Technical analysis (TA), often referred to as “chartism,” is a type of analysis focused on predicting future market behavior based on price actions and previous volume data. The AT approach is applied extensively to securities and other assets in traditional financial markets, but is also an integral component of digital currency trading in the cryptocurrency market.

Unlike fundamental analysis (FA), which takes into consideration multiple factors surrounding the price of an asset, AT focuses exclusively on the history of price actions. For this reason, it is used as a tool to examine the price fluctuations and volume data of an asset, and many traders employ it in an attempt to identify trends and favorable trading opportunities.

Although early forms of technical analysis appeared during the 17th century in Amsterdam and 18th century in Japan, modern TA is often linked to the works of Charles Dow. A financial journalist and founder of The Wall Street Journal, Dow was one of the first to observe that individual assets and markets often move by trends that can be segmented and examined. His work would later give birth to the Dow Theory, which would encourage new developments in the field of technical analysis.

In the initial stages, the rudimentary approach to technical analysis was based on hand-made chips and manual calculations; But with the advancement of technology and modern computing, AT became widespread, to the point of currently becoming an important tool for many investors and traders.


How does technical analysis work?

As already mentioned, AT is basically the study of the current and previous prices of an asset. The main hypothesis on which technical analysis is based is that the price fluctuations of an asset are not random, but generally evolve into identifiable trends over time.

In essence, AT is the analysis of the forces of supply and demand in the market, which are a representation of the general sentiment of the market. In other words, the price of an asset is the reflection of the opposition of buying and selling forces, closely related to the emotions of traders and investors (essentially fear and greed).

It should be noted that AT is considered more reliable and effective in markets that operate under normal conditions - that is, with high volume and liquidity. High volume markets are less exposed to price manipulation and abnormal external influences that could create false signals - which would make the AT a useless tool.

To examine prices and eventually identify favorable opportunities, traders use various charting tools called indicators. Technical analysis indicators can help traders identify existing trends, as well as provide relevant information on trends that may emerge in the future. Since AT indicators are not foolproof, some traders use combinations of them to reduce risk.


Common AT Indicators

Typically, traders who rely on AT use different indicators and metrics to try to determine market trends based on charts and the history of price actions. Among the numerous technical analysis indicators, simple moving averages (SMA) are one of the most used and well-known examples. As the name suggests, the SMA is calculated based on the closing prices of an asset over a given period of time. The exponential moving average (EMA) is a modified version of the SMA, which weights recent closing prices more heavily than old ones.

Another commonly used indicator is the Relative Strength Index (RSI), which is part of a category of indicators known as oscillators. Unlike moving averages, which simply track price changes over time, oscillators apply mathematical formulas to price data and then produce readings that will fall within predefined ranges. In the case of the RSI, this range covers 0 to 100.

Bollinger Bands (BB) are another oscillator-type indicator that is quite popular among traders. The BB indicator consists of two side bands that fluctuate around a moving average line. It is used to identify potential “overbought” or “oversold” market conditions, as well as to measure market volatility.

In addition to the most basic and simple TA instruments, there are other indicators that, in turn, depend on other indicators to generate data. For example, the Stochastic RSI is calculated by applying a mathematical formula to the regular RSI. Another popular example among indicators is the moving average convergence/divergence (MACD). The MACD is generated by subtracting two EMAs, which results in a main line (the MACD line). The first line is then used to generate another EMA, which gives rise to a second line (known as the signal line). Likewise, we also have the MACD histogram, which is calculated based on the differences between both lines.


Trading signals

Although indicators are useful for identifying general trends, they can also be used to provide clues to potential entry and exit points (i.e. buy or sell signals). These signals can be generated when specific events occur on an indicator's chart. For example, when the RSI produces a reading of 70 or higher, it may suggest that the market is operating under “overbought” conditions. The same logic applies when the RSI drops to 30 or below, which is generally perceived as a sign that “oversold” conditions exist in the market.

As explained above, the trading signals provided by technical analysis are not always accurate, and there is also a considerable amount of noise (false signals) produced by AT indicators. This is especially worrying in relation to cryptocurrency markets, as they are much smaller than traditional ones and therefore more volatile.


Reviews

Despite being widely used in all types of markets, the AT is considered a controversial and unreliable method by many specialists, which is why it is often called a “self-fulfilling prophecy” - a concept used to describe those events that only have place because a large number of people assume that they will 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 and resistance lines - the probability of these indicators responding correctly decreases. sees increased.

On the other hand, many defenders of AT argue that each chartist has his own particular way of analyzing charts and using the various indicators available, which means that it is virtually impossible for a large number of traders to use the same strategy.


Fundamental vs. fundamental analysis technical analysis

A central premise of technical analysis is that market prices already reflect all the fundamental factors related to a specific asset. But unlike the AT approach, which mainly focuses on historical price and volume data (market charts), fundamental analysis (FA) adopts a broader research strategy that places greater emphasis on qualitative factors.

Fundamental analysis considers that the future performance of an asset depends on many things and not just historical data. In essence, AF is a method used to estimate the intrinsic value of a company, business or asset, based on a wide range of micro and macroeconomic conditions - such as company management and reputation, market competition, investment rates. growth and health of the sector.

Therefore, we can consider that unlike AT, which is mainly used as a predictive tool for price action and market behavior, AF is a method to determine whether an asset is overvalued or not, according to its context and potential. While technical analysis is mostly used by short-term traders, fundamental analysis is usually preferred by fund managers and long-term investors.

A notable advantage of technical analysis is the fact that it is based on quantitative data. As such, it provides a framework for an objective investigation of price history, eliminating some of the guesswork that accompanies the more qualitative approach to fundamental analysis.

However, despite dealing with empirical data, TA is influenced by personal biases and subjectivities. For example, a trader who is strongly inclined to reach a certain conclusion regarding an asset will likely be able to manipulate his AT tools to support his biases and reflect his preconceptions - which, in many cases, occurs without him being aware of it. it. Furthermore, technical analysis can also fail in periods when markets do not present clear patterns or trends.


Final thoughts

Beyond the criticism and the traditional controversy regarding which method is better, a combination that includes both AT and FA approaches is considered by many to be the most rational choice. While AF is often linked to long-term investment strategies; The AT can provide relevant information regarding short-term market conditions, which can be useful to both traders and investors (for example, when trying to determine favorable entry and exit points).