Copula-based deviation measure of cointegrated financial assets

ArXiv ID: 2312.02081 “View on arXiv”

Authors: Unknown

Abstract

This study outlines a comprehensive methodology utilizing copulas to discern inconsistencies in the behavior exhibited by pairs of financial assets. It introduces a robust approach to establishing the interrelationship between the returns of these assets, exploring potential measures of dependence among the stochastic variables represented by these returns. Special emphasis is placed on scrutinizing the traditional measure of dependence, namely the correlation coefficient, delineating its limitations. Furthermore, the study articulates an alternative methodology that offers enhanced stability and informativeness in appraising the relationship between financial instrument returns.

Keywords: Copulas, Dependence modeling, Pair trading, Correlation analysis, Financial time series, Equities (General)

Complexity vs Empirical Score

• Math Complexity: 8.0/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats
• Why: The paper presents advanced mathematical concepts involving copulas, distribution theory, and theoretical properties, resulting in high mathematical complexity. However, it focuses on theoretical methodology and limitations of existing measures without providing empirical backtests, specific datasets, or implementation details for trading.

  flowchart TD
    A["Research Goal<br>Identify inconsistencies in<br>financial asset pairs"] --> B["Data: Historical Price Series<br>of Paired Financial Assets"]
    
    B --> C["Methodology: Copula-Based Analysis<br>vs. Traditional Correlation"]
    
    C --> D["Compute Returns<br>Stochastic Variables"]
    C --> E["Estimate Copula<br>Dependence Structure"]
    
    D --> F["Computational Process<br>Calculate Cointegration<br>& Deviation Measures"]
    E --> F
    
    F --> G["Outcome: Robust Detection<br>of Divergence/Inconsistency"]
    
    G --> H["Key Finding<br>Enhanced Stability & Insight<br>for Pair Trading Strategies"]