What is Technical Analysis in Trading?

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I will first start by saying sorry for all the references but this is meant to be a semi academic piece since we are talking theory and I will include my references at the bottom of the page.

The definition of technical analysis

To gain a base knowledge and understanding of TA, the definition of what TA is must first be established. Various authors and academics have given their definition as to what TA implies, and they all have very similar approaches (forecasting future prices).

Achelis (2010) simply defines TA as the study of prices, using charts as the primary tool, to make better investments.

Yamamoto’s (2012, p.3033) definition states;

Technical analysis involves the use of historical market data, such as price, volume, and other observables, to predict future returns in financial assets.”

Murphy’s (1999, p.1) definition of TA is …‘the study of market action, primarily through the use of charts, for the purpose of forecasting future trends’.

technical analysis tradingAchelis (2001) introduces the fact that TA is not an exact science and the results will not be positive on every application.  Technical Analysts study chart patterns and indicators backed by mathematical formulae and mass psychology in order to indicate points in time where the odds may be in their favour. If combined with the correct risk and money management successful trader’s gains can equate to more than their losses.

Murphy (1999), comments on one of the great strengths of technical analysis which is its adaptability to any trading medium or time dimension. He suggests that technicians also known as ‘chartist’ can follow as many different markets at one time and the same principles will apply.

Menkhoff’s (2010) article shows survey results that on average 87% of fund managers use TA to some extent, some more than others. The five countries used in the survey are Germany, USA, China, Italy and Thailand.

The use of backward looking behavior to predict future prices is seen as sceptical as expressed in Fama (1991). However Menkhoff’s article concludes that in the field, practitioners seem to rely on TA in particular to predict short term (daily and weekly) price behavior and trends.

some say markets are completely random

Murphy (1999), comments on the ‘Random Walk Theory’ or Efficient Market Hypothesis. He agrees that there is a level of randomness that exists in all markets. However, it is not realistic to believe that price movement as a whole is completely random. His idea is that this may be an area where actual experience in the field may prove to be of more use than sophisticated statistical tests.

The profitability of Technical Analysis has been questioned under the basis that there is a data snooping bias. This means previous data is looked so closely into and only the chunks of data that fit the models are used to prove its worth, so on the whole it may not be as profitable.

The data snooping bias is considered and tested by Yen & Hsu (2010). Technical Analysis is applied to ten futures markets and performance is compared with the benchmark ‘buy and hold’ strategy that a lot of fundamentalists use. The tests were conducted in both bullish and bearish markets.

and the result are…..!?

winning with technical analysis

Tests reveal persistent out performance by Technical Analysis relative to the ‘buy and hold’ strategy in eight of the ten markets. The article suggests that in futures markets most of the fund managers are using Technical Analysis and models based on behaviour as oppose to looking at the fundamentals. In the article a quote is taken from Sol Waksman, president of Barclays Trading Group, the quote reads;

“It’s a systematic approach, and the systems are designed to profit when the futures products move through certain designated levels”.

No surprise there

Now references and academic stuff aside, I will give my view on why technical analysis is so effective. TA basically helps you to identify points in time where the odds are in favor of the market going in one direction or another. The market is no longer “Random”.

A very basic example;

At key a point of previous resistance or support there is over a 50% chance that the market will make some kind of turn around, whether it be a major or minor one before continuing. For all the gamblers out there, we all know that anything over 50% in the long run becomes profitable. Market participators see these key zones and place their trades accordingly, hence creating  sort of self fulfilling prophecy. If enough people decide to sell the market at a certain area, then prices will inevitably fall. In reverse, if enough people decide to buy at a certain price, demand will rise and so will the price.

Clearly there are a lot more factors to look at and its not as simple as going with anything over 50% without looking at our own risk levels and fee’s incurred placing trades.

This also doesn’t mean that I believe every indicator has this power of becoming a self fulfilling prophesy either. The above example mainly explains the price action aspect of Technical Analysis like support, resistance and Fibonacci numbers. Some people use complex indicators very well in TA. I myself only use price action and moving averages.


Achelis, S.B. (2010). Technical Analysis from A – Z. New York : McGraw Hill 2nd ed. Retrieved 05/11/2013 from http://web.ebscohost.com

Menkhoff, L. (2010). Journal of Banking & Finance. The use of technical analysis by fund managers: International evidence. 34(11), p.2573 – 2586. Retrieved 05/11/2013 from http://www.sciencedirect.com/science/article/pii/S0378426610001755

Murphy, J. (1999). Technical analysis of the financial markets. A comprehensive guide to trading methods and applications. New York: New York Institute of Finance.

Yamamoto, R. (2012). Journal of Banking & Finance. Intraday technical analysis of individual stocks on the Tokyo Stock Exchange, 36(11), p.3033 – 3047.

Xue.Y. Zhang, M.H. (2011) Journal of Business Finance and Accounting. Fundamental Analysis, Institutional Investment, and Limits to Arbitrage, 38(9) and (10), p.1156 – 1183




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