These are some of the areas in quantitative finance, machine learning, and portfolio optimization that I'm currently researching or thinking about.

  • šŸ¦ Systematic Trading & Statistical Arbitrage - Exploring mean-reversion, momentum, and market inefficiencies.
  • šŸ“ˆ Alpha Discovery & Feature Engineering - Finding new predictive signals and alpha factors.
  • šŸ§  Machine Learning in Trading - Evaluating LLMs for market prediction, reinforcement learning for execution.
  • šŸ›  Portfolio Optimization - Implementing risk-aware allocation methods (conic programming, Kelly Criterion).
  • ā³ Time-Series Forecasting - Studying non-stationary market dynamics, volatility modeling.
  • šŸ” Market Microstructure & Execution Strategies - Analyzing slippage, impact models, order flow dynamics.

šŸ“š Reading List

These are some of the papers, books, and articles Iā€™m reading (or planning to write about).

šŸ“ Research Papers

šŸ“˜ Books

šŸ“ Blog Posts / Articles


āœļø Future Writing

Here are some ideas for papers or blog posts I want to write based on my research:

  • šŸ¦ Does Alpha Decay Differ in High-Frequency vs. Low-Frequency Trading?
  • šŸ“‰ Comparing Market Impact Models in Different Market Regimes
  • šŸ” How to Build a Better Pair Trading Model Using Machine Learning
  • šŸ“Š Backtesting: Hidden Pitfalls in Quant Research
  • šŸŽÆ What Really Works in Feature Selection for Quant Trading?

šŸ”— Want to Discuss?

If any of these topics interest you, feel free to reach out! Always happy to discuss quant research, finance, and trading strategies.