Occurrence Of Default Research Articles

Stochastic evaluation of mortgage default losses resulting from flood damages and different mortgage arrangements for post-Katrina Louisiana houses

Purpose – The purpose of this paper is to investigate the total number of mortgage default occurrence possibilities and monetary damage amounts to the sampled properties due to the excessive flooding caused by natural disasters. Mortgage default loss assessments due to natural catastrophic events are of great interest to lenders, insurance firms, forensic engineering professionals, inspecting agencies and the federal and state government planning officials and risk-mitigating teams. Design/methodology/approach – In this study, a stochastic methodology is used to address the risk of mortgage default losses and the homeowners’ investment returns, given: damage severity levels of hurricane floods and the mortgage types and arrangements on selected properties. Nine different houses, with various mortgage arrangements, located in different flood damage zones were investigated three years after Hurricane Katrina. To quantify the flood damage risk values which are compared with exceeding damage probabilities, the Poisson’s distribution is used through performing random variable analysis walks for each property during each house’s mortgage life cycle. Findings – Henceforth, through introduction and constructing the “Zonal Damage Matrix” for the investigated houses, the total number of mortgage default occurrence possibilities and monetary damage amounts to the properties are calculated for each exceeding flood. Thereafter, the homeowners’ net equity values and the investment returns are estimated for risk identification and evaluation purposes. Originality/value – For each of the sampled houses, the probability of mortgage defaults and the homeowners’ net equity values are estimated using Poisson’s distribution based on 60,000 randomly generated numbers to construct ten different hazard-related default scenarios for each property over the 30-year mortgage life cycle. The investment returns are therefore estimated for risk identification and evaluation purposes.

An Evidence of Link between Default and Loss of Bank Loans from the Modeling of Competing Risks

In this paper we propose a method that provides a useful technique to compare relationship between risk involved that takes customer becomes defaulter and debt collection process that might make this defaulter recovered. Through estimation of competitive risks that lead to realization of the event of interest, we showed that there is a positive significant relation between the intensity of default and losses from defaulted loans in collection processes. To reach this goal, we investigate a competing risks model applied to whole credit risk cycle into a bank loans portfolio. We estimated competing causes related to occurrence of default, thereafter, comparing it with estimated competing causes that lead loans to write-off condition. In context of modeling competing risks, we used a specification of Poisson distribution for numbers from competing causes and Weibull distribution for failures times. The likelihood maximum estimation is used for parameters estimation and the model is applied to real data of personal loans.

Market Risk and Liquidity of the Risky Bonds

In this paper, we present effect of the liquidity on risky bonds pricing. The liquidity effect is represented by the adjustment to the single price format. We begin with bid-ask pricing format and it helps to observe effect of the liquidity on each step of pricing. In the first section, we present simplified scheme when default can occur only at maturity. Next, we present discrete time approximation for default occurrence.

Multiresolution Analysis Based Effective Diagnosis of Induction Motors

Problem statement: Effective detection and localization of unbalance voltage supply affecting an induction motor may be compromised in presence of additionnal noise. Approach: In order to overcome the non possibility of the default detection and localization in presence of noise, the use of the discrete wavelet transform and especially the MultiResolution Analysis algorithm, to remove efficiently the noise associated to the stator currents is proposed. Results: Simulation results show that the de-noised stator current is a good estimation of the non disturbed one. They show also that the default occurrence instant can be well detected starting from high frequency detail signal. Furthermore, the signal details which characterize the default are not smoothed and still characterize the default occurrence. Experimental results validate the de-noising approach efficiency and the effective unbalance detection considering the MRA technique. Conclusion: In this study, current signal denoising problem is studied in order to perform an effective detection of an unbalance voltage supply induction machine default. It can be deduced that the wavelet transform and particularly the MRA technique is a good and powerful solution for both non linear noise filtering and transient default detection. Both simulation and experimental results show clearly that the stator currents MRA allows not only to detect when the default appears but also helps to separate the useful signal from noise without affecting or suppressing the default transient information.

Examples of Migration Matrices Models and their Performance in Credit Risk Analysis

Credit risk models used in banks are based on probability models for occurrence of default. A vast class of the models used in practice (e.g., Credit Metrics) is based on the notion of intensity. In 1997 Jarrow applied Markov chain approach to analyze intensities. The key problem that arises is the selection of appropriate estimators. Within the Markov approach among the most frequently used estimators of a migration matrix are cohort and duration estimators. Migration matrices can also be obtained with help of statistical longitudinal models (GLMM) in which states (rating classes) in discrete time points are regarded as matched pairs. In this paper we compare Markov chain models and GLMM models and the influence of their application on bank portfolio evaluation.

Quantification of Counterparty Risk Via Bessel Bridges

We construct a dynamical credit model that can be calibrated exactly to CDS quotes. Modelling the default time as the first-passage time of a credit index process to the level zero, we show that the parameters of this credit index process can be chosen such that the risk-neutral (implied) distribution of the time of default is matched. Employing this default model we develop a model for asset prices conditional on the occurrence of default at a given time. We illustrate the use of the model in estimating the expected positive exposure of an oil swap traded with an airline as counterparty.

Manajemen Risiko dalam Prinsip Pembiayaan Mudarabah: Kajian Kontekstual Islam terhadap Risiko

Risk management is one tool that can be used by companies to minimize the level of losses that are likely to occur or experienced by the company. Mudarabah is one form of cooperation in the field of finance which is based on the belief that financial trusts and investment trusts, moral hazard is one factor the risk faced by banking when they are confronted with a customer in the contract. The asymmetry of information provides opportunities for moral hazard and the occurrence of defaults that have a direct impact thelikelihood of losses for the company.

Business Time and New Credit Risk Models

This paper examines a new model of credit risk measurement, the Variance Gamma- Merton one, which seems to be adequate for describing single default occurrence and default correlation in turbulent times. It is based on the notion of business time. Business time runs faster than calendar time when the market is very active and a lot of information arrives; it runs at a slower pace than calendar time when few information arrives. We report a calibration to USA spread data, which shows the accurateness of the model at the single default level; we also compare the performance with a traditional structural model at the joint default level.

The Cost of Delay in a Mortgage/Credit Loan Portfolio

Using an actuarial model, we examine the cost of delay in mortgage/credit loan payments. It is assumed that the default arrival process follows the Poisson process and the loss sizes are assumed to be independent and an identical truncated exponential. We also assume that the delay between default occurrence and partially (or fully) recovered payment is an independent identical truncated exponential random variable. For the recovery rate random variable, we simply use its expectation. Using the relationship between the shot noise process and accumulated/discounted aggregate losses process and applying the piecewise deterministic Markov processes theory, we obtain the explicit expressions for the expected value of losses and the expected value of part (or whole) of the loan recovered with the delay. Based on these moments, we define and predict the cost of delay in a mortgage/credit loan portfolio and their numerical examples are provided.

Modeling Default Data Via an Interactive Hidden Markov Model

In this paper, we first introduce the use of an interactive hidden Markov model (IHMM) for modeling and analyzing default data in a sector. Under the IHMM, transitions of the hidden risk states of the sector depend on the observed number of bonds in the sector that default in the current time period. This incorporates the feedback effect of the number of defaults on the transitions of the hidden risk states. This feature seems to be more realistic and does not enjoy by the traditional HMMs. We then develop a “dynamic” version of the binomial expansion technique (BET) modulated by the IHMM for modeling the occurrence of defaults of bonds issued by firms in the same sector. Under the BET modulated by the IHMM, the number of bonds defaulting in each time period follows a Markov-modulated binomial distribution with the probability of defaulting of each bond depending on the states of the IHMM, which represent the hidden risk states of the sector. Efficient method will be presented for estimating the model parameters in the BET modulated by the IHMM. We shall compare the hidden risk state process extracted from the IHMM-modulated BET with that extracted from the BET modulated by HMM in order to illustrate the significance of the feedback effect using real data. We shall also present the estimation results for the BET modulated by the IHMM and compare them with those for the BET modulated by the HMM.

The Cost of Delay in a Mortgage/Credit Loan Portfolio

Using an actuarial model, we examine the cost of delay in mortgage/credit loan payments. It is assumed that the default arrival process follows the Poisson process and the loss sizes are assumed to be independent and an identical truncated exponential. We also assume that the delay between default occurrence and partially (or fully) recovered payment is an independent identical truncated exponential random variable. For the recovery rate random variable, we simply use its expectation. Using the relationship between the shot noise process and accumulated/discounted aggregate losses process and applying the piecewise deterministic Markov processes theory, we obtain the explicit expressions for the expected value of losses and the expected value of part (or whole) of the loan recovered with the delay. Based on these moments, we define and predict the cost of delay in a mortgage/credit loan portfolio and their numerical examples are provided.

Estimating Default Probabilities of CMBS Loans with Clustering and Heavy Censoring

This paper provides a comprehensive default estimation of commercial real estate loans with a complete commercial mortgage backed securites (CMBS) loan history database. Standard survival models assume that eventually every observation will experience the event. However, often there is a high proportion of censored observation in the sample. A mixture model is proposed to disentangle the probability of long-term survivorship and the timing of default occurrence. Loans within the same geographical area and property type tend to exhibit correlation in default incidence. A multilevel model is proposed to capture this correlation within and between clusters.

Some short elements on hedging credit derivatives

In practice, it is well known that hedging a derivative instrument can never be perfect. In the case of credit derivatives (e.g. synthetic CDO tranche products), a trader will have to face some specific difficulties. The first one is the inconsistence between most of the existing pricing models, where the risk is the occurrence of defaults, and the real hedging strategy, where the trader will protect his portfolio against small CDS spread movements. The second one, which is the main subject of this paper, is the consequence of a wrong estimation of some parameters specific to credit derivatives such as recovery rates or correlation coefficients. We find here an approximation of the distribution under the historical probability of the final Profit & Loss of a portfolio hedged with wrong estimations of these parameters. In particular, it will depend on a ratio between the square root of the historical default probability and the risk-neutral default probability. This result is quite general and not specific to a given pricing model.

Psychological Contract Violation in Online Marketplaces: Antecedents, Consequences, and Moderating Role

This study examines the nature and role of Psychological Contract Violation (PCV) in online marketplaces, a critical factor that has been largely overlooked by previous research. Applied to buyer-seller relationships, PCV is defined as a buyer’s perception of having being treated wrongly regarding the terms of an exchange agreement with an individual seller. PCV with individual sellers is proposed as a formative first-order construct driven by the occurrence of fraud, product misrepresentation, contract default, delivery delay, and failure to follow product guarantees and payment policies. PCV with an individual seller is proposed to prompt a generalized perception of PCV with the entire community of sellers in a marketplace. PCV with the community of sellers is hypothesized to negatively affect buyer transaction behavior in a marketplace by directly impacting transaction intentions, price premiums, trust, perceived risk, and the perceived effectiveness of institutional structures. PCV is also hypothesized to act as a moderator, transforming the buyers’ initial trust-based mindset to one more centered on perceived risk. Finally, PCV is hypothesized to attenuate the positive impact of trust on transaction intentions, while reinforcing the negative impact of perceived risk on transaction intentions. It is also proposed to attenuate the impact of the perceived effectiveness of institutional structures on trust, while strengthening its negative effect on perceived risk. As a means of preventing PCV, the buyers’ positive experience and the sellers’ favorable past performance are hypothesized to make PCV with the community of sellers less likely. A combination of primary and secondary longitudinal data from 404 buyers in eBay’s and Amazon’s online auctions support the proposed hypotheses, validating PCV as a central element of buyer-seller relationships in online marketplaces. Interestingly, ex post facto results show that buyers with higher perceptions of PCV with the community of sellers are less likely to experience PCV with an individual seller in the future. Implications for buyer-seller relationships in online marketplaces and the PCV literature are discussed. Also discussed is how the increasing number of buyers who experience PCV in online marketplaces extends the literature that has been largely developed based on buyers who had not experienced PCV.

Debt renegotiation with incomplete contract

A debt contract usually does not include a provision about renegotiation. The right to seize the borrower’s asset and the rules of this process are usually stipulated in the contract. Such a promise not to renegotiate is not credible since renegotiation can mitigate the dead-weight loss of liquidating insolvent borrowers. Once the initial contract may not consider the renegotiation procedure and renegotiation may occur, this paper investigates why a complete contract is not offered. It shows that the lender does not need to stipulate the renegotiation procedure on the initial contract because he is indifferent about committing or not to the terms of a contract. This indicates that a complete contract gives the lender the same expected return as an incomplete contract, in which the renegotiation process is determined after the occurrence of default.

Analysis of default data using hidden Markov models

The occurrence of defaults within a bond portfolio is modelled as a simple hidden Markov process. The hidden variable represents the risk state, which is assumed to be common to all bonds within one particular sector and region. After describing the model and recalling the basic properties of hidden Markov chains, we show how to apply the model to a simulated sequence of default events. Then, we consider a real scenario, with default events taken from a large database provided by Standard & Poor's. We are able to obtain estimates for the model parameters and also to reconstruct the most likely sequence of the risk state. Finally, we address the issue of global versus industry-specific risk factors. By extending our model to include independent hidden risk sequences, we can disentangle the risk associated with the business cycle from that specific to the individual sector.

The End: A New Indicator of Financial and Nonfinancial Corporate Sector Vulnerability

This paper describes a corporate sector vulnerability indicator, the expected number of defaults (END), based on the joint occurrence of defaults among a number of firms and/or institutions. The END indicator is general enough to assess systemic risk in the corporate and financial sectors, as well as systemic sovereign risk; and is also forward looking as it is constructed using information implied by financial securities prices. Using equity prices and balance-sheet data, we calculate the END to assess systemic risk in the corporate sector in Korea, Malaysia, and Thailand. We also discuss how the END systemic risk indicator overcomes some of the shortcomings of other vulnerability indicators.

The End: A New Indicator of Financial and Nonfinancial Corporate Sector Vulnerability

This paper describes a corporate sector vulnerability indicator, the expected number of defaults (END), based on the joint occurrence of defaults among a number of firms and/or institutions. The END indicator is general enough to assess systemic risk in the corporate and financial sectors, as well as systemic sovereign risk; and is also forward looking as it is constructed using information implied by financial securities prices. Using equity prices and balance-sheet data, we calculate the END to assess systemic risk in the corporate sector in Korea, Malaysia, and Thailand. We also discuss how the END systemic risk indicator overcomes some of the shortcomings of other vulnerability indicators.

Fundamental Properties of Bond Prices in Models of the Short-Term Rate

This paper develops restrictions that arbitrage-constrained bond prices impose on the short-term rate process in order to be consistent with given dynamic properties of the term-structure of interest rates. The central focus is the relationship between bond prices and the short-term rate volatility. In both scalar and multidimensional diffusion settings, typical relationships between bond prices and volatility are generated by joint restrictions on the risk-neutralized drift functions of the state variables and convexity of bond prices with respect to the short-term rate. The theory is illustrated by several examples and is partially extended to accommodate the occurrence of jumps and default.

Fundamental Properties of Bond Prices in Models of the Short-Term Rate

This article develops restrictions that arbitrage-constrained bond prices impose on the short-term rate process in order to be consistent with given dynamic properties of the term structure of interest rates. The central focus is the relationship between bond prices and the short-term rate volatility. In both scalar and multidimensional diffusion settings, typical relationships between bond prices and volatility are generated by joint restrictions on the risk-neutralized drift functions of the state variables and convexity of bond prices with respect to the short-term rate. The theory is illustrated by several examples and is partially extended to accommodate the occurrence of jumps and default. A standard approach to modeling the term structure of interest rates is to derive sets of arbitrage-free bond prices using as an input an exogenously given short-term rate process [see, e.g., Vasicek (1977) and Cox, Ingersoll, and Ross (1985)]. While this approach is widely used, there is no theoretically sound work establishing systematic answers to such fundamental questions as: When are bond prices a decreasing function of the shortterm rate? When are bond prices a convex function of the short-term rate? Are bond prices a decreasing function of the short-term rate volatility? This article demonstrates that it is possible to develop results addressing these questions in relation to all sets of economically admissible (i.e., noarbitrage) bond prices.