Article ID: | iaor20171862 |
Volume: | 253 |
Issue: | 1 |
Start Page Number: | 21 |
End Page Number: | 41 |
Publication Date: | Jun 2017 |
Journal: | Annals of Operations Research |
Authors: | Kim Young, Anand Abhinav, Li Tiantian, Kurosaki Tetsuo |
Keywords: | finance & banking, risk, simulation |
The measurement of financial risk relies on two factors: determination of riskiness by use of an appropriate risk measure; and the distribution according to which returns are governed. Wrong estimates of either, severely compromise the accuracy of computed risk. We identify the too‐big‐to‐fail banks with the set of ‘Global Systemically Important Banks’ (G‐SIBs) and analyze the equity risk of its equally weighted portfolio by means of the ‘Foster–Hart risk measure’–a bankruptcy‐proof, reserve based measure of risk, extremely sensitive to tail events. We model banks’ stock returns as an ARMA–GARCH process with multivariate ‘Normal Tempered Stable’ innovations, to capture the skewed and leptokurtotic nature of stock returns. Our union of the Foster–Hart risk modeling with fat‐tailed statistical modeling bears fruit, as we are able to measure the equity risk posed by the G‐SIBs more accurately than is possible with current techniques.