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Dependence Modeling
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Dependence Modeling
Article . 2022
Data sources: DOAJ
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Equity returns and sentiment

Authors: Huang, Z; Ibragimov, R;

Equity returns and sentiment

Abstract

Abstract This paper analyzes approximately 100 Gigabytes of raw text data from Twitter with keywords “AAPL,” “S&P 500,” “FTSE100” and “NASDAQ” to explore the relationship between sentiment and the returns and prices on the Apple stock and the S&P 500, FTSE 100 and NASDAQ indices. The findings point to significant relationship and dependence between sentiment measures and the S&P 500 and FTSE 100 indices’ returns and prices. The econometric analysis of dependence between the aforementioned variables in the paper is presented in some detail for illustration of the methodology employed.

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Keywords

asset prices, asset returns, Science (General), 330, sentiment, autoregressive distributed lag models, volatility, dependence, predictive regressions, Q1-390, granger causality, 91b84, 62p20, QA1-939, garch models, Mathematics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold