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stock-market-challenge

stock-market-charting-application

In this project, I have worked on Spring Boot microservices along with MongoDB Atlas as backend and Angular.js as frontend to design a Stock Market Charting Application.

stock-market-clustering

An unsupervised machine learning model to group companies into different clusters based on historical stock movements and using K-Means algorithm

stock-market-crashes

How to detect stock market crashes with topology.

stock-market-dash-plotly

Stocks dashboard to analyze stocks performance and apply backtesting strategies

stock-market-dashboard

Extracted financial data like historical share price and quarterly revenue from various sources using Python libraries and web scraping on popular stocks

stock-market-data-analysis

A simple stock market data analysis using Yahoo Finance and Plotly.

stock-market-database

# A real-time self-updating database The database tracks given stocks' prices and volumes in every minute from 2012-01-01 to present

stock-market-forecast

This is a project to learn using python library dash for creating basic dashboards.

stock-market-forecasting

Forecasting directional movements of stock prices for intraday trading using LSTM and random forest

stock-market-india

API for Indian Stock Market's NSE and BSE.

stock-market-indicators

A repository for some of the popular stock market indicators coded and backtested in python using backtrader.

stock-market-intraday-predictor

Mini project on stock market intra day prediction in python - 1) Top 10 companies for trading are found out using the stock screener from investing.com. 2) The details of a particular company selected from this list by the user are scraped from screener.in. Using the values scraped here like ROCE, ROE etc., we can figure out whether the stock is good for intraday trading and/or investment. 3) Open, close, high, low, adj. close, volume details are scraped for the particular stock from yahoo finance. 4) A basic linear regression model is used to predict the open price for next day.

stock-market-management-system-prediction-buy-sell-

Stock market management system includes functionaliities like prediction (of next day's opening price) and buy-sell of stocks.

stock-market-ml

Machine Learning using Historic Stock Market Data and Twitter Sentiment Analysis

stock-market-prediction

stock-market-prediction-1

An attempt to predict stock market volatility, return and trading volume of tech stocks using Semantic Vectors and Google Trends, which reflects real-time popularity of search terms

stock-market-prediction-and-analysis-using-technical-indicators

Prediction of Stock Prices using ARIMA model and analysis of Stocks using Technical Indicators

stock-market-prediction-and-decision-making

• Developed a decision model which helps the investor to make a good decision while investing in stock market using Python • A model which streams historical stock data from google finance API with python programming language and make 4 different predictive models • Considered expected monetary value, expected utility and certainty equivalence and other 10 significant factors while buying stocks • Model suggests decision, based on profit margins and allowance time while selling the stocks • Used scikit learn, matplotlib, pandas, googlefinance-client, statemodels, numpy and other important libraries

stock-market-prediction-forecasting-price-movements-using-technical-indicators

Trying to replicate the results in the paper "Forecasting Price Movements using Technical Indicators: Investigating the Impact of Varying Input Window Length."

stock-market-prediction-using-gan

Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets

stock-market-prediction-using-lstm-deep-learning

A deep learning algorithm used to make stock market predictions on historic data analysis.

stock-market-prediction-using-super-learner-model

This algorithm trains on a stocks dataset of Apple(AAPL) based on which the super learner model can make accurate predictions with regard to the same

stock-market-prediction-web-app-using-machine-learning-and-sentiment-analysis

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

stock-market-price-analysis

stock-market-project

This repository contains a crawler that downloads all the stock datas of S&P500 companies and then trains an LSTM network individually for prediction. In end we get graphs of predicted vs real closing prices. There is an option of also saving the weights of network so that it can be used later.

stock-market-scraper

scraps historical stock market data from https://finance.yahoo.com/

stock-market-screener

Stock market screener using FastAPI

stock-market-sentiment-analysis

Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka

stock-market-sentiment-analysis-1

Stock Market gets influenced by news articles' headlines. People read the headlines and decide whether a company's performance is good enough in the market or not. Instead of asking people what their opinion on a company is, we can use sentimental analysis to predict the company's performance in the stock market.