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Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model

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  • Orlando, Giuseppe
  • Bufalo, Michele

Abstract

In this paper, we suggest a deterministic approach for modelling credit risk time series even in distressed periods (including COVID-19). We examine the Moody’s Seasoned Aaa Corporate Bond Yield Relative to Yield on 10-Year Treasury Constant Maturity as well as the ICE BofA US High Yield Index Option-Adjusted Spread and we find that the proposed model could fit well the alternation between periods of low and high volatility. This result is compared to the ARIMA-EGARCH model to determine how a chaotic deterministic model stands with respect to a stochastic model expressly designed for handling moving average, autoregression, cointegration and heteroscedastic volatility. According to recent literature, we find that both models give comparable results.

Suggested Citation

  • Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321004888
    DOI: 10.1016/j.frl.2021.102599
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    Cited by:

    1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.
    2. Wanying Song & Jian Min & Jianbo Yang, 2023. "Credit Risk Assessment of Heavy-Polluting Enterprises: A Wide- ℓ p Penalty and Deep Learning Approach," Mathematics, MDPI, vol. 11(16), pages 1-19, August.
    3. Zhu, Ruihua & Chen, Fang, 2024. "Tax and financial credit risks—Empirical evidence from Chinese investment enterprises," Finance Research Letters, Elsevier, vol. 61(C).
    4. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
    5. Juan Meng & Bin Mo & He Nie, 2023. "The dynamics of crude oil future prices on China's energy markets: Quantile‐on‐quantile and casualty‐in‐quantiles approaches," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(12), pages 1853-1871, December.

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    More about this item

    Keywords

    Rulkov map; Credit risk; Chaos; COVID-19; ARIMA; GARCH;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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