The pattern in the distortion of the risk-return relation is consistent with short-term mispricing in which investors overvalue (undervalue) the stock market in reaction to good (bad) market news. We also show that ignoring the price adjustment process in the estimation of the risk-return relation leads to model misspecification and induces an upward (downward) bias in estimates of the relative risk aversion parameter conditional on good (bad) news. Our model of the asymmetric risk-return relation along with the price adjustment process is capable of generating the return dynamics that is attributable to technical trading profits. We suggest that the profitability of technical trading rules is not a violation of market efficiency, but a consequence of trading rules exploiting the asymmetric effect of price changes on the risk-return relation, along with the persistence property of price changes.     

The use of technical analysis by fund managers: International evidence

The use of technical analysis by financial market professionals is not well understood. This paper thus analyzes survey evidence from 692 fund managers in five countries, the vast majority of whom rely on technical analysis. At a forecasting horizon of weeks, technical analysis is the most important form of analysis and up to this horizon it is thus more important than fundamental analysis. Technicians are as experienced, as educated, as successful in their career and largely just as overconfident in decision-making as others. However, technical analysis is somewhat more popular in smaller asset management firms. What we find most significant is the relation of technical analysis with the view that prices are heavily determined by psychological influences. Consequently, technicians apply trend-following behavior.     

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.     

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.