Practical financial data science examples applying statistics, time series analysis, graph analytics, backtesting, machine learning, natural language processing, neural networks and LLMs

Support financial data science workflow, manage large structured and unstructured data sets, and apply financial econometrics and machine learning

Latest source files for the kdb+taq package

Estimation of realized quantities

Resample High Frequency Data

A simple SAS program that can extract TAQ data from WRDS cloud for a list of companies on particular dates during specific time periods.

Machine learning application in Finance using recurrent neural networks and reinforcement learning.

Access TAQ from WRDS and tick data from LSEG Tick History

Research framework for optimal high-frequency market making with Avellaneda-Stoikov quoting, WRDS TAQ replay backtesting, queue-aware fills, volatility-adaptive spreads, and robust execution/P&L analysis.

Quickly find and SSH into any host in your inventory — no more digging through command history.

Trade and quote data utilities for Julia