hansbuehler / deephedgingLinks
Implementation of the vanilla Deep Hedging engine
☆310Updated 2 years ago
Alternatives and similar repositories for deephedging
Users that are interested in deephedging are comparing it to the libraries listed below
Sorting:
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆199Updated last week
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆213Updated last year
- A collection of homeworks of market microstructure models.☆274Updated 7 years ago
- Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.☆277Updated last week
- Collection of papers from the Goldman Sachs Quantitative Strategies Research Notes series (published in the '90s)☆352Updated 2 months ago
- PyTorch-based framework for Deep Hedging☆334Updated last year
- Deep Learning Statistical Arbitrage☆254Updated 3 years ago
- ArbitrageLab is a python library that enables traders who want to exploit mean-reverting portfolios by providing a complete set of algori…☆622Updated last year
- We implement the paper: Deep Learning Volatility☆204Updated 5 years ago
- Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.☆162Updated 5 years ago
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆140Updated last year
- ☆152Updated 2 years ago
- experiments with pair trading☆332Updated last year
- Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Sta…☆206Updated last year
- Low Latency Interest Rate Markets – Theory, Pricing and Practice☆244Updated 11 months ago
- HFT signals on GDAX☆114Updated 8 years ago
- Using tabular and deep reinforcement learning methods to infer optimal market making strategies☆235Updated 2 years ago
- A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) …☆305Updated this week
- Goldman Sachs - Quantitative Strategies Research Notes☆386Updated 5 years ago
- ☆141Updated 2 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆123Updated 2 years ago
- Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, …☆481Updated last week
- Statistical Jump Models in Python, with scikit-learn-style APIs☆127Updated last year
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆75Updated 5 years ago
- Collection of resources used on QuantPy YouTube channel.☆268Updated last month
- This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (…☆265Updated 3 years ago
- To classify trades into buyer- and seller-initiated.☆155Updated 3 years ago
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆88Updated 4 years ago
- Python library for asset pricing☆126Updated last year
- This repository contains different tools to simulate underlyings under SV dynamics. As well, we have implemented several tools for comput…☆126Updated 3 months ago