niharikabalachandra / Market-Risk-Management-with-Time-Series-Prediction-of-Stock-Market-Trends-Links
Market Risk Management with Time Series Prediction of Stock Market Trends using ARMA, ARIMA, GARCH regression models and RNN for time series analysis and prediction of short-term tends in stock prices.
☆21Updated 7 years ago
Alternatives and similar repositories for Market-Risk-Management-with-Time-Series-Prediction-of-Stock-Market-Trends-
Users that are interested in Market-Risk-Management-with-Time-Series-Prediction-of-Stock-Market-Trends- are comparing it to the libraries listed below
Sorting:
- By combining GARCH(1,1) and LSTM model implementing predictions.☆57Updated 6 years ago
- Stock markets are an essential component of the economy. Their prediction naturally arouses afascination in the academic and financial w…☆21Updated 4 years ago
- Financial risk analysis on a stocks portfolio through the VaR (Value at Risk), using Monte Carlo Simulation and Multiple Linear Regressio…☆22Updated 4 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 4 years ago
- ARIMA & GARCH models for stock price prediction☆18Updated 4 years ago
- An Empirical Study of Optimal Combination of Algorithms for Prediction-Based Portfolio Optimization Model using Machine Learning over Co…☆11Updated 3 years ago
- Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity…☆48Updated 7 years ago
- Conversion of the time series values to 2-D stock bar chart images and prediction using CNN (using Keras-Tensorflow)☆40Updated 2 years ago
- keywords - Kmeans Clustering, Tsne, PCA, Indian Stocks, Johansen test☆32Updated 6 years ago
- This project is to practice applying Long Short-Term Memory network in deep learning to predict time series financial data. I selected Am…☆15Updated 7 years ago
- Compilation of technical analysis tools (EMA, Bollinger bands), fundamental analysis, machine learning models (LSTM, Random forest, ARIMA…☆13Updated 3 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆26Updated 2 years ago
- Using past price data and sentiment analysis from news and other documents to predict the S&P500 index using a LSTM RNN. Idea replicated …☆32Updated last year
- The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using t…☆60Updated 3 years ago
- Novice's attempt for Stock Prices Prediction & Portfolio Optimization using Machine Learning with Python & Scikit Learn☆56Updated 4 years ago
- Implementation of a variety of Value-at-Risk backtests☆37Updated 6 years ago
- RNN - Stock Prediction Model using Attention Multilayer Recurrent Neural Networks with LSTM Cells☆39Updated 7 years ago
- Stock Price Prediction with PCA and LSTM☆14Updated 4 years ago
- To create a data-web application deployed using the azure app service, which was made on Streamlit, the leading Pythonic data application…☆11Updated 3 years ago
- Estimating Value-at-Risk with a recurrent neural network (Jordan type) GARCH model☆68Updated 5 years ago
- Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=1…☆25Updated 4 months ago
- In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US s…☆54Updated 4 years ago
- The repository contains the code for project for DS 5500 course at Northeastern.☆36Updated 5 years ago
- Stock risk premium prediction via FM/ EXT/ GBDT/ XGB/LBGM. Mengxuan Chen's graduation thesis at WHU.☆14Updated 5 years ago
- Implement the model of Halperin and Feldshteyn for DJIA and SP500☆10Updated 6 years ago
- Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest N…☆25Updated 4 years ago
- Usage of policy gradient reinforcement learning to solve portfolio optimization problems (Tactical Asset Allocation).☆33Updated 6 years ago
- Univariate_ARIMA_models, ARCH/GARCH Volatility Forecasting models, VAR model for macro fundamentals forecasts☆11Updated 4 years ago
- Quantitative analysis of fundamentals in quarterly reports by Machine Learning☆22Updated 5 years ago
- SVM for stock/index prediction☆13Updated 8 years ago