SinghAbhi1998 / Stock-Market-Price-PredictionLinks
Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest Neighbor, Support Vector Machine, Decision Tree, and Random Forest to identify which algorithm gives better results. Used Neural Networks such as Auto ARIMA, Prophet(Time-Series), and LSTM(Long Term-Short Memory…
☆26Updated 5 years ago
Alternatives and similar repositories for Stock-Market-Price-Prediction
Users that are interested in Stock-Market-Price-Prediction are comparing it to the libraries listed below
Sorting:
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆14Updated 2 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US s…☆56Updated 4 years ago
- Crypto-Options Volatility Surface Calibration and Arbitrage☆16Updated 2 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 4 years ago
- 📈This repo describes a framework that leverages sentiment stability of a financial 10-K report as the trading signal (alpha factor)☆12Updated 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…☆43Updated 6 years ago
- Quantitative analysis of fundamentals in quarterly reports by Machine Learning☆23Updated 5 years ago
- A multi-factor stock selection model based on random forest with an average annualized yield of 33.74% from March 2014 to June 2017 when …☆17Updated 6 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 4 years ago
- Uisng CNN to predicte stock market trend, and feeding with 2D images☆15Updated 7 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆29Updated 7 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
- A low frequency statistical arbitrage strategy☆20Updated 6 years ago
- Design your own Trading Strategy☆39Updated last year
- This trading strategy deploy the copula model to define the divergence of two correlated asset. The backtesting system is built on backtr…☆23Updated 3 years ago
- Time-Series Momentum Strategies☆12Updated 7 years ago
- In this project, I had backtested the cross-over trading strategy on Google Stock from Jan 2016 to June 2020. By using historical time-se…☆45Updated 5 years ago
- Stock Price Prediction with PCA and LSTM☆15Updated 4 years ago
- Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market…☆16Updated 4 years ago
- ☆19Updated 8 years ago
- A machine learning pipeline that ingest and process a 20-year historical stock price dataset and try to predict future prices using Light…☆15Updated 5 years ago
- Having effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management…☆51Updated 5 years ago
- Pytorch implementation of deep learning models for financial time series forecasting using LOB☆19Updated 2 years ago
- Trend Prediction for High Frequency Trading☆43Updated 2 years ago
- This project explores stock trading modelling with the use recurrent neural network (RNN) with long-short term memory (LSTM) architecture…☆28Updated 6 years ago
- Deep learning models for high-frequency financial data (limited order book)☆19Updated 6 years ago
- Testing trading signals of commodity futures☆17Updated 5 years ago
- This project would demonstrate the following capabilities: 1. Extraction Loading and Transformation of S&P 500 data and company fundament…☆13Updated 4 years ago
- This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time …☆22Updated 5 years ago