Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

Using Reddit market sentiment to predict stock prices.

Can Reddit beat the stock market? AI-powered experiment scoring reasoning quality in r/ValueInvesting and backtesting against S&P 500.

StockTrendsBot is a Reddit bot that monitors various subreddits for mentions of public companies. It then retrieves year over year, month over month, and week over week stock performance data and posts it in Reddit markup.

Reddit price and stock checker bot - replies with useful info, and saves data for later analysis

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Scalable Data Pipeline for Stock Market Analysis with Reddit API and Yahoo Finance.

Stock sentiments analysis on data scrapped from Reddit using PRAW and analysing sentiments using Wit.AI.

TrendSage aims to develop a correlation between stock and cryptocurrency predictions based on the posts or comments on Reddit and the actual market trends.

Stock market prediction with Top Reddit's News

Python backend system that takes live time Reddit posts about penny stocks, uses sentiment analysis to determine whether to buy, hold, or sell the stock, and pushes information in live time to an angular website

The project is about predicting the stock market movement based on the news headlines that published on a particular day. The news data is collected from Reddit news and top 25 headlines, ranked based on reddit user votes, are taken on each day. The stock market data, DJIA (Dow Jones Industrial Average) of each day is collected from Yahoo finance. Combined both datasets to process and apply modeling techniques further to get desired results. Different NLP techniques and machine learning models are used to address the problem defined.

a mobile app focusing stock sentiment from reddit and twitter user data

AI agents analyze Reddit sentiment + real-time web research to deliver weekly stock BUY recommendations

Scrape most mentioned stock tickers from Reddit. Wallstreetbets and Wallstreetbetsnew

This Python script parses Reddit's API to find mentions of stock $tickers to gauge their rising popularity.

Scrape real-time stock data and breaking news from Webull, Reddit, CNBC websites and Twitter API.

A high frequency trading module based on how often stock symbols appear in reddit comments

Chrome extension showing the most recent stock prices and percent change of tickers founds in Reddit posts

A sentiment-driven trading algorithm using deep learning to analyze social media sentiment from StockTwits, Twitter, and Reddit for stock market predictions. Built with Python, TensorFlow/Keras, and MySQL.

Analyze Reddit posts/comments, uses an NLP model to recognize stock symbols and options positions

Reddish Trends is a Reddit powered stock market analyzer. This is a unique website that uses reddit to uncover stock data and anaylize sentiment data using algorithms, add financial data using yahoo finance and provide feedback using AI. the webiste uses Next.js, Javascript, Typescript, Tailwind and CSS. Feedback: reddishtrends@googlegroups.com

Determining the price of a stock is complex; it depends on the number of outstanding shares, the size of the company's future profits, and much more. An essential factor is the company's profit and growth of profits; if the company's profit is increasing, the stock price should increase. If you suspect the company's profit increases, you should buy the stock as the stock should increase, But what happens if you think the stock price will decrease. Short selling is how you make money if the stock decreases. An investor borrows a stock, sells the stock, and then repurchases it to return it to the lender. Typically stocks fall faster than they rise, so you can make a profit more quickly. Usually, experienced investors such as hedge funds partake in short selling. One problem is if the stock price increases, the investor can lose money. Sometimes short sellers get it wrong; for example, Tesla. A few years ago, many short sellers targeted Tesla. Then Tesla started becoming profitable, and profits were increasing; thus, the company stock went up. This was based on the companies performance, so the stock should continue to rise, and the short seller should sell the stock. Recently shorted stocks can increase for reasons that are not based on fundamentals; this is less sustainable. Individual investors using the forum on the Reddit online community named WallStreetBets, started buying into shares of GameStop, a video and computer-game retailer losing money. The influx of demand caused GameStop shares to soar. All this produced billions of dollars in losses for hedge funds who had sold the stock short. [ 1] GameStop's share price should fall eventually, so the Hedge funds should hold on to the short positions. As a data scientist working for a hedge fund, you will extract the profit data for Tesla and GameStop and build a dashboard to compare the price of the stock vs the profit for the hedge fund.

A stock-market simulator for memes on Reddit

Scraping Reddit's top trading subreddits for the next red-hot stock

A simple Reddit bot that replies to comments with pertinent stock information.

Scraping reddit's /r/wallstreetbets to obtain occurrences of frequently mentioned stock tickers.

Written in python, this script is buys and sells options based on stock ticker mentions on reddit's r/wallstreetbets. It uses the robin_stocks api for robinhood and praw api for reddit.

Stock Sentiment Tracker is an innovative platform for monitoring current market sentiments through real time sentiment analysis of textual information from social media sites like Twitter and Reddit.

A Cloud based Reddit stock sentiment analyzer that analyzes overall sentiment from a configurable selection of stock subreddits for each stock. The architecture utilizes AWS MSK (Kafka), AWS EMR (PySpark) and AWS Lambda (Python 3) for maximum scalability and the OpenAI API for sentiment analysis through prompt engineering.