Attention driven market risk

Název projektu anglicky
Attention driven market risk
Anotace anglicky
Extreme market disruptions have been common in the past two decades, from the global financial crisis to the pandemic and war in Europe, all fueling demand for better risk management tools. Moreover, an oversaturated information space makes risk management harder for investors, regulators, and policymakers. The main objective of the research proposal is to quantify the extent to which investor attention drives future asset return distribution by designing and empirically verifying new market risk models—specifically, the joint estimation of Value at Risk and Expected Shortfall, and volatility. We contribute to the literature by addressing three questions. First, are we able to improve the measurement of investor's attention? Second, does it matter if we focus on overall and limited attention? Third, can we improve the forecasting accuracy of low-frequency models with machine learning and attention measures? Our research is empirical in nature, based on state-of-the-art econometric and machine-learning methods.

Kategorie VaV
ZV - Základní výzkum
OECD FORD - hlavní obor
50206 - Finance
OECD FORD - vedlejší obor
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OECD FORD - další vedlejší obor
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CEP - odpovídající obory <br>(dle <a href="http://www.vyzkum.cz/storage/att/E6EF7938F0E854BAE520AC119FB22E8D/Prevodnik_oboru_Frascati.pdf">převodníku</a>)
AH - Ekonomie<br>GA - Zemědělská ekonomie

Důvěrnost údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Systémové označení dodávky dat
CEP26-GA0-GA-R
Datum dodání záznamu
6. 5. 2026

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