Replicate Post-Earnings Announcement Drift (PEAD)
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Updated
Aug 6, 2022 - Stata
Replicate Post-Earnings Announcement Drift (PEAD)
🏆 1st Place — 2026 UMN FMA Quant Trading Competition. Event-driven PEAD equity trading bot. Live-traded on Alpaca with 0.00% max drawdown.
Quant research engine and autonomous paper-trading bot for post-earnings drift (PEAD). Pre-registered tests, bias audits, risk-gated execution.
Minimal PEAD (post-earnings announcement drift) backtest using Wharton Research Data Services (IBES + CRSP) — Python pipeline for research & plots.
Auditable earnings-call PEAD pipeline using FinBERT, event-date-filtered financial features, and chronological model validation.
This repository explores whether earnings surprises predict stock returns in US markets (2000–2023). 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.
Event study of post-earnings announcement drift on US equities: surprise measurement, abnormal return windows, corrected inference, and a costed backtest.
Check event backtests for look-ahead: time earnings releases from SEC EDGAR 8-K acceptance times, and check that price bars sit on their target days.
코스피·코스닥 알파 심사 프레임워크 — 개별 트레이드 분포로 판정하고 랜덤 음성대조·purged CV·Deflated Sharpe 를 CI 가드레일로 강제. 기각 판정문까지 공개한다 · Alpha validation framework for KOSPI/KOSDAQ
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