ramtiin / Predicting-Stock-Prices-Using-FB-Prophet
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, an…
☆17Updated 3 years ago
Alternatives and similar repositories for Predicting-Stock-Prices-Using-FB-Prophet:
Users that are interested in Predicting-Stock-Prices-Using-FB-Prophet are comparing it to the libraries listed below
- By combining GARCH(1,1) and LSTM model implementing predictions.☆56Updated 6 years ago
- Forex price movement forecast☆36Updated 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
- Stock Price Prediction using CNN-LSTM☆85Updated 5 years ago
- ARIMA & GARCH models for stock price prediction☆18Updated 4 years ago
- Compilation of technical analysis tools (EMA, Bollinger bands), fundamental analysis, machine learning models (LSTM, Random forest, ARIMA…☆13Updated 3 years ago
- ☆55Updated 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…☆54Updated 4 years ago
- This repository represents work in progress for the Worldquant University Capstone Project titled: Asset Portfolio Management using Deep …☆80Updated 2 years ago
- Time Series analysis with Python and ARIMA model to forecast Bitcoin price☆22Updated 6 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
- Transformer and MultiTransformer layers for stock volatility forecasting purposes☆66Updated 3 years ago
- This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Networks to predict stock prices.☆84Updated 3 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 …☆134Updated 2 years ago
- A stock price prediction model based on ARMA and GARCH☆23Updated 10 months ago
- Mean-Variance Optimization using DL (pytorch)☆31Updated 3 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 3 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
- Stock selection and portfolio performance based on ESG Scores☆14Updated 4 years ago
- Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management using TensorFlow.☆92Updated 2 years ago
- A Python implementation of a Hybrid LSTM-GARCH model for volatility forecasting☆32Updated 2 years ago
- LSTM For Stock Market Prediction☆15Updated 6 years ago
- Intra day Stock Prediction 10 minutes into the future☆104Updated 5 years ago
- Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until…☆266Updated last year
- ☆23Updated 4 years ago
- Hidden Markov Model (HMM) based stock forecasting☆100Updated 7 years ago
- Using fastai and CNNs to predict stock prices☆25Updated 5 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
- A Streamlit based application to predict future Stock Price and pipeline to let anyone train their own multiple Machine Learning models o…☆89Updated 8 months ago
- ☆77Updated 5 years ago