Technical market indicators: An overview

Abstract

a b s t r a c tCurrent evidence on the predictability of technical analysis largely concentrates on pricebased technical indicators such as moving averages rules and trading range breakout rules. In contrast, the predictability of widely used technical market indicators such as advance/decline lines, volatility indices, and short-term trading indices has drawn limited attention. Although some market indicators have also become popular sentiment proxies in the behavioral finance field to predict returns, the results generally rely on using just one or a few indicators at a time. This approach raises the risk of data snooping, since so many proxies are proposed. We review and examine the profitability of a wide range of 93 market indicators. We give these technical market indicators the benefit of the doubt, but even then we find little evidence that they predict stock market returns. This conclusion continuously holds even if we allow predictability to be state dependent on business cycles or sentiment regimes.

Are technical indicators helpful to investors in china’s stock market? A study based on some distribution forecast models and their combinations

“…This is far inferior to financial information. Fang et al (2014) studied the profitability of 93 market indicators and found no evidence that they could predict the stock market returns. Naz ario et al (2017) classified and coded the technical analysis documents of the past 55 years, focusing on the stock analysis.…”

“…They found that the research results 'supporting technical analysis' and 'not supporting technical analysis' account for almost equal proportions. A more detailed overview of the technical analysis can be found in Bustos and Pomares-Quimbaya (2020), Fang et al (2014), Gandhmal andKumar (2019), andNaz ario et al (2017). This is where the role and influence of the stock markets' TIs are systematically reviewed.…”

Profitability of Technical Trading Rules in the Brazilian Stock Market

“…The second family is the Trading Range Break (TRB) or support and resistance rule which generates a buy (sell) signal when the price rises above (falls below) the resistance (support) level, which refers to the highest (lowest) over the k most recent days. That technique has also widely been used in the previous empirical evidence with different results; see Bessembinder and Chan (1995), Hudson et al (1996), Shynkevich (2012), Yu et al (2013) and Fang et al (2014) among others.…”

Testing the Predicting Ability of Technical Analysis Classical Patterns in the Egyptian Stock Market

“…It is being used now heavily by fund managers in most countries including the United states and is an important investment decision-making tool for short term traders. Technical Analysis has been defined in the literature as a science in terms of recording historical price changes in graphical form, and has been defined also as an art in terms of its great talent in discovering and identifying trend in an early stage letting traders and investors join the trend at the beginning and hold until an evidence for reversing the current trend (Pring 2002, P.3;Edward;Magee & Bassetti 2006, P.4;Fang;Qin and Jacobsen 2014;Shynkevich 2016).…”

“…It was believed that chart reading is of no real value to the stock market investors and traders (Bessembinder and Chan, 1995). Fang et al (2014); Fama and Blume (1966) and Jensen and Bennington (1970);Fama (1965Fama ( , 1970 However, a growing body of literature has been recognized recently that technical analysis could generate abnormal returns. For example (Zapranis & Tsinaslanidis 2012;Cervello-Royo;Guijarro & Michniuk 2015) for classical price patterns, (Marshall & Cahan 2005;Gustafsson 2012;Ülkü & Prodan 2013;Boboc & Dinică 2013;Baetje & Menkhoff 2016;Chen;Su & Lin 2016;El-Ansary & Atuea 2017) for technical indicators and (Brock;Lakonishok & LeBaron 1992;Bessembinder & Chan 1995) for both technical patterns and indicators.…”