AN AI APPROACH TO MEASURING FINANCIAL RISK
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10489895" target="_blank" >RIV/00216208:11320/23:10489895 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=sb~CJkP0HW" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=sb~CJkP0HW</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0217590819500668" target="_blank" >10.1142/S0217590819500668</a>
Alternative languages
Result language
angličtina
Original language name
AN AI APPROACH TO MEASURING FINANCIAL RISK
Original language description
AI artificial intelligence brings about new quantitative techniques to assess the state of an economy. Here, we describe a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (lambda) of a linear quantile lasso regression. The FRM is calculated by taking the average of the penalization parameters over the 100 largest US publicly-traded financial institutions. We demonstrate the suitability of this AI-based risk measure by comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual Granger causality exists between the FRM and these measures, which indicates the validity of the FRM as a systemic risk measure. The implementation of this project is carried out using parallel computing, the codes are published on www.quantlet.de with keyword FRM. The R package RiskAnalytics is another tool with the purpose of integrating and facilitating the research, calculation and analysis methods around the FRM project. The visualization and the up-to-date FRM can be found on hu.berlin/frm.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50201 - Economic Theory
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
The Singapore Economic Review
ISSN
0217-5908
e-ISSN
1793-6837
Volume of the periodical
68
Issue of the periodical within the volume
05
Country of publishing house
SG - SINGAPORE
Number of pages
21
Pages from-to
1529-1549
UT code for WoS article
001082623600002
EID of the result in the Scopus database
2-s2.0-85076347879