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BibTex format

@article{Huang:2022:10.1515/demo-2022-0109,
author = {Huang, Z and Ibragimov, R},
doi = {10.1515/demo-2022-0109},
journal = {Dependence Modeling},
pages = {159--176},
title = {Equity returns and sentiment},
url = {http://dx.doi.org/10.1515/demo-2022-0109},
volume = {10},
year = {2022}
}

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TY  - JOUR
AB  - 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.
AU  - Huang,Z
AU  - Ibragimov,R
DO  - 10.1515/demo-2022-0109
EP  - 176
PY  - 2022///
SN  - 2300-2298
SP  - 159
TI  - Equity returns and sentiment
T2  - Dependence Modeling
UR  - http://dx.doi.org/10.1515/demo-2022-0109
UR  - https://www.degruyter.com/document/doi/10.1515/demo-2022-0109/html
UR  - http://hdl.handle.net/10044/1/97653
VL  - 10
ER  -

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