lohithn4 / stock-market-prediction
A detailed study of four machine learning Techniques(Random-Forest, Linear Regression, Neural-Networks, Technical Indicators(Ex: RSI)) has been carried out for Google Stock Market prediction using Yahoo and Google finance historical data.
☆23Updated 7 months ago
Related projects ⓘ
Alternatives and complementary repositories for stock-market-prediction
- Stock closing and opening forecasting using Deep neural network and LSTM(technical indicators included)☆20Updated 7 years ago
- An adaptive model for prediction of one day ahead foreign currency exchange rates using machine learning algorithms☆38Updated 6 years ago
- Stock market prediction is the method of trying to determine the future value of publically listed company stock traded on an exchange. T…☆46Updated 8 years ago
- XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project atte…☆27Updated 5 years ago
- A comprehensive approach for stock trading implemented using Neural Network and Reinforcement Learning separately.☆21Updated 6 years ago
- • Conducted a volatility study to develop pairs trading strategy by writing web crawlers that automated extracting 30 equity and ETF spot…☆44Updated 3 years ago
- LSTM stock prediction and backtesting☆14Updated 4 years ago
- Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutatio…☆55Updated 5 years ago
- Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM☆50Updated 4 years ago
- 💸 A long-short equity quantitative trading strategy (sentiment-based)☆37Updated 6 years ago
- High Frequency Trading (HFT) done using the Alpaca Trade API and Python.☆25Updated 5 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…☆59Updated 3 years ago
- Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies…☆36Updated 3 years ago
- Having effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management…☆42Updated 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…☆47Updated 6 years ago
- Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to cho…☆69Updated 7 years ago
- Python based Quant Finance Models, Tools and Algorithmic Decision Making☆44Updated 6 years ago
- A financial trading method using machine learning.☆58Updated last year
- keywords - Kmeans Clustering, Tsne, PCA, Indian Stocks, Johansen test☆30Updated 6 years ago
- streaming order book data from TD Ameritrade API☆33Updated 4 years ago
- LSTM RNN for sentiment-based stock prediction☆64Updated 6 years ago
- trading strategy is a fixed plan to go long or short in markets, there are two common trading strategies: the momentum strategy and the …☆56Updated 4 years ago
- Algorithmic approach to analysing performance and the similarity of different stocks in S&P 500 via cluster analysis.☆9Updated 7 years ago
- ☆24Updated 6 years ago
- Algorithmic Trading using RNN☆32Updated 8 years ago
- Capital Asset Pricing Model implementation in python to analyze stock risk and return.☆25Updated 2 years ago
- Automatically performs the DCF calculation, sensitivity analysis and Piotroski f-score analysis for a given company. All financial data c…☆44Updated 4 years ago
- Multi Strategy Trading Algorithm☆46Updated 7 years ago
- Predicting a Stock Price Using a Genetic Algorithm☆15Updated 6 years ago