XuanyiJi / Forecasting-the-volatility-of-stock-price-indexLinks
A hybrid model to predict the volatility of stock index with LSTM and GARCH-type input parameters
☆25Updated 4 years ago
Alternatives and similar repositories for Forecasting-the-volatility-of-stock-price-index
Users that are interested in Forecasting-the-volatility-of-stock-price-index are comparing it to the libraries listed below
Sorting:
- Uisng CNN to predicte stock market trend, and feeding with 2D images☆15Updated 6 years ago
- Developing hybrid deep learning models by integrating Neural networks with (s,e,t)GARCH models to predict volatility in the Indian Commod…☆17Updated 4 years ago
- Univariate_ARIMA_models, ARCH/GARCH Volatility Forecasting models, VAR model for macro fundamentals forecasts☆12Updated 4 years ago
- A Python implementation of a Hybrid LSTM-GARCH model for volatility forecasting☆41Updated 2 years ago
- By combining GARCH(1,1) and LSTM model implementing predictions.☆57Updated 6 years ago
- Conversion of the time series values to 2-D stock bar chart images and prediction using CNN (using Keras-Tensorflow)☆42Updated 2 years ago
- This repository represents work in progress for the Worldquant University Capstone Project titled: Asset Portfolio Management using Deep …☆84Updated 2 years ago
- Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and …☆43Updated 3 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆28Updated 6 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 4 years ago
- XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project atte…☆37Updated 6 years ago
- This trading strategy deploy the copula model to define the divergence of two correlated asset. The backtesting system is built on backtr…☆22Updated 3 years ago
- The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using t…☆61Updated 3 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆26Updated 2 years ago
- ☆27Updated 2 years ago
- The repository contains the code for project for DS 5500 course at Northeastern.☆36Updated 5 years ago
- ☆77Updated 5 years ago
- kennedyCzar / STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABOOST-TREE-REGRESSION-AND-QDAForecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning …☆133Updated 2 years ago
- Transformer and MultiTransformer layers for stock volatility forecasting purposes☆72Updated 4 years ago
- For Chinese comments, the Finbert model was used to conduct polarity analysis and predict stock price rise☆24Updated 4 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- I use a LSTM ( long short term memory model) model to predict the fluctuations of VIX index ( the index of 50ETF options), and trade t…☆13Updated 6 years ago
- Trend Prediction for High Frequency Trading☆42Updated 2 years ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆20Updated 11 months ago
- 一些研报的复现☆13Updated 6 years ago
- Deep Direct Recurrent Reinforcement Learning to learn trading system☆26Updated 7 years ago
- ☆45Updated 3 years ago
- A low frequency statistical arbitrage strategy☆20Updated 6 years ago
- In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US s…☆55Updated 4 years ago
- Market Risk Management with Time Series Prediction of Stock Market Trends using ARMA, ARIMA, GARCH regression models and RNN for time ser…☆21Updated 7 years ago