Why RL Struggles in Options Trading
Exploring the fundamental challenges of applying reinforcement learning to options markets, from sparse rewards to non-stationary environments.
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NeuroStrike
Experiments, insights, and edge-hunting in the markets.
Building a Multi-Asset Portfolio with Deep Q-Learning
A practical implementation of DQN for portfolio allocation across equities, bonds, and commodities with risk-adjusted returns.
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Market Microstructure Through the Lens of Game Theory
How order book dynamics can be modeled as multi-agent games, and what this reveals about price formation mechanisms.
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The Curse of Dimensionality in Factor Models
Why traditional factor models break down in high-dimensional spaces and how regularization techniques can help.
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Implementing PPO for Crypto Market Making
A deep dive into using Proximal Policy Optimization for automated market making in volatile cryptocurrency markets.
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Signal Decay and Model Degradation
Understanding why quantitative models lose their edge over time and strategies for maintaining alpha in competitive markets.
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