Advanced AI-powered framework designed to forecast long-term financial asset prices.

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Introduction

prAIce is an innovative AI framework developed to make informed long-term price forecasts on financial assets, with a current focus on US stocks. By emulating the comprehensive approach of a financial analyst, prAIce integrates multiple analysis techniques to provide a holistic view of an asset's potential future performance.

Key features of prAIce include:

• News Sentiment Analysis: Evaluates the impact of current events on asset prices.
• Technical Analysis: Utilizes numerous technical indicators to identify trends and patterns.
• Candlestick Pattern Recognition: Recognizes and interprets various candlestick patterns.
• Fundamental Analysis: Assesses the financial health and intrinsic value of companies.
• Hedge Fund Holdings Analysis: Tracks and analyzes institutional investor positions.
• Options Market Analysis: Examines options data for insights into market sentiment and potential price movements.
• Macroeconomic Indicators Analysis: Considers broader economic factors that may impact asset prices.
• Peer and Sector Analysis: Compares performance and metrics within industry groups
• Data Collection and Management: Efficiently collects and stores relevant financial data.
• Customizable Analysis: Allows for flexible configuration of data collection and analysis parameters.

prAIce is designed to be a robust tool for investors, analysts, and researchers seeking to make data-driven decisions in the financial markets. By combining traditional financial analysis methods with cutting-edge AI technologies, prAIce aims to provide valuable insights for long-term investment strategies.

Installation

To set up prAIce on your local machine, follow these steps:

1. Clone the repository

   git clone https://github.com/reza-zereh/prAIce.git
   cd prAIce

2. Set up a PostgreSQL database for the project.
3. Create and activate a virtual environment with Python version 3.10 or higher.
4. Rename the .env.sample file to .env and fill in the required values.
5. Install the TA-Lib library:
   • Linux:

     make install-talib

   • MacOS/Windows: TBD
6. Install the project requirements:
   • Linux:

     make install-requirements

   • MacOS/Windows: TBD

Disclaimer

prAIce is an experimental tool designed for research and educational purposes only. The predictions and analyses provided by prAIce should not be considered as financial advice or a guarantee of future market performance. Users of prAIce should always conduct their research and consult with qualified financial advisors before making any investment decisions. The creators and maintainers of prAIce are not responsible for any financial losses incurred based on the use of this tool.