There are four types of technical analysis :
Classical
Advanced
Hybrid
Statistical.
sentiment and behavioral analysis. No matter what branch it is All analysis is ultimately interpreted using the behavioral traits. Each analyst has their own biases and filters. The psychological and behavioral traits are both included in the behavioral traits. Emotional and psychological elements.
Combining classical technical analysis, statistical analysis, sentiment analysis, and behavioral analysis can give traders a comprehensive view of the markets and help them make more informed trading decisions.
Classical technical analysis looks at historical data and identifies patterns that can help traders understand the markets. Statistical analysis uses mathematical models to analyze price data and make predictions by studying different statistical properties. Sentiment analysis focuses on the psychology of market participants and their emotions. Finally, behavioral analysis studies the way market participants react to news, profit and losses, the actions of other market participants, and their own psychological biases. By combining all these forms of analysis, traders can gain a better understanding of the markets and make more informed trading decisions.
The Advantages and Drawbacks of Technical Analysis:
There are many benefits to applying technical analysis to markets:
It can be used across all markets, instruments and timeframes. Prices patterns, oscillators and overlay indicators all get the same treatment. Trades in new markets and timeframes require no new knowledge, unlike fundamental analysis which requires the analyst to be familiar with all details of each stock or market.
It can be used across all markets, instruments and timeframes. Prices patterns, oscillators and overlay indicators all get the same treatment. Trades in new markets and timeframes require no new knowledge, unlike fundamental analysis which requires the analyst to be familiar with all details of each stock or market.
Technical Analysis provides a visual representation of market behavior, as opposed to fundamental analysis which focuses on numerical data.
It gives accurate and timely entry and exit prices. This is preceded by technical signals that indicate potential bearishness or bullishness. It also uses time projection techniques that are not available to fundamentalists, which can pinpoint the potential entry time. Fundamental analysis cannot provide an exact price or time of entry.
It makes it easier to gauge market risk. Volatility is easier to see on charts than in numerical form.
Market participants must work together to identify and respond to clearly defined price triggers on the markets. This creates the conditions for more reliable trades. This is the result of the self-fulfilling prophecy.
There are some drawbacks to applying technical analysis:
Its interpretation is subjective. There are many ways to perceive a certain price pattern. Every bullish interpretation can be interpreted in a different way. This makes it possible for all analyses to have interpretational ambiguity. All interpretations, regardless of their underlying analysis, whether it be behavioral, fundamental or statistical, are subjective in form and content.
Technical analysis assumes that price behavior will repeat. This makes it possible to predict future price actions. Unexpected volatility in markets due to geopolitical, economic or other factors may disrupt this tendency to repeat. New forms of trade execution may cause price patterns to change, such as automated, algorithmic or high-frequency trading, where trades are initiated in markets based upon non-classical patterns. This can affect the repeatability and consistency of classic chart patterns.
Charts are a history of price movements. To recognize classic patterns in price, it takes experience and practice. This skill is easy to master, but it's much harder to forecast or infer future price actions based on past prices. It is essential that the practitioner has a deep understanding of how prices behave in different time frames and markets. While classical patterns can be applied to all markets and timeframes equally well, each market action and every timeframe is unique.
Market action is fundamentally a random walk process. Therefore, technical analysis is useless as chart patterns are created out of pure chance and have no meaning in markets. If this is true, all types of analysis, whether statistical, behavioral, or fundamental, are useless. We know that market action is driven primarily by perception. Therefore, the random-walk process does not accurately reflect market action. Market participants respond in specific and predictable ways. Although there is always some randomness to the markets due to the actions of many market participants not coordinated, it is easy to observe how price reacts and tests at psychologically significant prices. It is difficult to believe that price actions are the result of random buying and selling of market participants, where participants are completely free from cost, biases or emotions.
Strong form of the Efficient market Hypothesis (EMH), which argues that because the markets discount all information price would already adjust to the new information. Any attempt to profit would be futile. The technical analysis of price action would be useless, as passive investment is the only form that allows for market participation. However, such efficiency would require all market participants to react immediately to any new information in a rational way. EMH faces a formidable challenge. It is not possible for a system with disparate parts to react instantly with perfect coordination.
It is therefore safe to conclude that, although absolute market efficiency cannot be achieved, the market adjusts to new information at a lower and less efficient rate of data discounting. Technical analysis is still a valid method of market investigation, until absolute and perfect efficiency is achieved.
Another argument against technical analysis is the idea of the Self‐Fulfilling Prophecy (SFP). Proponents of the concept contend that prices react to technical signals not because the signals themselves are important or significant, but rather because of the concerted effort of market participants acting on those signals that make it work. This may in fact be advantageous to the market participants. The trick is in knowing which technical signals would be supported by a large, concerted action. The logical answer would be to select only the most significantly clear and obvious technical signals and triggers. Of course, one can further argue that such signals, if they appearto be reliable indicators of support and resistance, would begin to attract an increasing number of traders as time passes. This would eventually lead to traders vying with each other for the best and most cost‐effective fills. What seems initially like the concerted action of all market participants now turns into competition with each other. Getting late fills would be costly as well as reduce or wipe out any potential for profit. This naturally results in traders attempting to pre-empt each other for the best fills. Traders start vying for progressively earlier entries as price approaches the targeted entry levels, leading finally to entries that are too distant from the original entry levels, increasing risk and reducing any potential profits. This disruptive feedback cycle eventually erodes the reliability of the signals, as price fails to react at the expected technical levels. Price finally begins to react reliably again at the expected technical levels as traders stop pre-empting each other and abandon or disregard the strategy that produced the signals. The process repeats. Therefore, SFP may result in technical signals evolving in a kind of six‐stage duty cycle, where the effects of SFP may be advantageous and desirable to traders in the early stages but eventually result in forcing traders into untenable positions.