Credit Risk Modeling With Misreporting and Incomplete Information

Abstract

We propose a structural model for the valuation of defaultable securities of a firm which models the effect of deliberate misreporting done by insiders in the firm and unobserved by others. We derive exact formulas for equity and bond prices and approximate expressions for the conditional default probability, recovery rate, and credit spread under the proposed credit risk framework. We propose a novel estimation approach to structural model estimation which accounts for noisy observed asset values. We apply the proposed method to calibrate a simple version of our model to the case of Parmalat and show that the model is able to recover a certain amount of misreporting during the years of accounting irregularities.

A calibration method for structural models of credit risk with reporting bias

“…It has been shown in [3] that, under the above setting, the pricing formulas for bond and equity are respectively given by…”

“…In [4] and [9], the authors present a framework in which the market is assumed to only partially observe, and possibly with a lag, relevant information concerning the state of the firm. We present a novel calibration methodology for a simple version of the credit model with reporting bias developed by the authors in [3]. Such methodology uses a set of balance sheet indicators and stock market prices to recover maximum likelihood parameter estimates.…”

“…Section II defines a simple version of the credit risk model with reporting bias developed in [3] and presents the pricing formulas for equity and bonds. Section III contains the main contribution of the paper which consists of a novel calibration methodology.…”

Optimal contracting with effort and misvaluation

“…Our setting also accounts for the fact that manager and shareholders do not observe the outcome process directly. Following evidence that accounting reports are typically contaminated by accounting noise (see also the models of Duffie and Lando (2001) and Capponi and Cvitanić (2009)), we assume that the manager and the shareholders can only observe a white noise contaminated version of the actual output. Moreover, while managerial effort cannot be directly contracted upon by the principal, she can either observe it or compute it correctly in equilibrium.…”

Stochastic filtering in jump systems with state dependent mode transitions

“…Applications of these type of systems can be found in target tracking [11], change point detection [2] and financial engineering [7]. A specific class of these systems is the class of jump Markovian systems.…”