Technical analysis (TA), or often referred to as mapping, is a type of analysis that aims to predict future market behavior based on past price action and volume data. The TA approach is widely applied to stocks and other assets in traditional financial markets, but is also an integral component of cryptocurrency trading in crypto markets.

In contrast to fundamental analysis (FA) which considers several factors surrounding the price of an asset, TA focuses only on past price action. Therefore, this analysis is used as a tool to observe price fluctuations and volume data for an asset. Most traders use it in an attempt to identify trends and profitable trading opportunities.

While primitive forms of technical analysis emerged in Amsterdam in the 17th century and in Japan in the 18th century, modern TA generally derives from the work of Charles Dow. Dow, a financial journalist and founder of The Wall Street Journal, was one of the first to observe that assets and markets often move in trends that can be segmented and researched. His work later resulted in the Dow Theory which prompted further developments in technical analysis.

In its early stages, the basic approach of technical analysis was based on hand-crafted sheets and manual calculations, but with the advent of modern technology and computing, TA became widespread and is now a tool for most investors and traders.

How does technical analysis work?

As mentioned, TA basically studies the current and previous prices of an asset. The main basic assumption of technical analysis is that price fluctuations of an asset are not random and generally turn into identifiable trends over time.

In essence, TA is an analysis of market demand and supply forces which is a representation of overall market sentiment. In other words, the price of an asset reflects opposing buying and selling forces. This force is closely related to the emotions of traders and investors (in essence, fear and greed).

Please note, TA is considered more reliable and effective in markets operating under normal conditions with high volume and liquidity. Markets with high volume are more resistant to market manipulation and abnormal external influences that can provide false signals and make TA worthless.

To observe prices and ultimately find profitable opportunities, traders utilize a variety of mapping tools called indicators. Technical analysis indicators can help traders identify existing trends as well as provide useful information regarding trends that may emerge in the future. Because TA indicators can be wrong, some traders use several indicators at once to reduce risk.

General TA indicators

Typically, traders using TA apply a wide variety of indicators and metrics to try to determine market trends based on charts and past price action. Among the number of technical analysis indicators that exist, the simple moving average (SMA) is one of the most widely used and well-known examples. As the name suggests, SMA is calculated based on the closing price of an asset within a certain time period. Exponential moving average (EMA) is a modified version of SMA that takes into account recent closing prices rather than previous ones.

Another commonly used indicator is the relative strength index (RSI) which is part of a group of indicators called oscillators. Unlike a simple moving average which only tracks price changes over time, an oscillator applies a mathematical formula to price data, then produces readings that fall within a predetermined range. For RSI itself, this range is from 0 to 100.

The Bollinger Bands (BB) indicator is another type of oscillator that is quite popular among traders. The BB indicator consists of two lateral bands flowing around the moving average line. This indicator is used to track potential overbought and oversold market conditions, as well as to measure market volatility.

Apart from the more basic and simple TA instruments, there are several indicators that rely on other indicators to produce data. For example, Stochastic RSI is calculated by applying a mathematical formula to the regular RSI. Another popular example is the moving average convergence divergence (MACD) indicator. The MACD is generated by subtracting the two EMAs to produce the main line (MACD line). Then, the first line is used to generate another EMA, thus generating the second line (referred to as the signal line). Additionally, there is a MACD histogram that is calculated based on the difference between the two lines.

Trading signals

As well as being useful in identifying general trends, indicators can also be used to provide insight into potential entry and exit points (buy or sell signals). These signals can be generated when certain events occur in the indicator chart. For example, when the RSI produces a reading of 70 or more, this can indicate that the market is operating in an overbought condition. The same logic applies when the RSI drops to 30 or less, which is generally considered a signal of oversold market conditions.

As discussed, the trading signals provided by technical analysis are not always accurate and there is a lot of noise (false signals) generated by the TA indicator. This often gives rise to concerns in the crypto market which is much smaller and more volatile than traditional markets.

criticism

Despite its widespread use in all types of markets, TA is still considered a controversial and unreliable method by experts, and is often referred to as “self-fulfilling forecasting”. The phrase is used to describe events that only happen because a large number of people assume that they will.

Critics argue that, in the context of financial markets, if a large number of traders and investors rely on the same type of indicator, such as a support or resistance line, then the chance of that indicator being effective increases.

On the other hand, most TA supporters argue that each diagram maker has his own way of analyzing diagrams and using available indicators. This implies that it is impossible for a large number of traders to use the same particular strategy.

Fundamental vs. fundamental analysis technical analysis

The main assumption in technical analysis is that market prices already reflect all fundamental factors related to a particular asset. However, in contrast to the TA approach which mainly focuses on past price and volume data (market diagrams), fundamental analysis (FA) adopts a broader research strategy and places more emphasis on qualitative factors.

Fundamental analysis assesses that the future performance of an asset depends on more than just past data. In essence, FA is a method used to estimate the intrinsic value of a company, business, or asset based on a set of micro and macroeconomic conditions, such as company management and reputation, market competition, growth rates, and industry health.

Therefore, we can conclude that, in contrast to TA which is used specifically as a predictive tool for price action and market behavior, FA is a method for determining whether an asset is overvalued based on its context and potential. Technical analysis is applied by most short-term traders, while fundamental analysis tends to be preferred by fund managers and long-term investors.

One of the important advantages of technical analysis is its reliance on quantitative data. Therefore, technical analysis provides a framework for the objective investigation of price history to eliminate assumptions derived from a more qualitative approach to fundamental analysis.

However, despite dealing with empirical data, TA is still influenced by personal bias and subjectivity. For example, a trader who is inclined to reach a particular conclusion about an asset will likely manipulate the TA tool to support his bias and reflect his assumptions. In many cases, this happens without them realizing it. Additionally, technical analysis can also fail when the market does not show a clear pattern or trend.

Closing

Despite criticism and long debates regarding which method is better, the combination of TA and FA approaches is considered by most people to be the more reasonable choice. While FA is usually concerned with long-term investment strategies, TA can provide more useful information on short-term market conditions. This is useful for traders and investors (for example, when trying to determine profitable entry and exit points).