FRM financial risk meter

Mihoci, A., Althof, M., Chen, C. Y.-H. and Härdle, W. K. (2020) FRM financial risk meter. In: de Paula, Á., Tamer, E. and Voia, M.-C. (eds.) The Econometrics of Networks. Series: Advances in econometrics (42). Emerald. ISBN 9781838675769

Abstract

A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilising tail event information. FRM (Financial Risk Meter) is based on Lasso quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identifies risk factors. In practice, FRM is applied to the return time series of selected financial institutions and macroeconomic risk factors. We identify companies exhibiting extreme "co-stress", as well as "activators" of stress. With the SRM@EuroArea, we extend to the government bond asset class, and to credit default swaps with FRM@iTraxx. FRM is a good predictor for recession probabilities, constituting the FRM-implied recession probabilities. Thereby, FRM indicates tail event behaviour in a network of financial risk factors.

• Item Type: Book Sections
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Chen, Professor Cathy Yi-Hsuan
• Authors: Mihoci, A., Althof, M., Chen, C. Y.-H., and Härdle, W. K.
• College/School: College of Social Sciences > Adam Smith Business School > Accounting and Finance
• Journal Name: Advances in Econometrics
• Publisher: Emerald
• ISSN: 0731-9053
• ISBN: 9781838675769
• Copyright Holders: Copyright © 2020 Emerald Publishing Ltd
• First Published: First published in The Econometrics of Networks 2020
• Publisher Policy: Reproduced in accordance with the publisher copyright policy