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Assessing network risk with FRM: links with pricing kernel volatility and application to cryptocurrencies

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10507672" target="_blank" >RIV/00216208:11320/24:10507672 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=G_jBfMWeOm" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=G_jBfMWeOm</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/14697688.2024.2370311" target="_blank" >10.1080/14697688.2024.2370311</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Assessing network risk with FRM: links with pricing kernel volatility and application to cryptocurrencies

  • Original language description

    The Financial Risk Meter (FRM) employs Quantile-LASSO regression to identify systemic financial risk and dependencies among tail events across financial assets. This paper establishes, both theoretically and empirically, a meaningful economic relationship between the FRM index, derived from the penalization parameter in quantile LASSO regression, and the volatility of assets&apos; pricing kernels, the attainable maximal Sharpe ratio, and market volatility. Despite the rapid growth of the crypto market and its increasing integration with traditional financial markets, there remains a dearth of risk measures in this space. $ FRM@Crypto $ FRM@Crypto exhibits robust predictive capabilities in anticipating future market risk, potentially filling a critical void in this market.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50201 - Economic Theory

Result continuities

  • Project

    <a href="/en/project/GX19-28231X" target="_blank" >GX19-28231X: DyMoDiF - Dynamic Models for the Digital Finance</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Quantitative Finance

  • ISSN

    1469-7688

  • e-ISSN

    1469-7696

  • Volume of the periodical

    24

  • Issue of the periodical within the volume

    7

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    18

  • Pages from-to

    975-992

  • UT code for WoS article

    001271375800001

  • EID of the result in the Scopus database

    2-s2.0-85198860242