The University of Southampton
University of Southampton Institutional Repository

An investigation into correlations between financial sentiment and prices in financial markets

An investigation into correlations between financial sentiment and prices in financial markets
An investigation into correlations between financial sentiment and prices in financial markets
There is now a small but growing literature showing some relationship between sentiment contained within blogs, online news article and message boards and price movements in financial markets. Typically, researchers use keyword searching to find financially relevant messages, then rate them in terms of their how positive or negative the sentiment they contain is in relation to prices.

Through an exploratory analysis of the statistical nature of word frequency movements on Twitter, we highlight some issues with this approach and define how a sentiment variable could be constructed to generate well specified linear regression models.

We then address a second issue of how to model time. Current research has used units of a day or week for both sentiment and price series. There is no discussion in the literature in this area as to what the best unit of time might be, or indeed, if there is a weekly topology to sentiment price correlations. We present two models which explore how these factors affect sentiment-price correlations.

Finally we present results correlating financial sentiment on Twitter to the price of the Standard and Poor's Index of 500 Leading Shares. We report both contemporaneous (R squared values up to 0.35) and predictive correlations (R squared values up to 0.27) between our sentiment metric and prices. Scale and weekly topology both appear significant factors that would benefit inclusion in future models.
978-1-4503-1889-1
99-108
Gaskell, Paul
9d855bff-86a2-4995-965a-3cbd968c5b8a
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Tiropanis, Thanassis
d06654bd-5513-407b-9acd-6f9b9c5009d8
Gaskell, Paul
9d855bff-86a2-4995-965a-3cbd968c5b8a
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Tiropanis, Thanassis
d06654bd-5513-407b-9acd-6f9b9c5009d8

Gaskell, Paul, McGroarty, Frank and Tiropanis, Thanassis (2013) An investigation into correlations between financial sentiment and prices in financial markets Proceedings of the 5th Annual ACM Web Science Conference, pp. 99-108.

Record type: Article

Abstract

There is now a small but growing literature showing some relationship between sentiment contained within blogs, online news article and message boards and price movements in financial markets. Typically, researchers use keyword searching to find financially relevant messages, then rate them in terms of their how positive or negative the sentiment they contain is in relation to prices.

Through an exploratory analysis of the statistical nature of word frequency movements on Twitter, we highlight some issues with this approach and define how a sentiment variable could be constructed to generate well specified linear regression models.

We then address a second issue of how to model time. Current research has used units of a day or week for both sentiment and price series. There is no discussion in the literature in this area as to what the best unit of time might be, or indeed, if there is a weekly topology to sentiment price correlations. We present two models which explore how these factors affect sentiment-price correlations.

Finally we present results correlating financial sentiment on Twitter to the price of the Standard and Poor's Index of 500 Leading Shares. We report both contemporaneous (R squared values up to 0.35) and predictive correlations (R squared values up to 0.27) between our sentiment metric and prices. Scale and weekly topology both appear significant factors that would benefit inclusion in future models.

Full text not available from this repository.

More information

e-pub ahead of print date: 1 January 2013
Published date: May 2013
Venue - Dates: Proceedings of the 5th Annual ACM Web Science Conference, France, 2013-05-02 - 2013-05-04
Organisations: Centre for Digital, Interactive & Data Driven Marketing

Identifiers

Local EPrints ID: 356113
URI: http://eprints.soton.ac.uk/id/eprint/356113
ISBN: 978-1-4503-1889-1
PURE UUID: 875a31de-953e-4f2b-979d-b59cbf5338e3
ORCID for Frank McGroarty: ORCID iD orcid.org/0000-0003-2962-0927
ORCID for Thanassis Tiropanis: ORCID iD orcid.org/0000-0002-6195-2852

Catalogue record

Date deposited: 10 Sep 2013 10:59
Last modified: 10 Nov 2017 17:51

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×