Equity-premium prediction: Attention is all you need

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AKZSIXUUX" target="_blank" >RIV/00216208:11320/23:KZSIXUUX - isvavai.cz</a>
Výsledek na webu
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138695644&doi=10.1002%2fjae.2939&partnerID=40&md5=529ff81ac37609c3fb4444360ae17fa2" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138695644&doi=10.1002%2fjae.2939&partnerID=40&md5=529ff81ac37609c3fb4444360ae17fa2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/jae.2939" target="_blank" >10.1002/jae.2939</a>

Jazyk výsledku
angličtina
Název v původním jazyce
Equity-premium prediction: Attention is all you need
Popis výsledku v původním jazyce
"Predictions of stock returns are greatly improved relative to low-dimensional forecasting regressions when the forecasts are based on the estimated factor of large data sets, also known as the diffusion index (DI) model. However, when applied to text data, DI models do not perform well. This paper shows that by simply using text data in a DI model does not improve equity-premium forecasts over the naive historical-average model, but substantial gains are obtained when one selects the most predictive words before computing the factors and allows the dictionary to be updated over time. © 2022 John Wiley & Sons, Ltd."
Název v anglickém jazyce
Equity-premium prediction: Attention is all you need
Popis výsledku anglicky
"Predictions of stock returns are greatly improved relative to low-dimensional forecasting regressions when the forecasts are based on the estimated factor of large data sets, also known as the diffusion index (DI) model. However, when applied to text data, DI models do not perform well. This paper shows that by simply using text data in a DI model does not improve equity-premium forecasts over the naive historical-average model, but substantial gains are obtained when one selects the most predictive words before computing the factors and allows the dictionary to be updated over time. © 2022 John Wiley & Sons, Ltd."

Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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