Paper: arXiv 2507.13391

Authors: Abiodun Finbarrs Oketunji

Abstract

This research presents a framework for quantitative risk management in volatile markets, specifically focusing on expectile-based methodologies applied to the FTSE 100 index. Traditional risk measures such as Value-at-Risk (VaR) have demonstrated significant limitations during periods of market stress, as evidenced during the 2008 financial crisis and subsequent volatile periods. This study develops an advanced expectile-based framework that addresses the shortcomings of conventional quantile-based approaches by providing greater sensitivity to tail losses and improved stability in extreme market conditions. The research employs a dataset spanning two decades of FTSE 100 returns, incorporating periods of high volatility, market crashes, and recovery phases. Our methodology introduces novel mathematical formulations for expectile regression models, enhanced threshold determination techniques using time series analysis, and robust backtesting procedures. The empirical results demonstrate that expectile-based Value-at-Risk (EVaR) consistently outperforms traditional VaR measures across various confidence levels and market conditions. The framework exhibits superior performance during volatile periods, with reduced model risk and enhanced predictive accuracy. Furthermore, the study establishes practical implementation guidelines for financial institutions and provides evidence-based recommendations for regulatory compliance and portfolio management. The findings contribute significantly to the literature on financial risk management and offer practical tools for practitioners dealing with volatile market environments.

Complexity vs Empirical Score

  • Math Complexity: 6.0/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides a mathematically solid expectile regression framework to overcome VaR limitations, supported by extensive empirical testing on two decades of FTSE 100 data. It balances theoretical rigor with clear practical implementation guidelines for market risk assessment.

Research Flowchart

  flowchart TD
    A[Research Goal: Develop Expectile-Based Risk Framework for Volatile Markets] --> B[Data Input: 20 Years of FTSE 100 Daily Returns]
    B --> C[Methodology: Formulate Expectile Regression Models & Thresholds]
    C --> D[Computation: Compute Expectile Value-at-Risk EVaR & Backtesting]
    D --> E[Outcome: EVaR Outperforms Traditional VaR in Tail Risk & Stability]
    E --> F[Applications: Guidelines for Financial Institutions & Regulators]