Data Snooping on Technical Analysis: Evidence from the Taiwan Stock Market

2011 ◽  
Vol 14 (02) ◽  
pp. 195-212 ◽  
Author(s):  
Cheng-Wei Chen ◽  
Chin-Sheng Huang ◽  
Hung-Wei Lai

The main purpose of this paper is to investigate the validity and predictability of technical analysis in the Taiwan stock market. Bootstrapped tests of White (2000) and of Hansen (2005) are employed to ascertain whether there exists a superior trading rule among two broadly used sets of technical analysis. One coming from Brock et al. (1992) and the other from Sullivan et al. (1999). Moreover, this study brings together powerful bootstrapped tests along with two institutional adjustments to ascertain the efficacy of technical analysis: (1) non-synchronous trading and (2) transaction costs. The empirical results indicate that this triad-data snooping, non-synchronous trading and transaction costs, has a great impact on the performance of technical analysis. In fact, the Taiwan stock market stands for market efficiency, and economical profits cannot be rendered from technical analysis in this market.

Author(s):  
Vasileiou Evangelos

The purpose of this chapter is to examine if even the simplest trading rules could take advantage of the market's inefficiency and lead to profitable trading decisions. For this reason, this study examined the profitability of the simplest trading rules, using only the simple moving averages (SMA) rules that even an amateur investor could apply. In order to examine the specific issue a data sample from the Greek stock market during the period 2002-12 was used. The results suggest that even if one takes into account the most expensive transaction fees, the trading rules signal profitable investment decisions; therefore, even an amateur trader and/or investor who does not have a significant amount of money to invest (which may lead to reduced transaction costs) could take advantage of the market's inefficiency. Behavioral finance theories may provide some useful and alternative explanations regarding some of the reasons that contribute to the Greek stock market's inefficient environment.


2013 ◽  
Vol 7 (2) ◽  
pp. 11-27 ◽  
Author(s):  
Massoud Metghalchi

Market Efficiency and Profitability of Technical Trading Rules: Evidence from Vietnam Abstract            We apply several well-known and popular technical indicators to the daily data for the Vietnam Ho Chi Minh stock index (VSI) from 5/15/2002 to October 31 of 2012.  The empirical results strongly support the predictive power of technical trading rules; these strong results also hold for each sub-period analyzed. Further, we ask whether a trader can use the predictive power of technical analysis to beat the profitability of the buy-and-hold strategy considering both transaction costs and risk.  Designing four strategies of various trading rules, we conclude that it is possible to beat the buy-and-hold strategy even considering transaction costs and risk.


2017 ◽  
Vol 6 (3) ◽  
pp. 94 ◽  
Author(s):  
Osama El-Ansary ◽  
Dina Mohssen

As an emerging market, Egyptian stock market is characterized by inefficiency which is confirmed empirically in this research. This provoked us to test the ability of technical analysis classical patterns in predicting the future returns through calculating the expected price target consequently the expected future return and compare it with the actual return.Statistical techniques and models including Box Pierce (Ljung-Box), Variance ratio test, Runs test, and t-test bootstrapping technique have been applied to test the research proposed hypotheses. The empirical results revealed that the Egyptian stock market is inefficient as returns don’t follow random walk and are dependent, it is found also that the actual returns have significantly exceeded the expected returns of the detected patterns indicating that classical patterns can perfectly predict the direction of the price movements rather than the exact price targets.


Economies ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 92 ◽  
Author(s):  
Lam ◽  
Dong ◽  
Yu

We find value premium in the Chinese stock market using a conventional buy-and-hold approach which longs the portfolio with the highest BM ratio and shorts the one with the lowest BM ratio. Based on the finding, we test a new strategy by combining the value premium effect and technical analysis. During the sample period (1995 to 2015), we trade the objective portfolio or risk-free asset according to the moving average timing signals, and we find excess return from such a zero-cost trading strategy. We perform various robustness tests and find that the excess returns remain significantly positive after adjusting for risks (on three factor models) and transaction costs. In general, we find that the combined trading strategy can generate significant positive risk-adjusted returns after the transaction costs.


2020 ◽  
Vol 1 (6) ◽  
Author(s):  
Rashesh Vaidya

There are two types of analysis done for a stock market. One is fundamental analysis, where an investor looks at an intrinsic value of the stock, and another is technical analysis, where investors determine the future trend of the market looking at the current pattern or trend of the market. This paper is focused on one of the technical analysis tools, i.e., Moving Average Convergence-Divergence. It is a tool based on the three exponential moving average (9-12-26 EMA Rule). The MACD analysis, with the help of a single line, was helpful to find out the exact bullish and the bearish trend of the Nepse. A signal line is a benchmark to determine the stock market moving either to a bullish or bearish trend. It can help an investor, where the market is going in a direction. A market convergence, divergence, and crossover were better identified with the help of the MACD histogram. The paper found that the Nepse return was stable for a very minimal period from 1998-99 to 2019-20. The shift from the bullish to bearish or vice-verse were seen easily identified with the help of a MACD histogram. Finally, a better-combined knowledge of moving average and candlestick chart analysis will help an investor, to put a clear picture of a market trend with the help of MACD analysis.


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