Abstract:This study tests four prevalent moving average technical trading rules for Taiwan stock markets. More notably, cross-national information from the US stock markets is also incorporated in our technical trading rules to project Taiwan stock market movements. We then design trading strategies and investigate their predictive power over buy-and-hold strategy. Our results suggest that technical trading rules are predictive for Taiwan stock markets. Applying the information reflected in the US stock markets to proj… Show more
“…Chang et al (2004) find profitable trading opportunities in a number of Asian emerging markets. Chang et al (2006) find that technical trading rules have predictive power for the Taiwan equity market.…”
Section: Introductionmentioning
confidence: 87%
“…Chang et al . () find that technical trading rules have predictive power for the Taiwan equity market.…”
“…Chang et al (2004) find profitable trading opportunities in a number of Asian emerging markets. Chang et al (2006) find that technical trading rules have predictive power for the Taiwan equity market.…”
Section: Introductionmentioning
confidence: 87%
“…Chang et al . () find that technical trading rules have predictive power for the Taiwan equity market.…”
“…For stock market studies see Goldberg and Schulmeister (1988), Brock, Lakonishok, and LeBaron (1992), Hudson, Dempsey, and Keasey (1996), Gunasekarage and Power (2001), Fernandez‐Rodriguez, Gonzalez‐Martel, Sosvilla‐Rivero (2000, 2005), Kwon and Kish (2002), Wong, Manzur, and Chew (2003), Jasic and Wood (2004), Chang, Metghalchi, and Chan (2006). “Abnormal” returns of technical analysis in foreign exchange markets are reported by Schulmeister (1988), Levich and Thomas (1993), Menkhoff and Schlumberger (1995), Gencay and Stengos (1998), Chang and Osler (1999), Neely and Weller (1999), Gencay (1999), LeBaron (1999), Osler (2000), Maillet and Michel (2000), Neely and Weller (2003), Okunev and White (2003), Schulmeister (2008a,b).…”
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AbstractThis 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-minutesprices to prices of higher frequencies.
“…For example, Kwon and Kish (2002) confirmed that technical trading rules can add a value to capture profit opportunities over a buy and hold strategy for the NYSE value-weighted index. Metaghachi and Chang (2003) and Chang, Metghalchi & Chan (2006) applied various moving average rules to conclude the profitability of technical trading in the Italian and the Taiwanese stock markets. Wong, Manzur & Chew (2003) investigated the Singapore data to indicate that the moving average and the relative strength index (RSI) can be used to generate significantly positive return.…”
We investigate the predictive power of various trading rules with different combinations of the most popular indicators in technical analysis for the Brazilian stock index (BOVESPA) over the period of 5/1/1996 to 3/1/2011, or 14.83 years. The empirical results show that all the buy-sell differences under single, double and triple-indicator combinations are insignificant in t-test; that is, technical trading models cannot beat the buy and hold strategy. Although few multiple-indicator trading models show profitability, their predictive power is eliminated after considering the possible interest earning from money market in the days out of stock market. The results support strongly the weak form of market efficiency for the Brazilian stock market.
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