Macroprudential Stress Testing for Credit Risk:

Empirical Evidence from the Thai Housing Loan

Authors

  • Chanont Sontha Krungthai Bank, Thailand
  • Thitivadee Chaiyawat Chulalongkorn University, Thailand

Keywords:

Credit Risk, Probability of Default, Macroprudential Policy, Capital, NPL

Abstract

This study aims to assess credit risk regulatory capital requirement under a stress scenario of non-performing housing loan during 2013-2014. Therefore, this paper uses Vector Autoregressive (VAR) model to analyze the impact of macroprudential policies and macroeconomic environment on credit risk of housing loan. The result indicates that macroeconomic factors; e.g., gross domestic product (GDP) and consumer price index (CPI) have a significant negative impact on non-performing loan (NPL). Furthermore, the result also suggests that loan-to-value (LTV) ratio as a macroprudential instrument is correlated with a change in non-performing housing loan. The deceasing of the past four period LTV ratio generates non-performing housing loan of the current period. The regulator should therefore effectively deploy macroprudential policies to slowdown the NPL and create financial stability, thus securing the resilience of the financial system. This study also found that the Bank of Thailand has overestimated the loan provision requirement of 1.00 percent of total outstanding debt. In addition, the study reveals that under a stress the Thai commercial bank should increase loan-loss provision level when an economic downturn sets in. Under a stress and economic crisis this study shows that value-at-risk (VaR) is not the proper approach to determine the regulatory credit risk capital. Therefore, conditional value-at-risk (CVaR) may represent an additional insight for estimating capital buffer from severe credit risk especially under systemic risk environment. Additional capital buffer of 0.0044-0.0064 percent of credit housing loan is also required to enhance bank’s financial stability under a stress scenario.

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Published

30-06-2017