Automated Asset Value Analysis Service

Analysis of coverage pay data

This repository contains R scripts for retrieving and analyzing company data from the U.S. Securities and Exchange Commission (SEC) filings.

An open source time-series database for fast ingest and SQL queries

Credit Card Analysis Report using Power BI and PostgreSQL, provides comprehensive insights into the credit card transactions and customer behavior. This report analyzes transaction trends, customer spending patterns, and demographic insights to optimize marketing strategies and improve customer satisfaction and overall business performance.

An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.

Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau

Predictor for stock and ETF prices

TDengine is an open source, high-performance, cloud native time-series database optimized for Internet of Things (IoT), Connected Cars, Industrial IoT and DevOps.

Creative analysis and exploration of capital markets and alternative databases

FinTwit-Bot is a Discord bot designed to track and analyze financial markets by pulling data from platforms like Twitter, Reddit, and Binance. It features customizable tools for sentiment analysis, market trends, and portfolio tracking to help traders stay informed and make data-driven decisions.

HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.

This strategy works for every market condition irrespective of the movement

Py-Alpaca-Api is a python package aimed at simplifying communication with Alpaca Markets REST API

Easily parse SDR data with this web application!

Sentiment Analysis of Financial Stocks

Personal accounting and financial system

Python code for a quantitative momentum investment strategy that selects high-momentum stocks from the S&P 500 index and calculates recommended trades for an equal-weight portfolio. Implements an alternative strategy based on the 80-20 principle.

This project demonstrates a quantitative value investing strategy that selects the 50 stocks with the best value metrics from the S&P 500. The strategy involves calculating the recommended trades for an equal-weight portfolio of these 50 stocks, as well as a more advanced robust value strategy.

Working with Alpaca's API, to help make develping strategies an easier task