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Asia-Pacific Financial Markets
Erschienen in: Asia-Pacific Financial Markets 4/2017

14.10.2017

Assessing Corporate Vulnerabilities in Indonesia: A Bottom-Up Default Analysis

verfasst von: Ken Miyajima, Jorge A. Chan-Lau, Weimin Miao, Jongsoon Shin

Erschienen in: Asia-Pacific Financial Markets | Ausgabe 4/2017

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Abstract

Under adverse macroeconomic conditions, the potential realization of corporate sector vulnerabilities could pose major risks to the economy. This paper assesses corporate vulnerabilities in Indonesia by using a Bottom-Up Default Analysis (BuDA) approach, which allows projecting corporate probabilities of default (PDs) under different macroeconomic scenarios. In particular, a protracted recession and the ensuing currency depreciation could erode buffers on corporate balance sheets, pushing up the probabilities of default (PDs) in the corporate sector to the high levels observed during the Global Financial Crisis. While this is a low-probability scenario, the results suggest the need to closely monitor vulnerabilities and strengthen contingency plans.
Vorheriger Artikel Internal Market Efficiency, Market Co-movement, and Cross-Market Efficiency: The Case of Hong Kong and Shanghai Stock Markets
Nächster Artikel Pricing Perpetual Put Options by the Black–Scholes Equation with a Nonlinear Volatility Function

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Fußnoten
1
The interest coverage ratio is earnings before interest and taxes (EBIT) over interest expenses for the same period. Bank Indonesia’s analysis showed that interest coverage ratio was above one for all economic sectors, due likely to differences in methodology and data sources.
 
2
The BuDA platform serves to support applied economic surveillance work. See for instance, Chapter 3 in International Monetary Fund (2015), and Chapter 2 in International Monetary Fund (2016).
 
3
The firm-specific factors selected for BuDA provide the best fit to the data, among a large number of different firm-specific factors initially tested guided by theory and practice. While the paper focuses on 1-year ahead PDs, the model performs well in forecasting default events up to a 5-year horizon. The model maximizes a quasi-likelihood function calibrated using data for thousands of firms in EMs. Information on interconnectedness, which could be useful to further refine the model, is not available for all the countries and firms included in the estimation.
 
4
See Duan et al. (2012) for detail on volatility-adjusted leverage.
 
5
The country average factor in this paper is analogous to the market return in the CAPM model. For instance, in the CAPM model, the returns of an individual firm are regressed on the returns of the aggregated market, to which the individual firm contributes. In this case, for the risk factors, this paper uses the country average as a common risk factor, and model firm-specific deviations from it.
 
6
See Duan et al. (2014) for details. The default settings in BuDA, used in our analysis, are 12-month aggregation, and the use of two lags of the dependent variable in Eqs. (1) and (2).
 
7
The “LASSO-OLS hybrid” is originated from the “LARS-OLS hybrid” proposed by Efron et al. (2004), with the variable selection in the first step replaced from LARS to LASSO. LARS is short for least angle regression, an efficient model selection algorithm; while LASSO is short for least absolute shrinkage and selection operator, a model selection method. A simple modification of the LARS implements the LASSO. BuDA uses AR (3) by default.
 
8
See Duffie and Singleton (2003), Lando (2004) and Bielecki and Rutkowski (2004) for an extensive treatment of mathematical credit risk.
 
9
Default and other exits are competing as opposed to independent risks, as both events are mutually exclusive. When modeled as two independent processes, the probability of their joint occurrence happens to equal zero, which blurs the distinction between competing and independent risks. Hence, the modeling assumption of two doubly stochastic Poisson processes appears acceptable, as first introduced by Duffie et al. (2007); and adopted by Duan et al. (2012), whose model this paper uses. The interested reader is referred to these two publications for further details.
 
10
The predictive accuracy of the PD model for corporate defaults in EMs over a 1-year horizon is 77%, if the accuracy ratio is used, and 89% percent, if the area under the receiver operating characteristic curve is used. A perfect predictive model would score 100% under both measures, and an uninformative model 50%.
 
Literatur
Acharya, V. et al. (2015). Corporate debt in emerging economies: A threat to financial stability, Report by the Committee on International Economic Policy and Reform Brookings Institute. Washington: Brookings Institution.
Bielecki, T., & Rutkowski, M. (2004). Credit risk. Berlin: Springer.
Chow, J. (2015). Stress testing corporate balance sheets in emerging economies, IMF Working Paper No. 15/216 (Washington: International Monetary Fund).
Duan, J. C., & Fulop, A. (2013). Multiperiod corporate default prediction with partially-conditioned forward intensity. RMI Working Paper No. 12/04 (Singapore: National University of Singapore, Risk Management Institute).
Duan, J. C., Miao, W., & Chan-Lau, J. A. (2015). BuDA: A bottom-up default analysis tool (Unpublished; Risk Management Institute. National University of Singapore and International Monetary Fund).
Duan, J. C., Sun, J., & Wang, T. (2012). Multiperiod corporate default prediction—A forward intensity approach. Journal of Econometrics, 170, 191–209.CrossRef
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Duffie, D., & Singleton, K. (2003). Credit risk : Pricing, measurement, and management. Princeton: Princeton University Press.
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Metadaten
Titel
Assessing Corporate Vulnerabilities in Indonesia: A Bottom-Up Default Analysis
verfasst von
Ken Miyajima
Jorge A. Chan-Lau
Weimin Miao
Jongsoon Shin
Publikationsdatum
14.10.2017
Verlag
Springer Japan
Erschienen in
Asia-Pacific Financial Markets / Ausgabe 4/2017
Print ISSN: 1387-2834
Elektronische ISSN: 1573-6946
DOI
https://doi.org/10.1007/s10690-017-9233-2