sardarosama / Stock-Market-Trend-Prediction-Using-Sentiment-AnalysisLinks
Stock Market Trend Prediction using sentiment analysis Leveraging machine learning and sentiment analysis, we accurately forecast stock market trends. Our project combines advanced algorithms like BERT and Naïve Bayes with sentiment analysis from Twitter and other sources. By analyzing sentiment and historical price data, we provide insights
☆33Updated last year
Alternatives and similar repositories for Stock-Market-Trend-Prediction-Using-Sentiment-Analysis
Users that are interested in Stock-Market-Trend-Prediction-Using-Sentiment-Analysis are comparing it to the libraries listed below
Sorting:
- Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutatio…☆62Updated 5 years ago
- In this Jupyter Notebook, I've used LSTM RNN with Technical Indicators namely Simple Moving Average (SMA), Exponential Moving Average (EM…☆41Updated 4 years ago
- This repository is the result of our work for the course CSCI-SHU 360 Machine Learning☆58Updated 4 years ago
- ☆38Updated 4 years ago
- Python Jupyter Notebooks for Financial Portfolio Optimization☆34Updated 6 years ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆65Updated 10 months ago
- A Streamlit based application to predict future Stock Price and pipeline to let anyone train their own multiple Machine Learning models o…☆91Updated 9 months 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
- Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news a…☆191Updated 2 months ago
- A dashboard for macroeconomic and stock market data built with Python and Dash.☆33Updated 2 years ago
- 😲🤑Method for Investors and Traders to make Buying and Selling Decisions. 😄Fundamental hare Market Analysis is about using Real data to…☆72Updated 4 years ago
- ☆14Updated 2 years ago
- Implementation of algorithmic trading using reinforcement learning.☆29Updated 4 years ago
- Predicting the price movement of stocks using past prices and sentiment analysis scores from financial News.☆18Updated 2 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆64Updated 2 years ago
- Developing a long/short equity investment portfolio with Machine Learning predictions using data acquired from web-scraping. Flatiron Mod…☆39Updated 4 years ago
- Real time scrapping of stock data in order to get the most recent available information. Cleaning, structuring and parsing of relevant da…☆91Updated 11 months ago
- Regime detection in historical markets using Hidden Markov Models (HMM) and Support Vector Machines (SVM).☆18Updated 3 years ago
- ☆74Updated 11 months ago
- Topic : Option trading Strategies , B&S , Implied Volatility &Stochastic & Local Volatility , Geometric Brownian Motion.☆26Updated last year
- Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and …☆42Updated 3 years ago
- A library of quantiative algorithms for algorithmic trading implemented with Python☆70Updated 3 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 …☆60Updated 5 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
- 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 4 years ago
- ☆13Updated 2 years ago
- The notebook with the experiments to replicate and enhance the stock clustering proposed by Han(2022) for alogtrading, with KMeans Optimi…☆16Updated last year
- 📈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
- Jupyter notebooks and data files of the new EDHEC specialization on quantitative finance (completed Aug 2022)☆41Updated 2 years ago
- Quantitative analysis of fundamentals in quarterly reports by Machine Learning☆22Updated 5 years ago