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Advances in Momentum Trading Strategies

Delve Deep into the World of Advanced Momentum Trading

Advances in Momentum Trading Strategies is a comprehensive and in-depth course designed for graduate-level students and seasoned professionals. This course offers a unique blend of theory, practical application, and cutting-edge research, enabling participants to master the intricacies of momentum trading across various market conditions.

What you’ll learn

Course Content

Requirements

Advances in Momentum Trading Strategies is a comprehensive and in-depth course designed for graduate-level students and seasoned professionals. This course offers a unique blend of theory, practical application, and cutting-edge research, enabling participants to master the intricacies of momentum trading across various market conditions.

Course Sections:

  1. A Century of Evidence on Trend-Following Investing: Explore the historical performance and methodology of trend-following strategies over a century, including during crises and different economic environments.
  2. Momentum Turning Points: Unravel the concept of turning points in momentum trading. Learn about dynamic versus static strategies, and the impact of noise and persistence on signal quality.
  3. Trending Fast and Slow: Delve into the theory and application of varying speed (window periods) in trend analysis. Discover the role of risk management and the statistics of S&P 500 in momentum strategies.
  4. Position Sizing: Volatility Targeting: Understand the impact of volatility targeting on position sizing across asset classes, and why this approach is effective.
  5. Deep Momentum Networks (Time Series Momentum Strategies): Learn about enhancing time-series momentum strategies using deep neural networks, including the construction of trading signals and performance evaluation.
  6. Advanced Deep Momentum Networks with Change Point Detection: Explore the integration of change point detection in deep momentum networks, examining methodology and results.
  7. Cross-Sectional Momentum Strategies with Learning to Rank: Gain insights into building cross-sectional systematic strategies using Learning to Rank (LTR), including Python library implementation for LambdaMart.
  8. Market Conditions that Favor Strategies: Analyze various investment strategies like carry, momentum, and value in different market conditions. Learn about signal and portfolio construction.
  9. Enhancing Cross-Sectional Strategies by Context-Aware LTR with Self-Attention: Understand how to enhance ranking in cross-sectional momentum strategies using context-aware models and transformer architecture.

Why This Course?

Whether you’re a graduate student specializing in financial engineering, machine learning, applied mathematics, or a professional quant trader or analyst, this course will elevate your understanding and application of momentum trading strategies. It’s not just a course; it’s an investment in your future in the dynamic world of trading.