hrbzkm98 / ml-research
A repository for machine learning based investment strategies
☆28Updated 4 years ago
Related projects: ⓘ
- Empirical asset pricing via Machine Learning in the Korean market☆30Updated 6 months ago
- Machine learning methods for identifing investment factors☆14Updated 2 years ago
- ☆60Updated last year
- PyTorch autoencoder implementation of asset pricing model using monthly returns/metrics☆36Updated 4 years ago
- Calculate U.S. equity (portfolio) characteristics☆78Updated last month
- Reimplementation of Autoencoder Asset Pricing Models (GKX, 2019)☆57Updated 2 months ago
- Machine learning methods for identifing investment factors☆14Updated 2 years ago
- My codework for my economics undergraduate thesis titled "Empirical Asset Pricing via Deep Learning"☆46Updated 4 years ago
- DCC GARCH modeling in Python☆84Updated 4 years ago
- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3350138☆114Updated 3 years ago
- Empirical Data and Some Simulation Codes☆96Updated 5 years ago
- Python Package: Fitting and Forecasting the yield curve☆33Updated 3 years ago
- Implementation of a variety of Value-at-Risk backtests☆35Updated 5 years ago
- Fama French model on a subset of Canadian Equity data with Python☆44Updated 5 years ago
- Modeling conditional betas with DCC-GARCH and COMFORT-DCC models with application in asset allocation.☆15Updated 4 years ago
- Multivariate DCC-GARCH model☆14Updated 5 years ago
- Replication and extension of paper on Conditional Value at Risk (CoVaR) by Adrian and Brunnermeier.☆15Updated 3 years ago
- Calculates 103 firm characteristics from CRSP + Compustat directly in Python – no WRDS SAS cloud☆27Updated last year
- US equity (portfolio) characteristics, the main file is in SAS.☆16Updated 8 months ago
- ☆20Updated 9 months ago
- Using three approaches to calculate Value at Risk and Conditional Value at Risk of a portfolio of assets.☆13Updated 4 years ago
- some interest rate models such as Vasicek and dynamic Nelson-Siegel model☆11Updated 4 years ago
- An economic forecasting model based on Factor Augmented VAR (FAVAR). The FAVAR approach is superior than classic VAR as it incorporates a…☆13Updated 3 years ago
- Winter 2020 Course description: Econometric and statistical techniques commonly used in quantitative finance. Use of estimation applicat…☆34Updated 3 years ago
- Recreation of Diebold and Li: Forecasting the term structure of government bond yields in python.☆21Updated 8 years ago
- Simulate and estimate volatility by GARCH with/without leverage, riskmetriks. Compute Value-at-Risk and Test on VaR Violation☆19Updated 6 years ago
- This resposity is a pre-released verison of Python code used in the paper "Asset pricing via the conditional quantile variational autoenc…☆13Updated 3 months ago
- ARMA-GARCH Mixture Copula Mean-CVaR portfolio optimization project.☆26Updated 3 years ago
- TensorFlow implementation of the HARNet model for realized volatility forecasting.☆24Updated last year
- Python code for rolling Value at Risk(VaR) of fiancial assets and some of economic time series, based on the procedure proposed by Hull &…☆11Updated 2 years ago