Filtering in a hazard rate change-point model with financial and life-insurance applications

TL;DR

This paper introduces a continuous-time filtering approach for estimating hazard rates with unobservable change-points, applicable to financial and insurance contexts, enabling better risk assessment and pricing of credit-sensitive instruments.

Contribution

It develops a novel filtering framework using filtration enlargement to estimate hazard rate change-points and derive explicit survival probabilities under partial information.

Findings

The filter is characterized as a unique strong solution to a stochastic differential equation.

Partial information causes delayed hazard rate updates and potential mispricing.

Explicit formulas for survival probabilities improve credit instrument valuation.

Abstract

This paper develops a continuous-time filtering framework for estimating a hazard rate subject to an unobservable change-point. This framework naturally arises in both financial and insurance applications, where the default intensity of a firm or the mortality rate of an individual may experience a sudden jump at an unobservable time, representing, for instance, a shift in the firm's risk profile or a deterioration in an individual's health status. By employing a progressive enlargement of filtration, we integrate noisy observations of the hazard rate with default-related information. We characterise the filter, i.e. the conditional probability of the change-point given the information flow, as the unique strong solution to a stochastic differential equation driven by the innovation process enriched with the discontinuous component. A sensitivity analysis and a comparison of the filter's behaviour under various information structures are provided. Our framework further allows for the derivation of an explicit formula for the survival probability conditional on partial information. This result applies to the pricing of credit-sensitive financial instruments such as defaultable bonds, credit default swaps, and life insurance contracts. Finally, a numerical analysis illustrates how partial information leads to delayed adjustments in the estimation of the hazard rate and consequently to mispricing of credit-sensitive instruments when compared to a full-information setting.