sohamch / Neural-Hawkes-studyLinks
A PyTorch exercise in implementing a continuous time LSTM to simulate Neural Hawkes Process based on the paper by Hongyuan Mei and Jason Eisner at https://arxiv.org/pdf/1612.09328.pdf - sohamch/Neural-Hawkes-study
☆10Updated 2 years ago
Alternatives and similar repositories for Neural-Hawkes-study
Users that are interested in Neural-Hawkes-study are comparing it to the libraries listed below
Sorting:
- A PyTorch Implementation of Neural Hawkes Process. Redefined.☆34Updated 5 years ago
- ☆18Updated 3 years ago
- Code for Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading at WWW 2021☆20Updated 4 years ago
- Implementation of the Bayesian Online Change-point Detector of Ryan Prescott Adams and David McKay.☆15Updated 4 years ago
- ☆23Updated 5 years ago
- [Python Package] Code from 'The Elements of Hawkes Processes' Book☆31Updated 2 years ago
- Code for IJCAI 2021 main conference paper "Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based M…☆23Updated 3 years ago
- The code and datasets of "Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction"☆56Updated 4 years ago
- The source code and data of the paper "Instance-wise Graph-based Framework for Multivariate Time Series Forecasting".☆32Updated 3 years ago
- ☆53Updated 5 years ago
- Final project repo for UCLA CS 267A☆14Updated 5 years ago
- ☆65Updated 4 years ago
- FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks☆128Updated 4 years ago
- This is a tensorflow-keras implementation of our paper "Attention Based Dynamic Graph Learning Framework for Asset Pricing"☆14Updated 3 years ago
- Option hedging strategies are investigated using two reinforcement learning algorithms: deep Q network and deep deterministic policy grad…☆21Updated 5 years ago
- Portfolio Optimization with Cumulative Prospect Theory Utility via Convex Optimization☆36Updated last year
- ☆37Updated 3 years ago
- Code for WWW-20 Paper: HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction☆60Updated last year
- Robust pricing and hedging via Neural SDEs☆37Updated 4 years ago
- Code for the paper "Estimating Transfer Entropy via Copula Entropy"☆42Updated 2 years ago
- Code for Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting☆42Updated 4 years ago
- Generative Adversarial Network to create synthetic time series☆23Updated 5 years ago
- a python package for simulation and inference of Hawkes processes.☆69Updated 4 years ago
- code for "Neural Jump Ordinary Differential Equations"☆30Updated 2 years ago
- Time series data structure learning with NOTEARS and DYNOTEARS☆13Updated last year
- Implementation of Log Gaussian Cox Process in Python for Changepoint Detection using GPFlow☆33Updated 2 years ago
- HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction☆162Updated 5 years ago
- Pytorch implementation of Deep Hedging, Utility Maximization and Portfolio Optimization☆16Updated last year
- Open code for PriceGraph☆72Updated last year
- Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks☆132Updated 3 years ago