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Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models
[Pricing the Term Structure with Linear Regressions]

Author

Listed:
  • Marcello Pericoli
  • Marco Taboga

Abstract

We propose a general method for the Bayesian estimation of a very broad class of non-linear no-arbitrage term-structure models. The main innovation we introduce is a computationally efficient method, based on deep learning techniques, for approximating no-arbitrage model-implied bond yields to any desired degree of accuracy. Once the pricing function is approximated, the posterior distribution of model parameters and unobservable state variables can be estimated by standard Markov Chain Monte Carlo methods. As an illustrative example, we apply the proposed techniques to the estimation of a shadow-rate model with a time-varying lower bound and unspanned macroeconomic factors.

Suggested Citation

  • Marcello Pericoli & Marco Taboga, 2022. "Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models [Pricing the Term Structure with Linear Regressions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(5), pages 807-838.
    • Handle: RePEc:oup:jfinec:v:20:y:2022:i:5:p:807-838.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbaa037
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    References listed on IDEAS

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    Cited by:

    1. Andrea Colabella, 2019. "Do the ECB’s monetary policies benefit emerging market economies? A GVAR analysis on the crisis and post-crisis period," Temi di discussione (Economic working papers) 1207, Bank of Italy, Economic Research and International Relations Area.
    2. Giuseppe Grande & Adriana Grasso & Gabriele Zinna, 2019. "The effectiveness of the ECB’s asset purchases at the lower bound," Questioni di Economia e Finanza (Occasional Papers) 541, Bank of Italy, Economic Research and International Relations Area.
    3. Andrea Colabella, 2021. "Do ECB's Monetary Policies Benefit EMEs? A GVAR Analysis on the Global Financial and Sovereign Debt Crises and Postcrises Period," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 472-494, April.

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    More about this item

    Keywords

    approximation methods; deep learning; shadow rate models; yield curve;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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