The Strategist

What is technical analysis?

Technical analysis is a method that uses price data and charts to decipher market dynamics and predict market movements. This approach stems from an investment philosophy distinctly different from that of fundamental analysis, yet in practice, they are not entirely exclusive. Technical analysis is widely prevalent in financial markets, primarily as a tool for market timing. With the advent of machine learning and artificial intelligence revitalising the industry, traditional candlesticks are being infused with new potential.

Date: 14 February 2024
Author: Ming Deng, Quantitative Analyst, LGT Private Banking
Reading time: 10 minutes

The Strategist Technical Analysis — © Shutterstock

Technical analysis has a long history in the investment world, dating back at least to the 18th century when the Japanese rice merchant Honma Munehisa introduced the candlestick chart. In general, technical analysts try to study patterns in past price and volume data to understand the supply and demand dynamics of the underlying asset, with the aim of predicting future price developments and making profitable investment decisions. Depending on the implementation, investors may rely directly on price charts, or transform information from the charts into numerical signals and apply heuristic rules to formulate trading strategies.

Technical analysis vs. fundamental analysis: Astrology vs. astronomy?

In the investment world, there is a saying that sometimes compares technical analysis to fundamental analysis, much as astrology is compared to astronomy. This analogy may stem from the fact that fundamental analysis relies on a thorough analysis of the economic fundamentals of the underlying asset to make investment decisions, which seems to offer more substantial merits. Fundamental analysis offers intuitive explanations of the drivers of asset prices, a philosophy that dates back to the renowned value investing guru Benjamin Graham in his book 'Security Analysis' (1934)[1].

The differences really lie in the logic of the investment philosophy and the beliefs or assumptions about the market. Ultimately, if we consider the task of predicting asset returns as a statistical exercise, the major distinctions lie in the data used and the predictive models employed. Fundamental analysts focus on economic factors, including both the macroeconomic environment and the micro characteristics of the underlying assets. Conversely, technical analysts assume that market prices aggregate all relevant information, rendering other data redundant. However, these two approaches should be seen as complementary rather than mutually exclusive, especially when considering the frequency of data availability and its implications for prediction horizons. As Menkhoff and Taylor (2007)[2] point out in their review of technical analysis in foreign exchange markets, technical analysis could be used to capture non-fundamental price drivers, which are more significant in the short run.

Trend following and mean reversion: Why would they work from a theoretical point of view?

Trend following and mean reversion are two groups of technical strategies that are widely used in practice. Trend following strategies attempt to identify the current market trend and invest in the same direction until the trend ceases. Common signals used in trend following include moving average crossovers and time series momentum. On the other hand, mean reversion strategies focus on the idea that asset prices cannot deviate from their fundamental values forever and will eventually revert to their true value. These strategies aim to identify when the underlying asset is overbought or oversold, and capture the turning points where market reversion is likely to occur. Common examples include the Relative Strength Index (RSI) and the stochastic oscillator.

Why might technical analysis work? An efficient market would suggest that there is no predictability in technical analysis, as all information is already priced in and future prices would follow a random walk. However, it may be too optimistic to assume that the market is able to price in all information instantaneously. Under-reaction to news that attracts less attention from investors and over-reaction to information that is highly visible and aligns with investor sentiment are widely observed in financial markets, leaving room for momentum and mean reversion strategies to be profitable. Additional behavioural effects such as the herding effect, where investors follow similar technical trading rules, can create a self-fulfilling prophecy where the price moves in the predicted direction merely due to the collective actions of technical analysts.

A backtesting example of a simple moving average crossover strategy

Now let’s look at an investment strategy based on trend following for the S&P 500 index to assess if technical analysis can be beneficial in timing the market. This strategy compares the current end-of-month stock prices with the simple moving average of the past ten months. If the current month's price is above the ten-month average, a long position in the index is taken; otherwise, the position is sold and moved to cash.

Looking at the sample from January 1990 to December 2023, the annualised returns of the S&P 500 (SPX) and the trend-following strategy yield similar returns, at 10.4% and 10.2% per annum, respectively. However, the volatility of the technical analysis strategy decreases to 11.3%, compared to the buy-and-hold strategy's 14.9%. Most notably, in terms of downside risk, the timing strategy has a maximum drawdown of 19.6%, compared to the S&P 500's 50.9%. Further analysis shows that the trend-following strategy avoids many of the drawdowns of the buy-and-hold strategy during turbulent periods without triggering many buy and sell signals. In fact, the average holding period is 398 days. Overall, this simple trend following example demonstrates how technical analysis can help to improve the performance of a simple buy-and-hold strategy by avoiding major drawdowns.

Stylised facts about technical analysis: Its use and profitability in financial markets

Do investors use technical analysis? Among practitioners, technical analysis is widely employed in the stock market, foreign exchange market, and futures markets. This has been corroborated by academic studies and professional investors’ survey.

How profitable is technical analysis used empirically? The effectiveness of technical analysis has been a subject of extensive discussion in the academic finance community. Most research provides positive evidence supporting the predictability of technical analysis.

Are all markets and methods equal? Technical analysis seems to work best for stock markets and foreign exchange markets, although it depends on which technique is used and for what time horizon. Trend-following methods seem to yield the best results, while shorter time horizons seem to be better suited than longer ones.

Future Trend: When technical analysis meets machine learning

Machine learning is revolutionising various industries, and the field of technical analysis for investors is no exception. Recent advancements have significantly improved the performance of machine learning approaches in recognising features in both images and numerical time series. While traditional economic theory assumes that asset prices reflect all available information, new machine learning techniques seem to suggest that this is not the case. As such, they offer valuable insights for the future of the industry, particularly in terms of improving price discovery and market efficiency.

References

[1] Benjamin Graham, David L. Dodd. Security analysis: Principles and technique. McGraw-Hill, 1934.

[2] Menkhoff, Lukas, and Mark P. Taylor. "The obstinate passion of foreign exchange professionals: technical analysis." Journal of Economic Literature 45, no. 4 (2007): 936-972.

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