Yahoo Finance

Yahoo Finance has a related Python package called 'yfinance'. yfinance is a popular Python library that allows users to download historical market data for stocks and other financial instruments from Yahoo Finance. With yfinance, users can easily access a wide range of financial data, including stock prices, volume, dividends, and more. By specifying the ticker symbol of the stock and the date range, yfinance can download the historical data and store it in a pandas DataFrame. The library is easy to use and provides a powerful tool for analyzing market trends and making informed investment decisions.

Financial Modeling Prep

Financial Modeling Prep is a web-based financial data platform that provides access to a wide range of financial data and analytics tools. The platform offers a comprehensive suite of financial modeling tools, including stock prices, financial statements, economic indicators, and more. Financial Modeling Prep is commonly used by investors, financial analysts, and traders to analyze market trends, identify profitable investment opportunities, and make informed investment decisions. With its user-friendly interface and powerful analytics tools, Financial Modeling Prep is an essential resource for anyone looking to stay ahead of the curve in the fast-paced world of finance.

Trading View

As a platform dedicated to technical and financial analysis of stocks, we understand the importance of providing our users with up-to-date and comprehensive information. To achieve this, we embed a variety of TradingView widgets on our website, which allow users to view real-time market data, track multiple charts and indicators, and access a wide range of technical analysis tools.

Our news is made with AI! We begin by scanning trending stock tickers on Reddit and Twitter, and then perform financial and technical analysis on them. We then use ChatGPT to synthesize this analysis and generate readable, informative paragraphs and articles. With this, we're able to provide timely and accurate market analysis that can help our users.

Automated trading has become my primary focus, and I'm constantly working on developing and refining trading bots that can generate profits around the clock. My ultimate goal is to minimize manual intervention as much as possible and rely on a series of customized bots to execute trades based on proven strategies. While I've already created some trading bots and have a high-level understanding of what's involved, I know that the real challenge lies in the specifics. Identifying the best trading strategies for different stocks and market conditions is a complex task that requires extensive research and experimentation. Nevertheless, I'm dedicated to the pursuit of automated trading excellence and am always exploring new technologies, techniques, and strategies to enhance the performance of my bots.

I'm proud to say that my stock trading bot is currently running in production and generating modest but consistent returns. This bot utilizes a wide range of technical indicators, including EMA/SMA crossovers, MACD, RSI, and Candle Pattern Recognition, to identify profitable trading opportunities. In addition, it takes into account macro factors such as overall market conditions and ETFs in the related industry to make informed decisions about when to enter and exit trades. I'm constantly refining and optimizing this bot to improve its performance and increase its profitability. I plan to make some of the signals I use in my bots available on this site in the future.

At Financial Python, we leverage the power of machine learning to make both intraday and multiday predictions for stock prices. Our proprietary Ridge machine learning module was trained on 10 years of historical data from companies within the same industry, grouped by high or low market caps. We use a wide range of factors in our model, including sector, historical pricing, volume, and other key technical and financial analysis metrics. Additionally, we incorporate factors from the DOW and SPY to capture overall market trends and improve the accuracy of our predictions.

We're committed to staying on the cutting-edge of machine learning and data science techniques, and we plan to share our knowledge with others through a video course that will explain how to generate machine learning models for price prediction. Whether you're an experienced trader or just getting started, our machine learning approach to stock price prediction can help you make more informed investment decisions and achieve your financial goals.

Our 'Reddit Script' is a powerful tool that scans various stock-related subreddits, including WallStreetBets, stocks, StockMarket, pennystocks, investing, spacs, and others, to identify the most frequently mentioned stock tickers. Once the script has collected this data, it applies sophisticated technical analysis to these stocks to generate reliable signals for investors. Our system is designed to analyze multiple indicators and send alerts to users based on the appearance of specific signals. With its ability to sift through vast amounts of data and identify actionable insights, our 'Reddit Script' is a valuable tool for anyone looking to stay ahead of the game in the stock market.

Our 'Twitter Script' is an innovative tool that begins with this Twitter list, maintained by our team. The script pulls down tweets from this list, which are composed of people we consider experts, known as 'furus'. The goal is to identify the most frequently mentioned stocks. From there, the logic is the same as the Reddit Script

If there is anyone you think should be added or removed from this list, please reach out to us at info@financialpython.com

We're constantly working to enhance the functionality and usability of our platform, and we have some exciting plans for the future. One of our top priorities is to expand our coverage to include cryptocurrencies. The signals for cryptocurrencies would behave the same as stocks.

In addition to crypto, we also plan to incorporate other signals beyond EMA/SMA crossovers. Check back soon for more updates.