Purpose

Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019.

Design/methodology/approach

In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk.

Findings

This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank.

Originality/value

Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

中文翻译：

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使用 SRISK 识别印度系统重要性银行

目的

自全球金融危机以来，系统性风险一直是全球银行监管机构关注的问题。本研究旨在通过使用 SRISK 来衡量系统性事件中银行的预期资本短缺，从而确定印度的系统重要性银行 (SIB)。样本规模包括 2006 年至 2019 年 31 家印度上市商业银行的平衡数据集。

设计/方法/方法

在这项研究中，作者使用 SRISK 来识别对印度银行业系统性风险贡献最大的银行。杠杆、规模和长期边际预期缺口 (LRMES) 用于计算 SRISK。前瞻性 LRMES 是使用 GJR-GARCH 动态条件相关方法计算的，用于早期预测银行对系统性风险的贡献。

发现

本研究发现，与私营部门银行相比，公共部门银行由于资本不足而更容易受到宏观经济冲击的影响。本研究还强调，规模不应被用作评估银行系统重要性的独立因素。

原创性/价值

系统性风险引起了很多研究兴趣；然而，它主要限于发达国家。本文填补了银行业文献中关于识别新兴经济体印度 SIBs 的重要研究空白。由于 SRISK 同时使用资产负债表和基于市场的信息，它可以用来补充印度储备银行用于识别 SIB 的现有方法。