Strategy manager
The module for trading strategies is responsible for implementing and executing automated trading algorithms based on predefined logic and market conditions. This module combines machine learning techniques, particularly boosting algorithms, with the client’s specific trading plan to generate actionable insights and execute trades in real time.
At the core of the module is the strategy itself, represented as a separate class, which encapsulates the trading logic and defines the actions to be taken under various market scenarios. By working with relevant datasets using machine learning, the module identifies and extracts data features to train models that automatically implement the strategies based on current conditions.
The process begins with training the ML models using the selected datasets. These models analyze and process market info, including trading volumes, to detect anomalies and determine optimal entry or exit points for specific assets. Using boosting algorithms, which provide enhanced accuracy, the models generate predictions for asset prices within the shortest possible time intervals, such as milliseconds.
The ML models communicate with the trading system’s backend, where the resulting predictions are stored in a database for further analysis and decision-making. As market data arrives from the exchanges, the models evaluate the conditions against predefined requests and criteria. Based on these evaluations, the models generate predictions that inform buying or selling decisions.
The models continuously learn and adapt to market patterns, improving their predictive capabilities over time. This enables the system to capture price discrepancies across different exchanges promptly, identifying opportunities to sell at higher prices or buy at lower prices.
The module’s architecture is designed to support multiple exchanges offering similar trading tools. Its primary objective is to capitalize on market fluctuations by swiftly identifying favorable trading opportunities. By incorporating trading volume data and ML-driven anomaly detection, the tool enhances the probability of executing trades.
