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Liquidity Spectrum: Unraveling Theoretical Frameworks and Leveraging Modeling Algorithms for In-Depth Insights into Overall and Relative Liquidity Risk Dynamics

In: Liquidity Dynamics and Risk Modeling

Author

Listed:
  • Mazin A. M. Al Janabi

    (Calle Maranon 16)

Abstract

This chapter critically examines the assessment of trading risk under illiquid market conditions, a crucial consideration for financial institutions striving to meet regulatory requirements such as those outlined in the Basel capital adequacy accords. With a specific focus on emerging financial markets, the chapter aims to look into the intricacies of asset liquidity risk and its implications for portfolio management. The primary objective is to derive Liquidity-Adjusted Value-at-Risk (L-VaR) estimates for a range of equity portfolios, recognizing the increasing importance of such risk measures in contemporary financial landscapes. To achieve this, the chapter adopts a comprehensive approach, integrating three distinct asset liquidity models within a multivariate framework. In addition to these models, the chapter employs the GARCH-M (1,1) method to estimate expected returns and conditional volatility, providing a nuanced understanding of risk dynamics under various market conditions. Through rigorous analysis of more than six years of daily return data from emerging Gulf Cooperation Council (GCC) stock markets, the study uncovers notable insights. Among the key findings is the critical influence of the selected internal liquidity model on L-VaR statistics, particularly evident in scenarios involving short-sales of stocks and extreme correlation factors among trading assets. The chapter highlights the significance of accounting for extreme correlations, especially when correlations exhibit significant fluctuations or approach unity. By offering real-world asset allocation tactics tailored for portfolios operating in adverse market conditions, the chapter addresses a notable gap in risk management literature. Through its exploration of L-VaR estimation techniques and their implications for portfolio risk management, this study provides valuable insights for practitioners navigating the complexities of contemporary financial markets.

Suggested Citation

  • Mazin A. M. Al Janabi, 2024. "Liquidity Spectrum: Unraveling Theoretical Frameworks and Leveraging Modeling Algorithms for In-Depth Insights into Overall and Relative Liquidity Risk Dynamics," Springer Books, in: Liquidity Dynamics and Risk Modeling, chapter 0, pages 453-538, Springer.
  • Handle: RePEc:spr:sprchp:978-3-031-71503-7_7
    DOI: 10.1007/978-3-031-71503-7_7
    as

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