A coupled Markov chain approach to credit risk modeling

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heuristic global optimization techniques.We benchmark the model against a GLMM model in the context of bond portfolio risk management. The proposed model yields stronger dependencies and higher risks than the GLMM model. As a result, the risk optimal portfolios are more conservative than the decisions resulting from the benchmark model.     

Overlapping portfolios,contagion, and financial stability

We study the problem of interacting channels of contagion in financial networks. The first channel of contagion is counterparty failure risk; this is captured empirically using data for the Austrian interbank network. The second channel of contagion is overlapping portfolio exposures; this is studied using a stylized model. We perform stress tests according to different protocols. For the parameters we study neither channel of contagion results in large effects on its own. In contrast, when both channels are active at once, bankruptcies are much more common and have large systemic effects.     

Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency

This paper analyzes the productivity of farms across 370 municipalities in the Center-West region of Brazil. A stochastic frontier model with a latent spatial structure is proposed to account for possible unknown geographical variation of the outputs. The paper compares versions of the model that include the latent spatial effect in the mean of output or as a variable that conditions the distribution of inefficiency, include or not observed municipal variables, and specify independent normal or conditional autoregressive priors for the spatial effects. The Bayesian paradigm is used to estimate the proposed models. As the resultant posterior distributions do not have a closed form, stochastic simulation techniques are used to obtain samples from them. Two model comparison criteria provide support for including the latent spatial effects, even after considering covariates at the municipal level. Models that ignore the latent spatial effects produce significantly different rankings of inefficiencies across agents.

A model of the topology of the bank – firm credit network and its role as channel of contagion

This paper proposes a stochastic model of a bipartite credit network between banks and the non-bank corporate sector that encapsulates basic stylized facts found in comprehensive data sets for bank-firm loans for a number of countries. When performing computational experiments with this model, we find that it shows a pronounced non-linear behavior under shocks: the default of a single unit will mostly have practically no knock-on effects, but might lead to an almost full-scale collapse of the entire system in a certain number of cases. The dependency of the overall outcome on firm characteristics like size or number of loans seems fuzzy. Distinguishing between contagion due to interbank credit and due to joint exposures to counterparty risk via loans to firms, the later channel appears more important for contagious spread of defaults.     

Quality control for structural credit risk models

Over the last four decades, a large number of structural models have been developed to estimate and price credit risk. The focus of the paper is on a neglected issue pertaining to fundamental shifts in the structural parameters governing default. We propose formal quality control procedures that allow risk managers to monitor fundamental shifts in the structural parameters of credit risk models. The procedures are sequential — hence apply in real time. The basic ingredients are the key processes used in credit risk analysis, such as most prominently the Merton distance to default process as well as financial returns. Moreover, while we propose different monitoring processes, we also show that one particular process is optimal in terms of minimal detection time of a break in the drift process and relates to the Radon–Nikodym derivative for a change of measure.     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

Geometrical Interpretation of the Mean and the Constant in a Box-Jenkins Time Series Model

Certain manuals and computer programs mistakenly identify the mean with the constant in Box-Jenkins time series models. In this paper, it will be shown that (a) the mean and the constant have different values in autoregressive models, and (b) they have an algebraic and graphical relationship.     

Past price ‘memory’ in the housing market: testing the performance of different spatio-temporal specifications

Recent methodological developments provide a way to incorporate the temporal dimension when accounting for spatial effects in hedonic pricing. Weight matrices should decompose the spatial effects into two distinct components: bidirectional contemporaneous spatial connections; and unidirectional spatio-temporal effects from past transactions. Our iterative estimation approach explicitly analyses the role of time in price determination. The results show that both spatio-temporal components should be included in model specification; past transaction information stops contributing to price determination after eight months; and limited temporal friction is exhibited within this period. These findings highlight the decidedly non-linear temporal patterns of such information effects.     

Behavioural heterogeneity and shift-contagion: Evidence from the Asian crisis

In this paper, we propose an empirical model based on the heterogeneous agents literature. Price changes are induced by fundamental, technical, and international factors. The model is estimated for Hong Kong and Thailand surrounding the Asian crisis. We find that the three sources are relevant and that their relative price impact fluctuates conditional on price impact in the previous period. Results imply that the crisis is triggered in Thailand due to an increased focus on the fundamental price, followed by an increase in chartism and finally aggravated by a focus on foreign developments. Furthermore, the crisis deepens in Hong Kong because of increased attention for foreign markets.     

The spillover effects of infill developments on local housing prices

This paper examines the spillover effects of infill developments, which involve developing vacant or under-used parcels within existing urban areas that are largely developed, on local housing prices. Employing a difference-in-difference specification on a sample of 275 new developments and 55,887 sale transactions of houses in Singapore, we find that infill developments have a positive and persistent impact on local housing prices. The contagion effect is larger for infill developments that are built on teardown sites. The spillover effect can also be traced to the overpricing of new homes by developers. Overall, the evidence indicates that developers act as price leaders and contribute significantly to price discovery in the local housing market.     

DO WE REALLY NEED BOTH BEKK AND DCC? A TALE OF TWO MULTIVARIATE GARCH MODELS

Abstract The management and monitoring of very large portfolios of financial assets are routine for many individuals and organizations. The two most widely used models of conditional covariances and correlations in the class of multivariate GARCH models are BEKK and dynamic conditional correlation (DCC). It is well known that BEKK suffers from the archetypal ‘curse of dimensionality’, whereas DCC does not. It is argued in this paper that this is a misleading interpretation of the suitability of the two models for use in practice. The primary purpose of this paper is to analyse the similarities and dissimilarities between BEKK and DCC, both with and without targeting, on the basis of the structural derivation of the models, the availability of analytical forms for the sufficient conditions for existence of moments, sufficient conditions for consistency and asymptotic normality of the appropriate estimators and computational tractability for ultra large numbers of financial assets. Based on theoretical considerations, the paper sheds light on how to discriminate between BEKK and DCC in practical applications.     

疾病诊断的概率模型

根据积累的资料,对各种疾病的验前概率及各种条件概率进行估算。在诸症状的一种具体组合已经出现的条件下,按贝叶斯公式计算出各种疾病在这种具体症状组合下发生的概率即验后概率。比较各疾病的验后概率,便可诊断患病类型。     

复杂产品研发项目技术风险识别研究

对复杂产品研发项目,本文综合运用核对表、解析结构模型与贝叶斯网络技术来完成技术风险的识别工作,为进一步量化研究技术风险发生的概率以及后果做好准备工作。此识别技术能够提高识别的效率与准确性。     

信用社担保贷款中的风险防范

着重探讨信用社风险必须从源头上警惕和防堵的问题。