niharikabalachandra / Market-Risk-Management-with-Time-Series-Prediction-of-Stock-Market-Trends-
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
- By combining GARCH(1,1) and LSTM model implementing predictions.☆56Updated 6 years ago
- Stock markets are an essential component of the economy. Their prediction naturally arouses afascination in the academic and financial w…☆21Updated 3 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 4 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
- RNN - Stock Prediction Model using Attention Multilayer Recurrent Neural Networks with LSTM Cells☆39Updated 7 years 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
- 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
- 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
- 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
- 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
- ARIMA & GARCH models for stock price prediction☆18Updated 4 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 11 months 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 …☆134Updated 2 years ago
- Multi-Factor Stock Profit Prediction Using EMD-ALSTM☆27Updated 5 years ago
- Stock Price Prediction with PCA and LSTM☆14Updated 4 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
- This project explores stock trading modelling with the use recurrent neural network (RNN) with long-short term memory (LSTM) architecture…☆26Updated 6 years ago
- Stock Market Prediction Using Unsupervised Features☆53Updated 6 years ago
- An Empirical Study of Optimal Combination of Algorithms for Prediction-Based Portfolio Optimization Model using Machine Learning over Co…☆11Updated 2 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆26Updated 2 years ago
- Stock risk premium prediction via FM/ EXT/ GBDT/ XGB/LBGM. Mengxuan Chen's graduation thesis at WHU.☆14Updated 5 years ago
- XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project atte…☆31Updated 6 years ago
- Deep Learning - Neural network (RNN, LSTM & GRU)☆66Updated 6 years ago
- Predicting the closing stock price given last N days' data that also includes the output feature for CNN & LSTM, while predicting it for …☆10Updated 5 years ago
- A hybrid model to predict the volatility of stock index with LSTM and GARCH-type input parameters☆24Updated 4 years ago
- Univariate_ARIMA_models, ARCH/GARCH Volatility Forecasting models, VAR model for macro fundamentals forecasts☆11Updated 4 years ago
- This project aims to predict VOLATILITY S&P 500 (^VIX) time series using LSTM.☆100Updated 4 years ago
- Attempt to replicate: A deep learning framework for financial time series using stacked autoencoders and long- short term memory☆91Updated 3 years ago
- Compilation of technical analysis tools (EMA, Bollinger bands), fundamental analysis, machine learning models (LSTM, Random forest, ARIMA…☆13Updated 3 years ago