Replicate Post-Earnings Announcement Drift (PEAD)
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Aug 6, 2022 - Stata
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pead
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This repository explores whether earnings surprises predict stock returns in US markets (2000β2023). It uses an event study approach and tests for abnormal returns under different asset pricing models. It also runs regressions to see if earnings surprises predict returns beyond firm-specific factors.
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Oct 13, 2025 - Jupyter Notebook
Minimal PEAD (post-earnings announcement drift) backtest using Wharton Research Data Services (IBES + CRSP) β Python pipeline for research & plots.
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Sep 4, 2025 - Python
π 1st Place β 2026 UMN FMA Quant Trading Competition. Event-driven PEAD equity trading bot. Live-traded on Alpaca with 0.00% max drawdown.
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Jun 22, 2026 - Jupyter Notebook
Alpha validation framework for KOSPI/KOSDAQ β trade-level distributions, random null controls, purged CV, deflated Sharpe and survivorship-corrected universes, all enforced by CI. Ships the judging machine and 5 honest verdicts (4 rejections) Β· νκ΅ μ£Όμ μν κ²μ¦ νλ μμν¬
python pandas quant quantitative-finance backtesting point-in-time overfitting supply-demand research-reproducibility negative-results kospi kosdaq alpha-research walk-forward pead korean-stocks survivorship-bias backtest-overfitting deflated-sharpe purged-cross-validation
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Aug 17, 2026 - Python
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