Technical analysis (TA), or charting, is a type of analysis aimed at predicting future market behavior based on historical price movement and volume data. AT is most often applied to stocks and other assets in traditional financial markets, but can be used in cryptocurrency trading.

Unlike fundamental analysis (FA), which considers multiple factors to predict the price of an asset, TA focuses strictly on historical price movements. It is therefore used as a tool to examine price fluctuations and volume data. Many traders use it to try to identify the most profitable trends and opportunities.

While the most primitive forms of technical analysis emerged in 17th century Amsterdam and 17th century Japan, modern TA is often associated with Charles Dow. Dow is a financial journalist and founder of Wallet Street Journal. He was one of the first to observe that assets and markets often move in patterns that can be segmented and examined. His work gave rise to the Dow Theory, a theory that encouraged the development of AT.

In its infancy, the rudimentary approach to technical analysis was based on handmade sheets and manual calculations. With the advancement of technology and the birth of modern computing, AT has become widespread and is today an important tool for many investors and traders.

How does technical analysis work?

As mentioned earlier, TA is the study of the current and previous prices of an asset. The premise of technical analysis is that fluctuations in the price of an asset are not random and evolve into identifiable trends over time.

TA is the analysis of market forces of supply and demand and represents general market sentiment. In other words, the price of an asset reflects the forces of selling and buying, with these forces being closely linked to the emotions of traders and investors (primarily fear and greed).

It should be noted that AT is considered more reliable and efficient in markets operating under normal conditions, with high volume and liquidity. Markets with a significant volume are in fact less sensitive to price manipulation and abnormal external influences which could render the AT obsolete.

In order to examine prices and possibly spot favorable opportunities, traders use a variety of charting tools known as indicators. Technical analysis indicators can help traders identify existing trends and provide insightful information about trends that may emerge in the future. Since AT indicators are not 100% reliable, some traders use multiple indicators to reduce risk.

Most common indicators in AT

Traders using AT employ different indicators and metrics to attempt to guess market trends, based on charts and historical price movements. Among the many technical analysis indicators, simple moving averages (SMA) are one of the most used and well-known examples. As the name suggests, SMA is calculated based on an asset's closing prices during a given period. The exponential moving average (EMA) is a modified version of the SMA weighting recent closing prices more than older ones.

Another commonly used indicator is the Relative Strength Index (RSI), an indicator that is part of a class of indicators known as oscillators. Unlike simple moving averages that simply track price changes over time, oscillators apply mathematical formulas to pricing data and then produce measurements that fall within predefined ranges. In the case of RSI, the interval is [0;100].

Bollinger Bands (BB) are another type of oscillator that is very popular among traders. The BB indicator consists of two sidebands wrapping around a moving average line. It is used to identify periods of overbought or oversold and to measure market volatility.

In addition to basic TA instruments, there are also indicators that rely on other indicators to generate data. For example, the stochastic RSI is calculated by applying a mathematical formula to the standard RSI. Another popular example is the Moving Average Convergence Divergence (MACD) indicator. The MACD is obtained by subtracting two EMAs to create the main line (the MACD line). The first line is used to generate a new EMA, generating a second line (the signal line). There is also a MACD histogram calculated based on the differences between the two lines.

Trading Signals

Although indicators can be useful for identifying general trends, they can also be used to provide entry and exit points (buy or sell signals). These signals can be generated when specific events occur in an indicator's chart. For example, when the RSI produces a reading of 70 or higher, it may suggest that the market is overbought. Conversely, if the RSI is below 30, the market may be oversold.

As we discussed previously, trading signals provided by technical analysis are not always accurate and there is a considerable amount of noise (false signals) produced by AT indicators. This is especially true in cryptocurrency markets, which are much smaller than traditional markets and therefore more volatile.

Critiques

Although it is widely used in all kinds of markets, TA is considered by many scholars to be an unreliable method, or even a “self-fulfilling prophecy.” This term means that events only happen because a large number of people assume they should happen.

Critics argue that, in the context of financial markets, if a large number of traders and investors rely on the same types of indicators, such as support or resistance lines, the chances of those indicators working increase. .

The defenders of the AT assert for their part that each chartist has his own way of analyzing the curves and his favorite indicators. Thus, it is virtually impossible for a large number of traders to use the same strategy.

Fundamental analysis or technical analysis.

The premise of technical analysis is that market prices already reflect all fundamental factors related to a particular asset. Unlike TA which relies on historical price and volume data (market charts), fundamental analysis (FA) adopts a broader investigative strategy emphasizing qualitative factors.

Fundamental analysis indeed considers that the future performance of an asset goes well beyond its historical data. FA is a method designed to estimate the intrinsic value of a company, activity or asset through a wide range of micro and macroeconomic tools, such as company management and reputation, its competitors, its growth rate and the health of its sector.

Therefore, we can consider that unlike AT which is mainly used as a tool for predicting price movement and market behavior, FA is a method to determine whether an asset is overvalued or not, based on of its context and its potential. If technical analysis is mainly used by short-term traders, fundamental analysis is preferred by fund managers and long-term investors.

One of the advantages of technical analysis is that it is based on quantitative data. As such, it provides a framework for an objective study of price history, removing some of the guesswork that comes with the more qualitative approach to fundamental analysis.

However, although this is empirical data, AT is still influenced by personal bias and subjectivity. A trader who is strongly predisposed to draw a certain conclusion about an asset will likely be able to manipulate their TA tools to agree with them, without even being aware of it. Additionally, technical analysis can also fail during periods when markets do not exhibit a clear pattern or trend.

To conclude

Aside from criticism and the long-standing controversial debate over which method is best, a combination of the AT and AF approaches is considered by many to be a more rational choice. While AF generally concerns long-term investment strategies, TA can provide relevant information about short-term market conditions, which can be useful to both traders and investors (e.g. when trying to determine favorable entry and exit points).