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Drawdown-based risk indicators for high-frequency financial volumes

Author

Listed:
  • Guglielmo D’Amico

    (Gabriele D’Annunzio University of Chieti-Pescara)

  • Bice Di Basilio

    (Gabriele D’Annunzio University of Chieti-Pescara)

  • Filippo Petroni

    (Gabriele D’Annunzio University of Chieti-Pescara)

Abstract

In stock markets, trading volumes serve as a crucial variable, acting as a measure for a security’s liquidity level. To evaluate liquidity risk exposure, we examine the process of volume drawdown and measures of crash-recovery within fluctuating time frames. These moving time windows shield our financial indicators from being affected by the massive transaction volume, a characteristic of the opening and closing of stock markets. The empirical study is conducted on the high-frequency financial volumes of Tesla, Netflix, and Apple, spanning from April to September 2022. First, we model the financial volume time series for each stock using a semi-Markov model, known as the weighted-indexed semi-Markov chain (WISMC) model. Second, we calculate both real and synthetic drawdown-based risk indicators for comparison purposes. The findings reveal that our risk measures possess statistically different distributions, contingent on the selected time windows. On a global scale, for all assets, financial risk indicators calculated on data derived from the WISMC model closely align with the real ones in terms of Kullback–Leibler divergence.

Suggested Citation

  • Guglielmo D’Amico & Bice Di Basilio & Filippo Petroni, 2024. "Drawdown-based risk indicators for high-frequency financial volumes," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-40, December.
    • Handle: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-023-00593-0
    DOI: 10.1186/s40854-023-00593-0
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    References listed on IDEAS

    as
    1. D’Amico, Guglielmo & Petroni, Filippo, 2012. "A semi-Markov model for price returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4867-4876.
    2. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
    3. Alexei Chekhlov & Stanislav Uryasev & Michael Zabarankin, 2005. "Drawdown Measure In Portfolio Optimization," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 13-58.
    4. Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    5. Cantor, Richard, 2001. "Moody's investors service response to the consultative paper issued by the Basel Committee on Bank Supervision "A new capital adequacy framework"," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 171-185, January.
    6. Guglielmo D’Amico & Bice Di Basilio & Filippo Petroni, 2020. "A Semi-Markovian Approach To Drawdown-Based Measures," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(08), pages 1-28, December.
    7. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    8. Martinez, Miguel A. & Nieto, Belen & Rubio, Gonzalo & Tapia, Mikel, 2005. "Asset pricing and systematic liquidity risk: An empirical investigation of the Spanish stock market," International Review of Economics & Finance, Elsevier, vol. 14(1), pages 81-103.
    9. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model with memory for price changes," Papers 1109.4259, arXiv.org, revised Dec 2011.
    10. Puneet Pasricha & Dharmaraja Selvamuthu & Guglielmo D’Amico & Raimondo Manca, 2020. "Portfolio optimization of credit risky bonds: a semi-Markov process approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-14, December.
    11. Guglielmo D'Amico & Filippo Petroni & Flavio Prattico, 2013. "Wind speed modeled as an indexed semi‐Markov process," Environmetrics, John Wiley & Sons, Ltd., vol. 24(6), pages 367-376, September.
    12. Hongzhong Zhang & Olympia Hadjiliadis, 2012. "Drawdowns and the Speed of Market Crash," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 739-752, September.
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