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Approximating intractable short ratemodel distribution with neural network

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  • Anna Knezevic
  • Nikolai Dokuchaev

Abstract

We propose an algorithm which predicts each subsequent time step relative to the previous timestep of intractable short rate model (when adjusted for drift and overall distribution of previous percentile result) and show that the method achieves superior outcomes to the unbiased estimate both on the trained dataset and different validation data.

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  • Anna Knezevic & Nikolai Dokuchaev, 2019. "Approximating intractable short ratemodel distribution with neural network," Papers 1912.12615, arXiv.org, revised Apr 2024.
    • Handle: RePEc:arx:papers:1912.12615
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    1. BALLY Vlad & TALAY Denis, 1996. "The Law of the Euler Scheme for Stochastic Differential Equations: II. Convergence Rate of the Density," Monte Carlo Methods and Applications, De Gruyter, vol. 2(2), pages 93-128, December.
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