Uncovering the skewness news impact curve

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985998%3A_____%2F16%3A00466532" target="_blank" >RIV/67985998:_____/16:00466532 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11640/16:00468755
Result on the web
<a href="http://dx.doi.org/10.1093/jjfinec/nbw005" target="_blank" >http://dx.doi.org/10.1093/jjfinec/nbw005</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/jjfinec/nbw005" target="_blank" >10.1093/jjfinec/nbw005</a>

Result language
angličtina
Original language name
Uncovering the skewness news impact curve
Original language description
We investigate, within flexible semiparametric and parametric frameworks, the shape of the news impact curve (NIC) for the conditional skewness of stock returns, that is, how past returns affect present skewness. We find that returns may impact skewness in ways that sharply differ from those proposed in earlier literature. The skewness NIC may exhibit sign asymmetry, other types of nonlinearity, and even non-monotonicity. In particular, the newly discovered “rotated S-shape of the skewness NIC for the S&P500 index is intriguing. We explore, among other things, properties of skewness NIC estimates and conditional density forecasts, the term structure of the skewness NIC, and previously documented approaches to its modeling.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
—

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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