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New Time Series Models for Corporate Bond Log Yields

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  • Jihyun Park
  • Andrey Sarantsev

Abstract

We propose a class of simple time series models for rates and spreads of portfolios of corporate bonds classified by ratings provided by Bank of America. We evaluate these models based on statistical analysis of innovations: Whether they are independent identically distributed. Our tests are unusually rigorous, compared with standard practice, Our novelty is taking logarithms of rates or spreads instead of rates or spreads themselves. We find out that the best option is to take logarithms of spreads of logarithms of rates. Sometimes, dividing these innovations by the volatility index for stocks makes them pass our statistical tests. It is remarkable that stock volatility can also serve as bond volatility.

Suggested Citation

  • Jihyun Park & Andrey Sarantsev, 2024. "New Time Series Models for Corporate Bond Log Yields," Papers 2410.22498, arXiv.org, revised Jul 2026.
    • Handle: RePEc:arx:papers:2410.22498
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    1. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    2. Stephen J. Taylor, 1994. "Modeling Stochastic Volatility: A Review And Comparative Study," Mathematical Finance, Wiley Blackwell, vol. 4(2), pages 183-204, April.
    3. Stein, Elias M & Stein, Jeremy C, 1991. "Stock Price Distributions with Stochastic Volatility: An Analytic Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 727-752.
    4. Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L., 2020. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1318-1328.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    7. Shephard, Neil (ed.), 2005. "Stochastic Volatility: Selected Readings," OUP Catalogue, Oxford University Press, number 9780199257201.
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