crsp

Calculates 103 firm characteristics from CRSP + Compustat directly in Python – no WRDS SAS cloud

Sample SAS programs that process WRDS data and facilitate econometric analysis

Data matching for corporate governance research

A python script to create a mapping table between I/B/E/S and Compustat

This GitHub repository shows data collection and analysis for “Regulatory Fragmentation” paper by Kalmenovitz, Lowry and Volkova, The Journal of Finance (Forthcoming)

Fuzzy match entity names (primarily persons and companies) across databases

US-equity quantitative research, backtest and paper-trading system (codename Plutus).

Pipeline dealing with WRDS (Wharton Research Data Services) datasets including crsp, master, etc, in order to build mega-database for scaling in Market Microstructure research

Point-in-time backtest of a 200-day moving-average rule on S&P 500 constituents, 1996-2024, on CRSP data: historical membership, delisting returns, next-open fills, spread costs, CRSP tape reconciliation and a rebalance timing-luck audit.

Classify CRSP-style delisting reasons from SEC EDGAR for quant pipelines

Replication code for "Industry factor structure: Beta estimation and cross-sectional returns" (Woo & Kim, 2026)

End-to-End Python implementation of Mo et al.'s (2025) ACT-Tensor methodology; a tensor completion framework for financial dataset imputation. Implements cluster-based CP decomposition, HOSVD factor extraction, temporal smoothing (CMA/EMA/Kalman), and downstream asset pricing evaluation. Transforms sparse data into dense machine readable data.

Point-in-time insider filing de-noising, ML scoring, and cross-sectional return tests.

Stock Factor Data

按决策难度匹配 Agent 介入方式的智能数据准备系统 | Intelligent Data Preparation Agent

This is a project that collects SEC Form 4 filings (filings that detail stock transactions made by company officers, directors, and large shareholders), transforms the data into daily trading signals, and uses CRSP/Compustat daily data to model portfolios made using those signals.

Idiosyncratic volatility and abnormal returns during VIX spike events empirical study using a survivorship-bias-free CRSP universe (2005–2024)

Replication of Byun & Jeon (2023): does the 52-week high remove momentum crashes? CRSP 1926–2024, WML vs WML* vs V-WML. R.

Jump detection via expanding-window Z-score on SPY and BRK.B (2020-2025) + logistic regression using Loughran-McDonald NLP sentiment from 48 SEC 8-K filings. McFadden R²=0.50. VCU FIRE 691.

Minimal PEAD (post-earnings announcement drift) backtest using Wharton Research Data Services (IBES + CRSP) — Python pipeline for research & plots.