Earnings Momentum and Quality Strategy (EMQ)
The project investigates how behavioral biases like the disposition effect and delayed market reactions create mispricing opportunities in financial markets. We developed an investment strategy that combines earnings momentum with quality factors to generate alpha.
Economic Concept:
Based on post-earnings drift, the strategy leverages the idea that market participants are slow to update expectations after earnings announcements. Behavioral biases lead to underreaction, allowing for predictable price movements.
Implementation:
Earnings Momentum: Used SUE (Standardized Unexpected Earnings) and CAR3 (Cumulative Abnormal Returns) metrics to capture earnings surprises.
Quality Factors: Incorporated metrics like Profitability Z-Score and Altman Z-Score to ensure earnings growth was backed by strong fundamentals.
Key Results:
The long-short strategy yielded statistically significant alphas, driven largely by short positions. Adding a “Safety” signal refined the strategy, although its impact was less pronounced.
Tool Used:
- Python
Explore the project on GitHub