Analyzing the profit-loss sharing contracts with Markov model

The purpose of this paper is to examine how to use first order Markov chain to build a reliable monitoring system for the profit-loss sharing based contracts (PLS) as the mode of financing contracts in Islamic bank with censored continuous-time observations. The paper adopts the longitudinal analysi...

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Main Authors: Imam Wahyudi, Ali Sakti
Format: Article
Language:English
Published: Komunitas Ilmuwan dan Profesional Muslim Indonesia 2016-12-01
Series:Communications in Science and Technology
Subjects:
Online Access:https://cst.kipmi.or.id/index.php/cst/article/view/17/13
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spelling doaj-5b0b6bbdef36466ab90e50bdd17edf0d2020-11-24T23:19:50ZengKomunitas Ilmuwan dan Profesional Muslim IndonesiaCommunications in Science and Technology2502-92582502-92662016-12-0112788810.21924/cst.1.2.2016.17Analyzing the profit-loss sharing contracts with Markov modelImam Wahyudi0Ali Sakti1Department of Management, Faculty of Economics and Business, Universitas IndonesiaBank IndonesiaThe purpose of this paper is to examine how to use first order Markov chain to build a reliable monitoring system for the profit-loss sharing based contracts (PLS) as the mode of financing contracts in Islamic bank with censored continuous-time observations. The paper adopts the longitudinal analysis with the first order Markov chain framework. Laplace transform was used with homogenous continuous time assumption, from discretized generator matrix, to generate the transition matrix. Various metrics, i.e.: eigenvalue and eigenvector were used to test the first order Markov chain assumption. Cox semi parametric model was used also to analyze the momentum and waiting time effect as non-Markov behavior. The result shows that first order Markov chain is powerful as a monitoring tool for Islamic banks. We find that waiting time negatively affected present rating downgrade (upgrade) significantly. Likewise, momentum covariate showed negative effect. Finally, the result confirms that different origin rating have different movement behavior. The paper explores the potential of Markov chain framework as a risk management tool for Islamic banks. It provides valuable insight and integrative model for banks to manage their borrower accounts. This model can be developed to be a powerful early warning system to identify which borrower needs to be monitored intensively. Ultimately, this model could potentially increase the efficiency, productivity and competitiveness of Islamic banks in Indonesia. The analysis used only rating data. Further study should be able to give additional information about the determinant factors of rating movement of the borrowers by incorporating various factors such as contract-related factors, bank-related factors, borrower-related factors and macroeconomic factors.https://cst.kipmi.or.id/index.php/cst/article/view/17/13profit-loss sharingIslamic bankingdefault riskMarkov modelsurvival rate
collection DOAJ
language English
format Article
sources DOAJ
author Imam Wahyudi
Ali Sakti
spellingShingle Imam Wahyudi
Ali Sakti
Analyzing the profit-loss sharing contracts with Markov model
Communications in Science and Technology
profit-loss sharing
Islamic banking
default risk
Markov model
survival rate
author_facet Imam Wahyudi
Ali Sakti
author_sort Imam Wahyudi
title Analyzing the profit-loss sharing contracts with Markov model
title_short Analyzing the profit-loss sharing contracts with Markov model
title_full Analyzing the profit-loss sharing contracts with Markov model
title_fullStr Analyzing the profit-loss sharing contracts with Markov model
title_full_unstemmed Analyzing the profit-loss sharing contracts with Markov model
title_sort analyzing the profit-loss sharing contracts with markov model
publisher Komunitas Ilmuwan dan Profesional Muslim Indonesia
series Communications in Science and Technology
issn 2502-9258
2502-9266
publishDate 2016-12-01
description The purpose of this paper is to examine how to use first order Markov chain to build a reliable monitoring system for the profit-loss sharing based contracts (PLS) as the mode of financing contracts in Islamic bank with censored continuous-time observations. The paper adopts the longitudinal analysis with the first order Markov chain framework. Laplace transform was used with homogenous continuous time assumption, from discretized generator matrix, to generate the transition matrix. Various metrics, i.e.: eigenvalue and eigenvector were used to test the first order Markov chain assumption. Cox semi parametric model was used also to analyze the momentum and waiting time effect as non-Markov behavior. The result shows that first order Markov chain is powerful as a monitoring tool for Islamic banks. We find that waiting time negatively affected present rating downgrade (upgrade) significantly. Likewise, momentum covariate showed negative effect. Finally, the result confirms that different origin rating have different movement behavior. The paper explores the potential of Markov chain framework as a risk management tool for Islamic banks. It provides valuable insight and integrative model for banks to manage their borrower accounts. This model can be developed to be a powerful early warning system to identify which borrower needs to be monitored intensively. Ultimately, this model could potentially increase the efficiency, productivity and competitiveness of Islamic banks in Indonesia. The analysis used only rating data. Further study should be able to give additional information about the determinant factors of rating movement of the borrowers by incorporating various factors such as contract-related factors, bank-related factors, borrower-related factors and macroeconomic factors.
topic profit-loss sharing
Islamic banking
default risk
Markov model
survival rate
url https://cst.kipmi.or.id/index.php/cst/article/view/17/13
work_keys_str_mv AT imamwahyudi analyzingtheprofitlosssharingcontractswithmarkovmodel
AT alisakti analyzingtheprofitlosssharingcontractswithmarkovmodel
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