Technical analysis, a critical aspect of financial market trading, is a forecasting method based on the study of past market data, primarily price and volume, to anticipate future price trends and patterns. It uses statistical trends gathered from trading activity to identify opportunities for investments. This form of analysis has a rich history, stretching back hundreds of years, with an ever-evolving methodology and increasing recognition by various authorities and financial institutions.
The seeds of technical analysis were sown in 17th century Japan with Munehisa Homma, a successful rice trader. Homma developed candlestick charting, a method of plotting price movements over time that provides more information than standard line graphs (Nison, 1991).
However, it was not until Charles Dow’s work in the late 19th and early 20th centuries that technical analysis as we know it began to take shape. Dow’s theories, collectively known as Dow Theory, posited that market prices reflected all available information and, therefore, was the most accurate measure of the intrinsic value of securities. Dow’s principles continue to underpin modern technical analysis (Edwards, Magee, & Bassetti, 2007).
The advent of computer technology in the mid-20th century led to significant advancements in technical analysis. Computerized charting and data analysis made it easier to spot patterns and trends, opening up the field to more traders and analysts. In the 1970s, the development of the efficient market hypothesis (EMH) by Eugene Fama challenged the fundamental basis of technical analysis. EMH asserts that all current prices fully reflect all available information, implying it’s impossible to beat the market consistently (Fama, 1970). However, empirical studies have shown that technical analysis can be profitable, suggesting that markets may not be fully efficient (Lo, Mamaysky, & Wang, 2000).
One of the most significant developments of the last few decades is the emergence of algorithmic trading. High-frequency trading (HFT) algorithms make use of complex technical analysis to make rapid-fire trades, often within fractions of a second.
Recognition of technical analysis has improved significantly over the years. The Chartered Market Technician® (CMT) designation, managed by the CMT Association, has been a significant milestone in this direction. It was established in the 1980s to promote the education of investment professionals in the field of technical analysis and is now recognized by the Financial Industry Regulatory Authority (FINRA) as the leading certification for technical analysis (CMT Association, n.d.).
In addition, the International Federation of Technical Analysts (IFTA) was established in 1986 as a global organization of market analysis societies and associations. IFTA is dedicated to encouraging the highest standards of professional ethics among technical analysts worldwide (IFTA, n.d.).
Technical analysis is now taught at numerous universities and is used by major financial institutions globally. While some critics still favor the efficient market hypothesis, the effectiveness of technical analysis has been widely recognized by many academics, professional traders, and financial institutions.
The evolution of technical analysis, from its nascent days of candlestick charting to today’s complex algorithmic trading systems, is a testament to the enduring power and relevance of this methodology in the ever-changing financial market landscape. As the field continues to advance, with the proliferation of machine learning and artificial intelligence techniques, the future of technical analysis seems bright and promising.
References
- Nison, S. (1991). Japanese Candlestick Charting Techniques. New York: New York Institute of Finance.
- Edwards, R. D., Magee, J., & Bassetti, W. H. C. (2007). Technical Analysis of Stock Trends. CRC Press.
- Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.
- Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705–1765.
- CMT Association. (n.d.). CMT Program. Retrieved from https://cmtassociation.org/program/overview/
- IFTA. (n.d.). About IFTA. Retrieved from https://www.ifta.org/about/
