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.     

Trend‐Following Trading Strategies in U.S. Stocks: A Revisit

We show that previous findings regarding the profitability of trend‐following trading rules over intermediate horizons in futures markets also extend to individual U.S. stocks. Portfolios formed using technical indicators such as moving average or channel ratios, without employing cross‐sectional rankings of any kind, tend to perform about as well as the more commonly examined momentum strategies. The profitability of these strategies appears significant, both statistically and economically, through 2007, but evidence of profitability vanishes after 2007. Market‐state dependence, while clearly present, does not explain the post‐2007 reduction in returns to these strategies.     

Predictability of nonlinear trading rules in the U.S. stock market

Most of the existing technical trading rules are linear in nature. This paper investigates the predictability of nonlinear time series model based trading strategies in the U.S. stock market. The performance of the nonlinear trading rule is compared with that of the linear model based rules. It is found that the self-exciting threshold autoregressive (SETAR) model based trading rules perform slightly better than the AR rules for the Dow Jones and Standard and Poor 500, while the AR rules perform slightly better in the NASDAQ market. Both the SETAR and the AR rules outperform the VMA rules. The results are confirmed by bootstrap simulations.     

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.     

Economic and financial crises and the predictability of U.S. stock returns

We argue that the use of publicly available and easily accessible information on economic and financial crises to detect structural breaks in the link between stock returns and macroeconomic predictor variables improves the performance of simple trading rules in real time. In particular, our results suggest that accounting for structural breaks and regime shifts in forecasting regressions caused by economic and financial crises has the potential to increase the out-of-sample predictability of stock returns, the performance of simple trading rules, and the market-timing ability of an investor trading in the U.S. stock market.     

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.     

Predictability,trading rule profitability and learning in currency markets

This paper studies currency predictability over time. We assess predictability by testing for the presence of exploitable patterns in currency returns. To do so, we first generate consistent and parsimonious reduced-form estimates of currency expected returns and variances and then use these estimates to form dynamic trading strategies that maximize the multi-period Sharpe ratio. Our results show that currency predictability is time-varying and, for a number of currencies, has increased substantially in recent times, casting doubt on the widespread view that currency pricing may be on a path of convergence towards efficiency. We find, however, that currency markets learn in an efficient manner and a close relation between our strategies and indices that track popular technical trading rules, namely moving average cross-over rules and the carry trade, suggesting that the technical rules represent heuristics by which professional market participants exploit currency mispricing.     

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.     

Persistence and Predictability in UK House Price Movements

This paper extends the analysis of predictability and persistence of inflation-adjusted house price movements in the UK housing market both on a regional level across 13 regions and on a nationwide level. Applying a univariate time series approach, the results from the quarterly transaction-based Nationwide Building Society indices from 1974 to 2009 provide empirical evidence for a high persistence of house price movements. In addition to conducting parametric and non-parametric tests, we provide technical trading strategies as a robustness check to compare predictability across markets and to test whether or not the detected persistence can also be used for detecting turning points in the market. The empirical findings from the technical trading strategies support the results from the statistical tests. Moving average-based trading strategies perform extremely well in the southern regions, while trading strategies are less profitable for the northern regions and Wales. Thus, from an investors’ perspective, there are excess real returns from moving average-based strategies compared to a buy-and-hold strategy for most regional markets. From a household perspective, the findings support the importance of derivative markets where households could hedge their risk exposure from being homeowner.     

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.     

Information, speed vs. cost trade-offs, and order routing decisions in U.S. equity markets

Prior research indicates that both execution speed and cost are important to traders, but that these two dimensions of execution quality are negatively related across U.S. equity markets. In our paper, we examine how U.S. equity traders, who are (un)informed about future price changes, trade-off between speed and cost in their order-routing decisions. We find that informed traders are more likely to choose trading systems that allow them to trade-off lower cost for faster speed; whereas, uninformed traders are more likely to choose trading systems that allow them to sacrifice speed for lower costs. Our results indicate that traders have varying preferences for the different dimensions of execution quality based on their information levels. These differences subsequently influence order-routing decisions.     

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.     

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.     

中国A股市场存在品质溢价吗?

本文从价值投资的核心理念出发,基于盈利性、成长性、安全性、分红能力四个维度构建复合品质指标,并通过分析品质溢价在中国A股市场中的存在性来探讨价值投资的可行性和有效性。实证结果表明:(1)中国A股市场上存在显著为正的品质溢价,且品质溢价在控制其他相关变量后依然稳健存在;(2)高品质股票具有大市值、高成长特征,且品质溢价在大市值、高盈利的分组中更加显著;(3)品质溢价在不同时期下均能稳定存在;(4)中国A股市场上的品质溢价并非源于高风险承担,相反,由正向反馈偏好、博彩偏好、套利限制引起的错误定价有助于解释品质溢价。本文结论佐证了价值投资策略在中国A股市场的可行性和有效性,为培育良好投资理念、抑制过度投机、促进中国股市合理健康发展等提供了经验证据。     

Predictable Stock Returns in the United States and Japan: A Study of Long-Term Capital Market Integration

This paper uses the predictability of monthly excess returns on U.S. and Japanese equity portfolios over the U.S. Treasury bill rate to study the integration of long-term capital markets in these two countries. During the period 1971–1990 similar variables, including the dividend-price ratio and interest rate variables, help to forecast excess returns in each country. In addition, in the 1980's U.S. variables help to forecast excess Japanese stock returns. There is some evidence of common movement in expected excess returns across the two countries, which is suggestive of integration of long-term capital markets.     

Profitability of technical stock trading: Has it moved from daily to intraday data?

This paper investigates how technical trading systems exploit the momentum and reversal effects in the S&P 500 spot and futures market. When based on daily data, the profitability of 2580 technical models has steadily declined since 1960, and has been unprofitable since the early 1990s. However, when based on 30-minutes-data the same models produce an average gross return of 7.2% per year between 1983 and 2007. These results do not change substantially when trading is tested over eight subperiods. In particular, there is no clear trend of a declining profitability of technical stock trading based on 30-minutes-data. Those 25 models which performed best over the most recent subperiod produce a significantly higher gross return over the subsequent subperiod than all models. Between 2001 and 2007 the 2580 models perform worse than over the 1980s and 1990s. This result could be due to stock markets becoming recently more efficient or to stock price trends shifting from 30-minutes-prices to prices of higher frequencies.     

Information Flows Between the U.S. and China Commodity Futures Trading

Using a bivariate GARCH model, we examine patterns of information flows for three commodity futures traded in both the developed U.S. market and the emerging China market (copper, soybeans and wheat). For copper and soybeans, the two commodities that are subject to less government regulation and fewer import restrictions in China, we find that the U.S. futures market plays a dominant role in transmitting information to the Chinese market, a result that confirms the importance of the U.S. role as a leader in the global financial market. For the heavily regulated and subsidized wheat commodity, our empirical results indicate that the U.S.-China futures markets are highly segmented in pricing, although information transmission via volatility spillover across markets is present.     

French and U.S. trading of cross-listed stocks around the period of U.S. decimalization: Volume, spreads, and depth effects

We analyze how U.S. decimalization affects stocks cross-listed in France (Euronext) and the U.S. (NYSE). The French stocks examined are much larger than the non-U.S. stocks examined in prior studies of decimalization, and their U.S. trading is likely to be dominated by institutions. So, we explore whether a reduction in depths in the U.S. due to decimalization makes the U.S. market less competitive for institutions trading these French stocks. We find evidence consistent with the above. First, the average NYSE trade size for these stocks relative to that on Euronext declines substantially after decimalization. Second, we categorize individual trades by the number of shares traded. We find that mainly driven by large trades, the NYSE proportion of trading of French firms declines markedly after decimalization. Third, using regression analysis, we find that the decline in the U.S. share of institutional trading volume is significantly positively related with the decline in NYSE depths relative to Euronext, and the decline is greater for French firms. Overall, we find consistent results indicating a migration of institutional order flow in French firms to France after NYSE decimalization. Also, intraday analysis indicates that the institutional volume in both France and the U.S. is greatest when both the markets are open.     

Factor beta,overnight and intraday expected returns in China

We study the relationship between common factor betas and the expected overnight versus intraday stock returns. Using data from the Chinese A-share markets, we find that the Fama-French five-factor betas and expected returns exhibit contrasting relationships overnight versus intraday. The market, value, and profitability factors earn positive beta premiums overnight and negative premiums intraday, while the size and investment factors' beta premiums behave oppositely. The night and day factor beta premium differentials are more muted among stocks with higher investor sophistication and vary across macroeconomic conditions. The contrasting day and night beta premiums extend to some other common factors and Chinese B shares, and vary their signs for some factors in the U.S. market.     

The Causality Effects of the Federal Reserve's Monetary Policy on U.S. and Eurodollar Interest Rates

Previous studies argue that U.S. interest rates will become more sensitive to changes in eurodollar rates as international financial-market integration increases. However, the empirical results of these studies are suspect because they select their subperiods in an ad hoc manner and ignore the different trading hours of the U.S. and London markets. This study adjusts for the markets' different trading hours and uses Goldfeld and Quandt's switching regression technique to show that the causal relation between U.S. CD rates and eurodollar rates is impacted by the Federal Reserve's monetary policy. Because the latest subperiod exhibits uni-directional causality (i.e., U.S. interest rates cause changes in eurodollar rates), the results cast doubt on the implicit assumption made in the literature that interest-rate causality is only affected by increasing levels of financial-market integration.