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
☆11Updated 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.☆35Updated 5 years ago
- ☆25Updated 5 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
- [Python Package] Code from 'The Elements of Hawkes Processes' Book☆30Updated 2 years ago
- ☆18Updated 3 years ago
- Implementation of the Bayesian Online Change-point Detector of Ryan Prescott Adams and David McKay.☆15Updated 4 years ago
- Code for Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting☆42Updated 4 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 4 years ago
- Contrastive Multi-granularity Learning for Stock Trend Prediction☆24Updated 4 years ago
- a python package for simulation and inference of Hawkes processes.☆70Updated 4 years ago
- Python class for generation and parameter estimation of multivariate Hawkes processes☆175Updated 5 months ago
- The code and datasets of "Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction"☆58Updated 4 years ago
- Portfolio Optimization with Cumulative Prospect Theory Utility via Convex Optimization☆37Updated last year
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated last year
- FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks☆132Updated 4 years ago
- Implementation of Log Gaussian Cox Process in Python for Changepoint Detection using GPFlow☆36Updated 2 years ago
- The source code and data of the paper "Instance-wise Graph-based Framework for Multivariate Time Series Forecasting".☆33Updated 4 years ago
- Option hedging strategies are investigated using two reinforcement learning algorithms: deep Q network and deep deterministic policy grad…☆21Updated 6 years ago
- Code for paper "Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions"☆17Updated 4 years ago
- Codes for the paper Stock Trading Volume Prediction with Dual-Process Meta-Learning accepted by ECML PKDD 2022☆35Updated 3 years ago
- Learning Hawkes Processes from a Handful of Events☆13Updated 2 years ago
- Open code for PriceGraph☆73Updated last year
- This is a tensorflow-keras implementation of our paper "Attention Based Dynamic Graph Learning Framework for Asset Pricing"☆14Updated 4 years ago
- ☆58Updated 4 years ago
- code for "Neural Jump Ordinary Differential Equations"☆30Updated 2 years ago
- Bayer, Friz, Gulisashvili, Horvath, Stemper (2017). Short-time near-the-money skew in rough fractional volatility models.☆13Updated 8 years ago
- Final project repo for UCLA CS 267A☆13Updated 5 years ago
- This github repo contains my replicate experiments of paper 'Enhancing Stock Movement Prediction with Adversarial Training'.☆20Updated 4 years ago
- Financial time series forecasting with multi-modality graph neural network☆52Updated 2 years ago
- ☆37Updated 3 years ago