Google search data has proven to be useful in portfolio management. The basic idea is that high search volumes are related to bad news and risk increase. This paper shows additional evidence about the use of Google search volumes in risk management. The empirical application is performed on the Standard & Poor Industrial index components from 2004 to 2017. To overcome the (time-series and cross-section) limitations Google imposes on the data download, a re-normalization procedure is presented, to obtain a multivariate sample of volumes which preserve their relative magnitude. Different ways to incorporate Google data are compared, showing that the volumes’ normalization and the starting portfolio are decisive for the portfolio performances. Correctly normalized Google search volumes yield poor results. This may lead to revise the interpretation of the search volume: it can be considered a risk indicator, but when used in an equally risk contribution portfolio, no evidence of the improvement of the risk-return performances is found.

Google Searches for Portfolio Management: A Risk and Return Analysis

Mario Maggi
;
2018-01-01

Abstract

Google search data has proven to be useful in portfolio management. The basic idea is that high search volumes are related to bad news and risk increase. This paper shows additional evidence about the use of Google search volumes in risk management. The empirical application is performed on the Standard & Poor Industrial index components from 2004 to 2017. To overcome the (time-series and cross-section) limitations Google imposes on the data download, a re-normalization procedure is presented, to obtain a multivariate sample of volumes which preserve their relative magnitude. Different ways to incorporate Google data are compared, showing that the volumes’ normalization and the starting portfolio are decisive for the portfolio performances. Correctly normalized Google search volumes yield poor results. This may lead to revise the interpretation of the search volume: it can be considered a risk indicator, but when used in an equally risk contribution portfolio, no evidence of the improvement of the risk-return performances is found.
2018
Mathematical and Statistical Methods for Actuarial Sciences and Finance
M. Corazza, M Durban, A. Grané, C. Perna, M. Sibillo
The Mathematics category includes resources dealing with mathematics, applied mathematics, statistics and probability.
Comitato scientifico
Inglese
Internazionale
STAMPA
461
466
6
978-3-319-89823-0
Springer International Publishing AG
Cham
SVIZZERA
Portfolio management, Online searches, Google Trends
no
2 Contributo in Volume::2.1 Contributo in volume (Capitolo o Saggio)
2
268
none
Maggi, MARIO ALESSANDRO; Uberti, Pierpaolo
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1229726
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