Deep learning for forecasting company fundamental data
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Updated
Jul 23, 2019 - Python
Deep learning for forecasting company fundamental data
Calculates 103 firm characteristics from CRSP + Compustat directly in Python – no WRDS SAS cloud
A lightweight Claude Code project for exploring academic literature, brainstorming research ideas, and managing citations. Powered by Corbis MCP.
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.
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
Interactive research platform for volatility-surface reconstruction, Heston and GBM scenarios, and option-portfolio VaR/ES.
From-scratch replication of Loughran and McDonald (2011) — SEC 10-K sentiment analysis with the LM Master Dictionary, and Fama-MacBeth regressions on filing-period excess returns.
Replication code for "The Shape of Beta: Industry Factor Structure and Crisis Risk Premium" (Woo & Kim, 2026)
Minimal PEAD (post-earnings announcement drift) backtest using Wharton Research Data Services (IBES + CRSP) — Python pipeline for research & plots.
Academically rigorous implementation of the Fama-French (2015) five-factor model using WRDS (CRSP + Compustat) data.
Point-in-time asset-pricing pipeline linking Compustat geographic segments to macro states, CRSP returns, and leakage-aware ML diagnostics.
Point-in-time insider filing de-noising, ML scoring, and cross-sectional return tests.
Replication code for "The Dark Side of Connectivity: How Board Interlock Networks Are Associated with Accounting Risk Through Director Mobility" (Woo & Kim, 2026)
Reinforcement learning for alpha factor discovery, trained on executable backtests against WRDS (CRSP/TAQ) and crypto data.
Academically rigorous implementation of the Fama-French (1993) three-factor model using WRDS (CRSP + Compustat) data.
Option-implied tail-risk connectedness factor research pipeline
Replicate the Loughran and McDonald 2011 sentiment analysis study using 10-K filings and domain-specific financial dictionaries.
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