Replication of Reference-Dependent Preferences and the Risk-Return Trade-Off in the Chinese Market

ArXiv ID: 2505.20608 “View on arXiv”

Authors: Penggan Xu

Abstract

This study replicates the findings of Wang et al. (2017) on reference-dependent preferences and their impact on the risk-return trade-off in the Chinese stock market, a unique context characterized by high retail investor participation, speculative trading behavior, and regulatory complexities. Capital Gains Overhang (CGO), a proxy for unrealized gains or losses, is employed to explore how behavioral biases shape cross-sectional stock returns in an emerging market setting. Utilizing data from 1995 to 2024 and econometric techniques such as Dependent Double Sorting and Fama-MacBeth regressions, this research investigates the interaction between CGO and five risk proxies: Beta, Return Volatility (RETVOL), Idiosyncratic Volatility (IVOL), Firm Age (AGE), and Cash Flow Volatility (CFVOL). Key findings reveal a weaker or absent positive risk-return relationship among high-CGO firms and stronger positive relationships among low-CGO firms, diverging from U.S. market results, and the interaction effects between CGO and risk proxies, significant and positive in the U.S., are predominantly negative in the Chinese market, reflecting structural and behavioral differences, such as speculative trading and diminished reliance on reference points. The results suggest that reference-dependent preferences play a less pronounced role in the Chinese market, emphasizing the need for tailored investment strategies in emerging economies.

Keywords: Reference-Dependent Preferences, Capital Gains Overhang, Cross-Sectional Regression, Behavioral Finance, Emerging Markets, Equities

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail
• Why: The paper employs advanced econometric techniques (dependent double sorting, Fama-MacBeth regressions) with multiple risk proxies and complex formulas for reference price and CGO, leading to high mathematical density. It also demonstrates high empirical rigor through extensive data coverage (1995-2024), detailed data preprocessing, and explicit backtesting-ready portfolio construction methodology.

  flowchart TD
    A["Research Goal: <br>Replicate Reference-Dependent Preferences & Risk-Return Trade-Off in Chinese Market"] --> B["Data: China A-Share Stocks 1995-2024"]
    B --> C["Methodology: <br>Dependent Double Sorting & Fama-MacBeth Regressions"]
    C --> D["Compute Variables: <br>CGO, Beta, RETVOL, IVOL, AGE, CFVOL"]
    D --> E["Analysis: <br>Test Risk-Return Relationship across CGO Quintiles"]
    E --> F["Key Outcomes: <br>1. Weaker Risk-Return Link in High-CGO Firms<br>2. Interaction Effects Negative vs. US Positive<br>3. Lower Reliance on Reference Points in China"]