Managing the data infrastrcture and computing resources of Imperial Algosoc
Database: price and fundamentals data of US Equities and other asset classes
Cloud computing: deploy machine learning models on cloud computing services to generate live predictions
Python: Pandas, Dask
Database: MongoDB
Computing: Docker, Linux
Kaggle US Equities Data (1992-2019)
Kaggle US reported financial Data (2010-2020)
Quandl Financial Industry Regulatory Authority (2013-2020)
https://www.kaggle.com/finnhub/reported-financials
https://www.kaggle.com/finnhub/end-of-day-us-market-data-survivorship-bias-free
https://www.quandl.com/data/FINRA-Financial-Industry-Regulatory-Authority
Calendar for US Equities Installation
pip install pandas_market_calendars
https://github.com/rsheftel/pandas_market_calendars
Stage 1: Historical database
Design database schema for storing daily US Equity and fundamentals data
Build metadata for database
Build functions for feature engineering
Build API for database access
Stage 2: Cloud services
Process live data
Deploy database on cloud services
Deploy machine learning models