The concept of trading has existed for quite some time. It involves the buying and selling of securities, currencies, electronic coins, or various goods in large volumes. This industry is continually evolving, with new promising directions emerging.
Sergey Tereshkin, the founder of "Oil Resource Group," will elaborate on these developments. He possesses extensive knowledge and experience in the trading sector.
New and Promising Directions
Some of the most modern and promising directions in trading include:
- the use of trading robots;
- behavioral trading;
- application of neural network capabilities;
- cluster analysis.
Each of these directions warrants a more detailed discussion.
Trading Robots
Recently, the so-called "trading robots" have emerged. These are automated systems used for trading without human involvement. The robot independently executes buy or sell orders based on predefined algorithms and rules.
The software analyzes the market, places buy or sell orders, monitors positions, and so forth.
This technology is actively utilized in many countries around the world and demonstrates reliable results. The advantages of trading robots include:
- Speed. A robot can simultaneously perform various operations and work with any number of financial instruments. A human, on the other hand, cannot physically execute multiple actions at once.
- Accuracy. With properly written code, a robot does not make errors in its operations. It precisely calculates trading positions.
- Lack of emotions. Humans often make incorrect decisions under the influence of emotional highs, stress, fatigue, depression, and other factors; robots do not suffer from this flaw. They do not need sleep or food, and they do not experience headaches. They can work around the clock.
- Progress. Software can be upgraded to optimize processes and, consequently, improve the trading robot's performance. In this case, the possibilities for enhancement are limited only by the skill level of the programmer.
Despite these visible advantages, any software has its drawbacks. The primary concern is analysis. Robots cannot read news and therefore cannot respond quickly to unexpected market fluctuations.
Additionally, for a trading robot to function effectively, a skilled specialist is required—not just someone who knows how to write code, but also someone who can develop trading strategies.
It is crucial to understand that software executes logical processes as defined by the author. In the event of significant market changes, the robot needs further programming and modifications to adapt to the current situation. This necessitates hiring a programmer who will require time to understand the existing code, or alternatively, keeping a specialist on staff who was involved in the initial development, although this can also be costly.
Behavioral Trading
A relatively new concept in the trading market is behavioral trading. It is based on the psychological aspects of how situations in the market are perceived and the trading processes. This involves a thorough analysis of not only the technical aspects but also of human behavior.
Leading traders have long understood that mathematical analysis alone is insufficient for obtaining a comprehensive picture and predicting market fluctuations. It is far more effective to additionally utilize behavioral factors. It has been observed that similar reactions from market participants to various situations lead to the repetition of market formations. Thus, behavioral trading allows for high accuracy in anticipating developments in specific situations, identifying patterns, and utilizing them effectively.
The combination of multiple approaches yields outstanding results in trading. As a result, a unique symbiosis of effective management and psychology emerges. This opens new horizons and possibilities for traders to generate income.
Neural Network Capabilities
Artificial intelligence is actively applied in various fields, including trading. Its capabilities are virtually unlimited. Neural networks minimize human intervention in the trading process. They function similarly to robots; however, the key difference is that neural networks possess the ability to learn. Robots operate solely based on the code developed by programmers and do not have self-improvement capabilities.
Neural networks can analyze not only current market movements but also nearly any dataset. This allows for the integration of fundamental information with technical analysis.
Neural networks are capable of processing vast amounts of incoming data simultaneously, learning, and quickly adapting to any market fluctuations. Unlike trading robots, neural networks do not require programmers to restructure them for new conditions.
Cluster Analysis
One effective method for market analysis is cluster analysis. It is a highly accurate price forecasting technique based on trading volumes.
This involves detailed analysis over a specified period during which homogeneous transactions—either buying or selling—occur. As a result of compiling data, clusters form around total trading volumes at which transactions were executed at a particular price. This allows traders to predict market movements with a high degree of probability.
To facilitate this process, charts are constructed. This informative approach allows for the visual representation of trends.
Modern and popular directions in trading can be utilized in conjunction, ensuring maximum results and helping to mitigate significant financial losses regardless of market changes and their nature.
