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Technical Analysis in Investing

Authors: Gil Cohen;

Technical Analysis in Investing

Abstract

Technical analysis helps investors to better time their entry and exit from financial asset positions. This methodology relies solely on past information on financial assets price and volumes to predict a financial asset’s future price trend. Modern research has established that combined with other sentiment measures such as social media, it can outperform the standard buy and hold strategy. Moreover, it has been documented that novice and professional investors technical analysis in their investing strategy. An experienced investor should combine fundamental analysis and technical analysis for better trading results. Programmers use technical analysis to create algorithmic trading systems that learn and adapt to the changing trading environments and perform trading accordingly without human involvement. There are hundreds of technical tools offered by known trading platforms. investors must use specific tools that fit their trading style and risk adoption. Moreover, different financial assets such as stocks, exchange trade funds (ETFs), cryptocurrency, futures, and commodities demand different sets of tools. Furthermore, investors should use these tools according to the time frame they use for trading. This paper will discuss different technical tools that are used to help traders of different time frames and different financial assets to achieve better returns over the traditional buy and hold strategy.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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