Instant Exchange Analytics: A Compelling Mathematical Model for Real-Time Debt Instrument and Cash Conversion Rates

Authors

  • Wichai Witayakiattilerd Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, Thailand.
  • Kammanai Phothong Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, Thailand
  • Kanticha Sudtinont Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, Thailand
  • Panisara Bundasak Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, Thailand

Keywords:

Zero-coupon bond pricing, maximum likelihood estimation, stochastic interest rate models

Abstract

This research investigates a model for determining instantaneous debt instrument prices for converting debt securities into cash over time. The study employs three interest rate models: Vasicek, Cox-Ingersoll-Ross, and Hull-White, using historical daily treasury bill interest rates from January 2004 to October 2020. The findings suggest that the Hull-White model outperforms the Vasicek and Cox-Ingersoll-Ross models, simulating interest rates for determining debt-to-cash exchange rates. Additionally, a real-time continuous debt-to-cash conversion prototype is developed using zero-coupon government bonds with maturities of no more than 10 years, traded in the Thai secondary debt market as a case study.

References

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Published

2024-03-31

How to Cite

Witayakiattilerd, W. ., Phothong, K. ., Sudtinont, K. ., & Bundasak, P. . (2024). Instant Exchange Analytics: A Compelling Mathematical Model for Real-Time Debt Instrument and Cash Conversion Rates . Thailand Statistician, 22(2), 390–406. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/253431

Issue

Vol. 22 No. 2 (2024): April

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.