Implementation of the DDPG algorithm for Optimal Finance Trading
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Sep 15, 2019 - Jupyter Notebook
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almgren-chriss
Here are 7 public repositories matching this topic...
monte-carlo monte-carlo-simulation optimal-control bootstrapping-statistics monte-carlo-integration yield-curve optimal-execution almgren-chriss computational-finance financial-engineering monte-carlo-sampling modern-portfolio-theory financial-economics markowitz-portfolio stochastic-optima
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Dec 19, 2019 - MATLAB
DRIP Asset Allocation is a collection of model libraries for MPT framework, Black Litterman Strategy Incorporator, Holdings Constraint, and Transaction Costs.
java drip asset-allocation portfolio-construction optimal-execution drip-asset-allocation black-litterman constrained-portfolio-optimization factor-models idzorek almgren-chriss optimal-transaction transaction-cost optimal-dynamic-portfolio multi-period-portfolio-optimization stochastic-liquidity-volatility market-impact-models principal-program-trades mean-variance-optimization
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Sep 26, 2018 - CSS
Optimal trade execution using the Almgren–Chriss stochastic control framework with illustrative notebooks.Optimal trade execution using the Almgren–Chriss stochastic control framework with illustrative notebooks.Using Stochastic Control especially the Almgren-Chriss framework
python finance trading quantitative-finance quantitative optimal-execution almgren-chriss market-microstructure stochastic-control market-impact
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Oct 9, 2024 - Jupyter Notebook
Portfolio execution strategy based on the Almgren-Chriss model, focusing on trade cost optimization in Python
python quantitative-finance optimal-execution almgren-chriss trading-strategy trade-execution transaction-cost-analysis portfolio-execution
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May 1, 2025 - Jupyter Notebook
Optimal trade execution using Deep Q-Networks (DQN) and PyTorch. Simulates an Almgren-Chriss market environment to outperform TWAP benchmarks.
python machine-learning reinforcement-learning deep-learning pytorch fintech dqn trading-algorithms quantitative-finance algorithmic-trading deep-q-network gymnasium optimal-execution almgren-chriss financial-engineering market-microstructure twap order-execution market-impact
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Jan 15, 2026 - Python
This project implements an advanced trading execution system based on the research paper "A reinforcement learning extension to the Almgren-Chriss framework for optimal trade execution" by Hendricks and Wilcox. The system combines traditional algorithmic trading methods with machine learning to optimize trading performance.
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Nov 4, 2024 - Python
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