viai957 / Optimal-Portfolio-Transactions
We consider the execution of portfolio transactions with the aim of minimizing a combination of risk and transaction costs arising from permanent and temporary market impact. As an example, assume that you have a certain number of stocks that you want to sell within a given time frame. If you place this sell order directly to the market as it is…
☆36Updated 7 months ago
Alternatives and similar repositories for Optimal-Portfolio-Transactions:
Users that are interested in Optimal-Portfolio-Transactions are comparing it to the libraries listed below
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆69Updated 4 years ago
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆72Updated 3 years ago
- Time Series Prediction of Volume in LOB☆56Updated 10 months ago
- An optimal trading trajectory solver.☆28Updated 3 years ago
- Baruch MFE 2019 Spring☆37Updated 4 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆116Updated last year
- ☆42Updated 5 years ago
- CS7641 Team project☆93Updated 4 years ago
- A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change☆75Updated 6 years ago
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆102Updated 9 months ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆58Updated 11 months ago
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆142Updated 8 months ago
- A financial trading method using machine learning.☆58Updated last year
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆151Updated last month
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆65Updated 5 years ago
- Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio …☆43Updated 2 years ago
- This is a course project of the course « Machine Learning for Finance » at ENSAE ParisTech.☆45Updated 5 years ago
- Machine Learning in Asset Management☆21Updated 5 years ago
- Code for the paper Volatility is (mostly) path-dependent☆59Updated 10 months ago
- Using Dask, a Python framework, I handle 900 million rows of S&P E-mini futures trade tick data directly on a local machine. Through expl…☆37Updated 11 months ago
- Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.☆153Updated 4 years ago
- ☆35Updated 2 years ago
- My Quant Research Papers (incl. Coding & Excel Examples)☆108Updated 3 months ago
- Quantamental finance research with python☆144Updated 2 years ago
- Portfolio optimization with cvxopt☆37Updated 3 weeks ago
- Algo Trading Research & Documentation☆16Updated 8 months ago
- Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM☆52Updated 4 years ago
- Delta hedging under SABR model☆23Updated 9 months ago
- The pricing models and neural network representations used in part one of the paper "Empirical analysis of rough and classical stochastic…☆51Updated 2 years ago
- Neural network local volatility with dupire formula☆75Updated 3 years ago