An information explanation of the survival of technical analysis in capital market (original) (raw)
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Technical analysis and individual investors
Journal of Economic Behavior & Organization, 2014
We find that individual investors who use technical analysis and trade options frequently make poor portfolio decisions, resulting in dramatically lower returns than other investors. The data on which this claim is based consists of transaction records and matched survey responses of a sample of Dutch discount brokerage clients for the period 2000-2006. Overall, our results indicate that individual investors who report using technical analysis are disproportionately prone to have speculation on short-term stock-market developments as their primary investment objective, hold more concentrated portfolios which they turn over at a higher rate, are less inclined to bet on reversals, choose risk exposures featuring a higher ratio of nonsystematic risk to total risk, engage in more options trading, and earn lower returns.
The Role of Technical Analysis in Retail Investor Trading
SSRN Electronic Journal, 2015
Technical Analysis (TA) is a security analysis methodology based on the study of past market data. Although it has been criticized by academics and the profitability of many related strategies has been statistically rejected, TA remains highly popular among practitioners and retail investors, in particular. We analyze the role of TA for retail investors trading structured products on Stuttgart Stock Exchange. We find a 35% increase in trading activity on days of chart pattern trading signals and an 11% increase for moving average signals. The increase in activity typically reverses on the following trading days. Furthermore, we identify trading characteristics of round-trip trades and find that trades associated with TA trading signals differ. First, we find significantly higher raw returns in TA-related trades while leverage levels at purchase as well as holding duration appear to be lower. Second, the shape of the realized return distribution of trades in accordance to TA signals is distinct from their peer groups. Specifically, realized returns are significantly less left-skewed (more right-skewed). In this regard, retail investors using TA methods might be less prone to the disposition effect due to the system-based trading approach. If we assume a general gambling intention with respect to the considered products, then TA-related trades tend to reach this goal more effectively.
Re-Examining the Profitability of Technical Analysis with White’s Reality Check
RePEc: Research Papers in Economics, 2004
In this paper, we reexamine the profitability of technical analysis using the Reality Check of White (2000, Econometrica) that corrects the data snooping bias. Comparing to previous studies, we study a more complete "universe" of trading techniques, including not only simple trading rules but also investor's strategies, and we test the profitability of these rules and strategies with four main indices from both relatively mature and young markets. It is found that profitable simple rules and investor's strategies do exist with statistical significance for NASDAQ Composite and Russell 2000 but not for DJIA and S&P 500. Moreover, the best rules for NASDAQ Composite and Russell 2000 outperform the buy-and-hold strategy in most in-and out-of-sample periods, even when transaction costs are taken into account. We also find that investor's strategies are able to improve on the profits of simple rules and may even generate significant profits from unprofitable simple rules.
Profitability and Market Stability: Fundamentals and Technical Trading Rules
2000
Traders endogenously select an information source to maximized expected profits. Those traders selecting to use fundamental information receive a noisy indicator of next period's dividend and construct a portfolio to maximize expected utility. The other option is to employ a technical trading rule. Due to the noise in the fundamental signal, optimal behavior by the fundamental traders creates patterns in the price which can profitably be exploited by the technical trading rule. The technical trading rule performs best when the price is dominated by the fundamental traders. Endogenous swings in the popularity of the technical trading rule can create price bubbles which amplify the movement of the underlying intrinsic value.
Technical analysis, even if deliberated by some as purely conjecture, is still generally acknowledged as additional information to main brokerage companies. There are existent two reasons for the achievement of technical analysis and why its success is still debated: (1) stock return predictability stems from efficient markets that can be analysed by time-varying equilibrium returns, and (2) stock return predictability forms from prices wandering apart from their fundamental valuations. Fundamentally, both explanations show some kind of overall market inefficiency where investors are capable of exploiting. Therefore, technical analysis derived its importance from its ability to train investors to take investment decision based on historical trends of securities prices. To help find answers to the issues raised and to structure the study, the following general research question is set: is it possible for technical analysis to achieve abnormal returns in an Emerging Capital Markets (ECM's) country, more specifically, the Egyptian Stock Exchange? If yes, hence it could be possibly used to help individual investors to take effective investment decision. By means of theoretical and empirical investigation, this study provides significant evidences that technical analysis achieved abnormal returns in inefficiency periods. This study suggests that simple trading rules, more specifically; the simple moving average beat the standard buy-and-hold strategy for the Egyptian stock exchange.
Journal of Economic Integration, 2009
In the aftermath of the Asian financial crisis, a series of reform and liberalization measures have been implemented in Singapore to upgrade its financial markets. This study investigates whether these measures have led to less profitability for those investors who employ technical rules for trading stocks. Our results show that the three trading rules consistently generate higher annual returns for 1988-1996 than those for 1999-2007. Further, they generally perform better than the buy-and-hold (BH) strategy for 1988-1996 but perform no better than the BH strategy for 1999-2007. These findings suggest that the efficiency of the Singapore stock market has been considerably enhanced by the measures implemented after the crisis. JEL CODE: G14; D92
The rise and fall of technical trading rule success
Journal of Banking & Finance, 2014
The purpose of this paper is to examine the performance of an important set of momentum-based technical trading rules (TTRs) applied to all members of the Dow Jones Industrial Average (DJIA) stock index over the period 1928-2012. Using a set of econometric models that permit time-variation in riskadjusted returns to TTR portfolios, the results reveal that profits evolve slowly over time, are confined to particular episodes primarily from the mid-1960s to mid-1980s, and rely on the ability of investors to short-sell stocks. These findings are demonstrated to be consistent with theoretical models that predict a relationship between TTR performance and market conditions. 1 It is quite possible that TTRs provide other functions. For instance, Kavajecz and Odders-White (2004) demonstrate that technical analysis provides useful information regarding liquidity provision relating to the depth of the order book.
Social Science Research Network, 2005
In this paper, we reexamine the profitability of technical analysis using the Reality Check of White (2000, Econometrica) that corrects the data snooping bias. Comparing to previous studies, we study a more complete "universe" of trading techniques, including not only simple trading rules but also investor's strategies, and we test the profitability of these rules and strategies with four main indices from both relatively mature and young markets. It is found that profitable simple rules and investor's strategies do exist with statistical significance for NASDAQ Composite and Russell 2000 but not for DJIA and S&P 500. Moreover, the best rules for NASDAQ Composite and Russell 2000 outperform the buy-and-hold strategy in most in-and out-of-sample periods, even when transaction costs are taken into account. We also find that investor's strategies are able to improve on the profits of simple rules and may even generate significant profits from unprofitable simple rules.
Technical Analysis of the Taiwanese Stock Market
International Journal of Economics and Finance, 2011
We study the profitability of technical trading rules based on 9 popular technical indicators. To further examine whether investors can design technical trading strategies that can beat the buy-and-hold strategy, we establish 13 trading models based on one indicator, 25 models based on two indicators, and 28 models based on three indicators. The empirical results show that 58 out of 66 models reject the null hypothesis of equality of the mean returns between buy days and sell days. Our findings provide support for the predictive power of technical trading rules. Finally we employ Hansen's (2005) Superior Predictive Ability to investigate data snooping problem. Overall we observe an inverse association between the number of technical indicator combinations and trading profitability.
How rewarding is technical analysis? Evidence from Singapore stock market
Applied Financial Economics, 2003
This paper focuses on the role of technical analysis in signalling the timing of stock market entry and exit. We introduce test statistics to test the performance of the most established of the trend followers, the Moving Average, and the most frequently used counter-trend indicator, the Relative Strength Index. Using Singapore data, the results indicate that the indicators can be used to generate significantly positive return. We find that member firms of Singapore Stock Exchange (SES) tend to enjoy substantial profits by applying technical indicators. This could be the reason why most member firms do have their own trading teams that rely heavily on technical analysis.