Dynamic Credit Quality Evaluation with Social Network Data

We investigate the filtering problem where the borrower’s time varying credit quality process is estimated using continuous time observation process and her (in this paper we refer to the borrower as female and the lender as male) ego-network data. The hidden credit quality is modeled as a hidden Ga...

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Main Authors: Stanley Sewe, Philip Ngare, Patrick Weke
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2019/8350464
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author Stanley Sewe
Philip Ngare
Patrick Weke
author_facet Stanley Sewe
Philip Ngare
Patrick Weke
author_sort Stanley Sewe
collection DOAJ
description We investigate the filtering problem where the borrower’s time varying credit quality process is estimated using continuous time observation process and her (in this paper we refer to the borrower as female and the lender as male) ego-network data. The hidden credit quality is modeled as a hidden Gaussian mean-reverting process whilst the social network is modeled as a continuous time latent space network model. At discrete times, the network data provides unbiased estimates of the current credit state of the borrower and her ego-network. Combining the continuous time observed behavioral data and network information, we provide filter equations for the hidden credit quality and show how the network information reduces information asymmetry between the borrower and the lender. Further, we consider the case when the network information arrival times are random and solve stochastic optimal control problem for a lender having linear quadratic utility function.
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institution Kabale University
issn 1110-757X
1687-0042
language English
publishDate 2019-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-a1133cb3b9ea41ffaf416a3c39a7ebaf2025-02-03T05:51:00ZengWileyJournal of Applied Mathematics1110-757X1687-00422019-01-01201910.1155/2019/83504648350464Dynamic Credit Quality Evaluation with Social Network DataStanley Sewe0Philip Ngare1Patrick Weke2Pan African University Institute for Basic Sciences, Technology and Innovation, KenyaPan African University Institute for Basic Sciences, Technology and Innovation, KenyaPan African University Institute for Basic Sciences, Technology and Innovation, KenyaWe investigate the filtering problem where the borrower’s time varying credit quality process is estimated using continuous time observation process and her (in this paper we refer to the borrower as female and the lender as male) ego-network data. The hidden credit quality is modeled as a hidden Gaussian mean-reverting process whilst the social network is modeled as a continuous time latent space network model. At discrete times, the network data provides unbiased estimates of the current credit state of the borrower and her ego-network. Combining the continuous time observed behavioral data and network information, we provide filter equations for the hidden credit quality and show how the network information reduces information asymmetry between the borrower and the lender. Further, we consider the case when the network information arrival times are random and solve stochastic optimal control problem for a lender having linear quadratic utility function.http://dx.doi.org/10.1155/2019/8350464
spellingShingle Stanley Sewe
Philip Ngare
Patrick Weke
Dynamic Credit Quality Evaluation with Social Network Data
Journal of Applied Mathematics
title Dynamic Credit Quality Evaluation with Social Network Data
title_full Dynamic Credit Quality Evaluation with Social Network Data
title_fullStr Dynamic Credit Quality Evaluation with Social Network Data
title_full_unstemmed Dynamic Credit Quality Evaluation with Social Network Data
title_short Dynamic Credit Quality Evaluation with Social Network Data
title_sort dynamic credit quality evaluation with social network data
url http://dx.doi.org/10.1155/2019/8350464
work_keys_str_mv AT stanleysewe dynamiccreditqualityevaluationwithsocialnetworkdata
AT philipngare dynamiccreditqualityevaluationwithsocialnetworkdata
AT patrickweke dynamiccreditqualityevaluationwithsocialnetworkdata