Machine Learning For Quant Strategies
Machine Learning For Quant Strategies by Surendra Singh
English | June 26, 2024 | ISBN: N/A | ASIN: B0D899GHJ6 | 234 pages | EPUB | 0.35 Mb
English | June 26, 2024 | ISBN: N/A | ASIN: B0D899GHJ6 | 234 pages | EPUB | 0.35 Mb
Unlock the full potential of algorithmic trading with "Algorithmic Trading Mastery: Advanced Quant Strategies with Machine Learning, Time Series Analysis, and Bayesian Statistics." This comprehensive guide is designed for finance professionals, traders, and developers looking to elevate their trading strategies using advanced quantitative methods and state-of-the-art technologies.What You'll Learn
- Algorithmic Trading Foundations: Understand the fundamentals of algorithmic trading, its history, key concepts, and the benefits and challenges it presents.
- Data Preparation and Analysis: Master the importance of high-quality data, data cleaning, preprocessing, and feature engineering to build robust trading models.
- Machine Learning in Finance: Explore supervised, unsupervised, and reinforcement learning techniques and their application in financial markets.
- Advanced Trading Strategies: Delve into momentum strategies, mean reversion, statistical arbitrage, pairs trading, and Kalman filter-based strategies.
- Risk Management and Portfolio Optimization: Learn to manage risk using Value at Risk (VaR), Conditional VaR (CVaR), and optimize portfolios with advanced techniques.
- Deep Learning and AI: Utilize deep learning models, LSTM networks, GANs, and reinforcement learning for developing sophisticated trading algorithms.
- Real-Time Trading Systems: Implement real-time trading systems with a focus on software and hardware requirements, execution algorithms, and real-time risk management.
- Ethics and Compliance: Ensure ethical practices and regulatory compliance in algorithmic trading, and learn from case studies.
- Future Directions: Stay ahead with insights into machine learning and AI trends, quantum computing, and decentralized finance (DeFi).
- 500+ Pages of In-Depth Content: Covering the latest in machine learning-based systematic trading techniques.
- Practical Examples and Code Snippets: Implement advanced quant methods using easy-to-read R and Python code.
- Comprehensive Appendices: Additional resources, Python and R code snippets, and a detailed glossary for quick reference.
- Expert Insights: Authored by Surendra Singh, a finance professional with over two decades of experience in financial technology.