Technical analysis: Take it or skip it?

TA is a tool that uses historical data to forecast a security’s future price movement. (iStockphoto)
TA is a tool that uses historical data to forecast a security’s future price movement. (iStockphoto)


TA is very popular among both rookie investors and market experts, but it has its share of detractors as well.

It has drawn massive interest from both rookie and seasoned investors in the last two to three years. Technical analysis (TA) has sort of become a buzzword in the stock market trading communities. And, ironically, the credit for this goes to finfluencers.

TA—a tool that uses historical data to forecast a security’s future price movement— is not a new concept and is used widely to determine stock selection. Yet, its popularity was fuelled by finfluencers who used random lines and shapes drawn on a price chart to mislead investors into believing that fortunes could be made easily through trading.

TA’s growing fame, though, has sparked an ideological battle. Traditional quants and mathematicians view it with scepticism. They contend that TA lacks a solid scientific foundation, labelling it as pseudoscience. On the other hand, staunch believers in TA argue that its effectiveness transcends scientific rigidity, rooted instead in the understanding of market psychology and the analysis of price patterns.

Its simplicity makes it appealing to most investors. “Even rookies can implement TA strategies from day one, making it accessible to a broader audience. However, it’s worth noting that while TA works well in the cash markets, it may not be as effective in the options markets," said Meraj Inamdar, assistant professor, National Institute of Securities Markets (NISM).

Simplicity, however, is not the only measure of TA’s popularity: The number of experts using TA is growing by the year. For instance, between 2020 and 2022, the number of charters who cleared the Chartered Market Technician (CMT) program crossed the 220 mark, showcasing the growing community of experts in technical analysis.


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Moreover, over 400 individuals successfully cleared CMT level 3, demonstrating their proficiency in applying TA principles effectively. Additionally, the increasing number of individuals taking CMT exams over the past five years, amounting to nearly 2,000, highlights the burgeoning interest in the field.

The TA timeline

During the late 1800s to early 1900s, speculators began observing trends in stock prices and created hand-drawn charts to analyse market movements. These individuals recognized the importance of tracking price patterns and identified the need for a systematic approach to understand market behavior.

Yet,, it was only In 1932 that the Dow Theory was introduced, marking a significant milestone in the development of Technical Analysis (TA). The Dow Theory proposed three key principles: prices discount all available information, prices move in trends, and history tends to repeat itself. This theory laid the foundation for the principles that underpin TA.

“By incorporating TA into models alongside traditional factors, the models can capture a broader spectrum of market dynamics. TA’s short-term triggers, when combined with fundamental analysis, provide a more comprehensive view of market behaviour.” - Sivanath Ramachandran

Despite the emergence of TA, it initially faced skepticism from academia. The ‘random walk hypothesis’ suggested that stock prices followed a random pattern, while the ‘efficient market hypothesis’ claimed that prices already incorporated all available information.

These viewpoints challenged the validity of TA as a reliable approach for predicting price movements.

However, in response to the academic challenges, the CMT Association (formerly known as the Market Technicians Association) was formed. The association aimed to promote TA as a disciplined approach and establish it as a legitimate field of study. This move helped solidify the credibility of TA and fostered its acceptance within the financial industry. TA gained traction during the 1930s, particularly in the foreign exchange and commodity markets. These markets had underlying factors that changed infrequently and lagged behind price movements, making TA a valuable approach. Traders and investors recognized the utility of analyzing price patterns and utilizing technical indicators to predict future market trends.

The late 1990s and early 2000s witnessed significant advancements in trading technology. With the advent of computerized trading and the availability of charting software, TA indicators became readily accessible to market participants. Traders could now utilize a wide range of technical indicators, such as moving averages, oscillators, and trend lines, to analyse price behaviour and make informed trading decisions.

Moreover, during this period, there was a growing trend towards quantifying TA. Hedge funds and quant trading firms began back-testing indicators, integrating momentum directly into trading models, and incorporating TA indicators as features in machine learning-based trading models. In this context, Nalin Moniz, chief investment officer— Edelweiss Alternative Equity, claims that volume and momentum indicators are good for portfolio hedging.

This quantitative approach aimed to enhance the precision and effectiveness of TA in predicting price movements.

In the 2010s and continuing into the present, TA remains widely practiced and influential in financial markets. When asked about how practitioners should look at TA in the current context, Sivanath Ramachandran ,CFA, director, capital markets policy at the CFA Institute, said, “By incorporating TA into models alongside traditional factors, the models can capture a broader spectrum of market dynamics. TA’s short-term triggers, when combined with fundamental analysis, provide a more comprehensive view of market behaviour."

Can patterns be exploited?

TA identifies patterns that exist in financial data and provide insights and potential trading opportunities. But the accuracy of these patterns is subjective and influenced by market psychology and herd mentality.TA patterns are derived from human decision-making and emotions, leading to recurring patterns in price movements. Traders who follow TA attempt to exploit these patterns to predict market direction and make profitable trades. However, its important to note that the accuracy of TA patterns is not foolproof, as market conditions can be influenced by a multitude of factors.

Quants, or quantitative analysts, on the other hand, employ statistical models and algorithms to exploit statistical anomalies in financial data. Unlike TA patterns, statistical anomalies are quantifiable and based on mathematical calculations. Quants seek to identify patterns and inefficiencies in the market through complex statistical analysis and algorithmic trading strategies. They rely on data-driven approaches rather than subjective interpretations.

For instance, the ‘high and tight flag’ pattern shows an average return of 69% and reaches the target price 90% of the time. The ‘rectangle bottom’ pattern has an average return of 46% and reaches the target price 85% of the time. These patterns indicate potential bullish signals.

Among ‘candlestick patterns’, the ‘three line strike pattern’ boasts an impressive accuracy rate of 84% as a bullish reversal pattern. The ‘three black crows’ pattern, a bearish reversal pattern, shows a notable accuracy rate of 78%. These patterns suggest potential trend reversals and have displayed a historical track record of success.

However, its important to note that TA pattern recognition involves subjectivity. Different traders may interpret and identify patterns differently, leading to variations in outcomes.

While the surge in popularity of TA during the covid-19 pandemic has sparked debates and discussions among traders, investors, and academics, it remains open-ended whether TA truly works or whether it is merely a play of probabilities. Ultimately, the decision to utilise TA as part of an investment strategy depends on individual preferences, risk tolerance, and belief in its effectiveness. As market participants continue to explore new avenues and refine trading methodologies, the debate surrounding the efficacy of TA is likely to persist, reflecting the dynamic nature of the financial world.

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