Skip to content
← All Tags

# Python

11 posts

Building Portafel: A Research Terminal for 10,800 Instruments

5 min read Automation Featured

Portafel covers ~10,800 stocks, ETFs, indices, commodities, FX pairs and crypto, turning company news into a personal briefing with filings, financials and price history alongside it. Here is how it is built and what was harder than expected.

Software EngineeringFinancial DataNLPFinBERTPostgreSQL

The Stop Loss Was the Expensive Part: Backtesting Polymarket's 15-Minute BTC Markets

7 min read Quant Research Featured

Four ways a prediction-market backtest quietly lies to you, the recorder built to avoid them, and one clear finding: adding a stop loss made every variant of the strategy worse without changing which side was right.

Quant TradingPrediction MarketsBacktestingMarket MicrostructurePython

Teaching a Machine to Stock ATMs: Deep Reinforcement Learning for Cash Demand Forecasting

12 min read Quant Research

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.

Reinforcement LearningDeep LearningTime Series ForecastingDDPGActor-Critic

The Application of Hidden Markov Model to Detect BTC Market Regime

4 min read Quant Research

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.

Quant TradingHidden Markov ModelsMachine LearningBinancePython

Optimal Blackjack Strategy Through Dynamic Programming

12 min read Automation

An analysis of optimal Blackjack strategies using recursive decomposition and dealer probability analysis.

Dynamic ProgrammingAlgorithmsBlackjackPython

Learning Optimal Pricing with Reinforcement Learning

6 min read Quant Research Featured

A technical implementation of the Actor-Critic algorithm to solve dynamic pricing. This project benchmarks RL against theoretical optima to test its effectiveness in combinatorial optimization.

Reinforcement LearningMachine LearningActor-CriticDynamic PricingCombinatorial Optimization
1 / 2 Next →
© 2026 Elvin Zeynalli. All rights reserved.