A Systematic Approach to identify Systemically

Important Firms : A Summary

Rishabh Shukla

Since the 2008 crisis, there has been a growing interest in measuring systemicrisk in the financial sector, as prudential regulation of individual financialfirms did not prove adequate to manage the risk posed by the financial sectorto the economy. In such a scenario it is wise to identify systemically importantfinancial firms (SIFIs) as it enables policy-makers to choose the most suitablegovernment intervention when such a firm approaches failure.

The paper by Agarwal, Arora et.al (2013) identifies systemically importantfinancial firms (SIFIs) in India using three measures which are grounded inquality datasets, namely Granger Causality (GC), Marginal ExpectedShortfall (MES) and Conditional Value at Risk (Co-VaR). The paper alsoproposes a Systemic Risk Index (SRI), an aggregate measure of systemic riskbased on average of percentile rankings on individual measures.

Granger causality (GC) measures the degree of interconnectedness betweenfirms and also the direction of causality of their relationship. Greater thenumber of inter-connections, more likely will a firm’s failure cause a systemicshock. Marginal Expected Shortfall (MES) measures the market capitalizationthat a firm stands to lose on the worst performing days of the market. Greaterthe MES of a firm, more vulnerable it is to a crisis. Co-VAR measures themarginal contribution of a firm to the overall level of systemic risk of themarket.

The systemic risk index (SRI) is computed for a firm i by calculating GC,MES and Co-VAR at sample time period t. The percentile rank of each firm isthen calculated on the basis of each measure. The average of these percentileranks are then obtained for each firm at each time period to obtain the SRI.The differences between rankings based on different measures is thuseliminated and a unique set of SIFIs is determined for a given time period.

The paper calculates SRI for the 50 largest firms listed on the NSE for eachquarter from July 2006 to October 2012, including both financial andnon-financial firms. The paper also evaluates the SRI for the 25 largest banksin the country. The firms with higher SRI are systemically riskier compared tothe lower ranked firms.

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The hypothesis that the paper then tests is whether the measures capturesome or all facets of systemic risk. If they do, then they’ll have significantlydifferent values in the pre-crisis period compared to the crisis period, sincesystemic risk increases during the time of a crisis. The hypothesis is testedusing the test of difference in medians between two periods using theWilcoxon-Mann-Whitney test.

The paper finds that GC and MES rise significantly between the pre-crisisperiod, the crisis period and the post-crisis period while co-VAR fallssignificantly in the post-crisis period, implying that it could be a lead indicatorof rise in systemic risk; thereby acting as an early warning signal. The medianGC of the banks is higher compared to the 50 largest firms, implying a higherdegree of interconnectedness among the major banks compared to the averagefirm. Since the median MES, as a fraction of GDP, is found to be higherduring the crisis period compared to the post-crisis period, banking sector islikely to contribute a larger portion to the systemic risk during the crisisperiod compared to periods with low systemic risk.

By ranking of the firms by averaging the SRI in each quarter within a period,it is found that ICICI Bank was the most SIF during the crisis period. If thetop 20 SIFs are calculated by averaging the GC, MES, SRI or co-VAR, thenumber of financial firms vary across measures. However, the largest numberof financial firms among the top 20 are identified during the crisis across allmeasures, with SRI identifying the most number of financial firms across allperiods (pre, during and post crisis).

The paper also finds that non-financial firms may cause systemic risk tospread during a crisis due to the exposure of commercial banks to such firmsthrough bank loans. For example, during Jul-Sep 2008, DLF, a real estate firmwith a market cap under 4% of GDP, similar to HDFC Bank during thatquarter, had a higher MES than HDFC, however the bank was moreinter-connected (higher GC).

An extension of the paper could identify SIFs in different industry sectors. Ifthe systemically important sectors have a concentration in the loan portfolio ofthe banking sector, it could serve as a useful input for better risk managementof the banking firm and also the sector at large.

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