I'm Elvin Zeynalli
Business Analyst · Quantitative Researcher · Automation Engineer
Recent Work
Deep Reinforcement Learning for Hedging
An overview of deep hedging, focusing on how hedging can be framed as a risk-aware sequential decision problem under transaction costs, liquidity constraints, and convex risk measures.
Teaching a Machine to Stock ATMs: Deep Reinforcement Learning for Cash Demand Forecasting
A PhD course project applying the Deep Deterministic Policy Gradient (DDPG) algorithm to ATM cash demand forecasting. The problem is framed as a continuous Markov Decision Process, evaluated against industry benchmarks on the 111-ATM NN5 dataset.
The Application of Hidden Markov Model to Detect BTC Market Regime
A research-oriented overview of how a Gaussian Mixture Hidden Markov Model can be used for BTC regime learning, with focus on theory, structure, and practical limitations.
Optimal Blackjack Strategy Through Dynamic Programming
An analysis of optimal Blackjack strategies using recursive decomposition and dealer probability analysis.