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Introduction to Machine Learning and AI-Driven Trading Algorithms
- Technical indicators are mathematical calculations based on historical price, volume, or open interest information that traders use to predict future market movements. They are crucial in algorithmic trading, especially when integrated into ML and AI models. By quantifying market trends and patterns, these indicators help in making informed trading decisions.
- This article explores ten fundamental trend indicators and provides Python functions for each. These functions can be organized into a utils.py file for seamless integration into trading algorithms. Technical indicators discussed include: the simple moving average (SMA), exponential moving average (EMA), relative strength index (RSI), moving average convergence divergence (MACD), Bollinger Bands, parabolic SAR, average directional index (ADX), Ichimoku Cloud, Fibonacci retracement, and on-balance volume (OBV).
- The use of modular coding is also highlighted, which enhances code reusability and maintainability, allowing for efficient development and testing of trading strategies.
- Junior coders and traders can begin building sophisticated trading systems by utilizing the functions provided in this article, enabling the analysis of market trends and making data-driven decisions.
- Deploying any trading strategy requires thorough testing and validation to ensure its efficacy and compliance with financial regulations.
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