FernandoDeMeer / Hierarchical-SigCWGANLinks
Implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation: https://doi.org/10.3905/jfds.2022.1.109
☆17Updated 2 years ago
Alternatives and similar repositories for Hierarchical-SigCWGAN
Users that are interested in Hierarchical-SigCWGAN are comparing it to the libraries listed below
Sorting:
- Calculate predictive causality between time series using information-theoretic techniques☆103Updated 4 years ago
- Pipeline for Time Series Generation with Comprehensive Evaluation Metrics☆42Updated 8 months ago
- Non-parametric method for estimating regime change in bivariate time series setting.☆14Updated 8 years ago
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆49Updated 8 months ago
- Pytorch implementation of Deep Hedging, Utility Maximization and Portfolio Optimization☆16Updated last year
- DCC-GARCH(1,1) for multivariate normal distribution.☆61Updated 2 years ago
- Loose collection of Jupyter notebooks, mostly for my blog☆28Updated 10 months ago
- Market simulator☆61Updated 5 years ago
- Code to accompany the paper "Fin-GAN: Forecasting and Classifying Financial Time Series via Generative Adversarial Networks"☆127Updated last year
- ☆21Updated 10 months ago
- Thesis project done on Generation Financial Time-Series with GANs. The project was a collaboration between Wholesale Banking Advanced Ana…☆71Updated 5 years ago
- Transformer and MultiTransformer layers for stock volatility forecasting purposes☆72Updated 4 years ago
- MTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)☆94Updated 4 years ago
- Estimators and analysis for extreme value theory (EVT)☆20Updated 4 years ago
- Estimation of the Covariance Matrix - linear and nonlinear shrinkage☆23Updated 3 years ago
- Multiple Univariate AR-GARCH Modelling with Copula marginals for simulation☆20Updated last year
- Implementation of 2019 Quant GANs: Deep Generation of Financial Time Series paper☆31Updated last year
- Implementation of the Bayesian Online Change-point Detector of Ryan Prescott Adams and David McKay.☆15Updated 4 years ago
- Quant GAN from [Wiese et al., Quant GANs: Deep Generation of Financial Time Series, 2019]☆22Updated 4 years ago
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated last year
- ☆33Updated 2 years ago
- The implementation of "modeling financial time-series with generative adversarial networks"☆62Updated 2 years ago
- DCC GARCH modeling in Python☆96Updated 5 years ago
- Time Series Forecasting with Temporal Fusion Transformer in Pytorch☆12Updated 3 years ago
- Deep Learning methods to solve path-dependent PDEs / to price path-dependent derivatives like exotic options☆36Updated 3 years ago
- Dynamic lead/lag inference for time series☆17Updated 6 years ago
- ARMA-GARCH☆98Updated last year
- Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization☆58Updated 3 years ago
- This Python function dm_test implements the Diebold-Mariano Test (1995) to statistically test forecast accuracy equivalence for 2 sets of…☆121Updated 7 years ago
- Time Series Forecasting with LightGBM☆85Updated 3 years ago