Google’s Search Data and its Application in Finance

Bodo Herzog

doi:doi:10.11648/j.ijefm.20140201.11

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Google’s Search Data and its Application in Finance

Bodo Herzog

Published in International Journal of Economics, Finance and Management Sciences (Volume 2, Issue 1)

Received: 1 November 2013 Published: 10 December 2013

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Abstract

This paper examines the relationship of asset price determination via Google data. To capture this relation, I create a model and estimate several time series’ regressions. I use weekly data from 2004 to 2010 from 30 international banks. To my knowledge this is the first study which differentiates between Google’s search volume and Google’s search clicks. I show that asset prices are positively related to the rate of change in Google’s search volume, trading volume and the level of Google search clicks. Secondly, I demonstrate that the absolute level of Google’s search volume and Google’s search clicks behave differently regarding the asset price dynamics. Google’s search volume, which measures long-run searches, is negatively related while Google’s search clicks have a positive relationship to asset prices. Hence, Google’s data offer new insights on both measuring attention and pricing financial assets.

Published in	International Journal of Economics, Finance and Management Sciences (Volume 2, Issue 1)
DOI	10.11648/j.ijefm.20140201.11
Page(s)	1-7
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Search Data, Asset Price, Asset Bubbles, Google Measures

References

[1]	S. J. Grossmann and J.E. Stiglizt, "On the Impossibility of Informationally Efficient Markets," in American Economic Review, vol. 70, issue 3,1980, pp. 393-408.
[2]	F. Allen, "The market for information and the origin of financial intermediation," in Journal of Financial Intermediation, vol. 1, issue 1, 1990, pp. 3-30.
[3]	L. Cohen and D. Lou, "Complicated Firm," SSRN working paper, AFA 2011 Denver Meetings Paper, no. 1570869, October 2010.
[4]	D. Duffie, "Presidential Address: Asset Price Dynamics with Slow-Moving Capital," in Journal of Finance, vol. 65, No. 4, 2010, pp. 1237-1267.
[5]	D. Kahneman, "Attention and Effort," Prentice-Hall,1973.
[6]	Z. Da, J. Engelberg and P. Gao, "In Search of Attention," in Journal of Finance, vol.66, No. 5, 2011, pp. 1461-1499.
[7]	B.M. Barber and T. Odeau, "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," in Review of Financial Studies, vol. 21(2), 2008, pp. 785-818.
[8]	X. Li, R.S. Mahani and V. Sandhya, "Does Investor Attention Affect Stock Prices?," SSRN Working Paper, no. 1748851, March 2011.
[9]	H. Choi and H. Varian, "Predicting the Present with Google Trends," Working Paper, www.google.com/googleblogs/pdfs/google_predicting_the_present.pdf (14.03.2010, 09:37), 2009.
[10]	R.E. Lucas, "Asset Prices in an Exchange Economy," in Econometrica, vol. 46, issue 6,1978, pp. 1426-1445.

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APA Style

Bodo Herzog. (2013). Google’s Search Data and its Application in Finance. International Journal of Economics, Finance and Management Sciences, 2(1), 1-7. https://doi.org/10.11648/j.ijefm.20140201.11

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Bodo Herzog. Google’s Search Data and its Application in Finance. Int. J. Econ. Finance Manag. Sci. 2013, 2(1), 1-7. doi: 10.11648/j.ijefm.20140201.11

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AMA Style

Bodo Herzog. Google’s Search Data and its Application in Finance. Int J Econ Finance Manag Sci. 2013;2(1):1-7. doi: 10.11648/j.ijefm.20140201.11

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@article{10.11648/j.ijefm.20140201.11,
  author = {Bodo Herzog},
  title = {Google’s Search Data and its Application in Finance},
  journal = {International Journal of Economics, Finance and Management Sciences},
  volume = {2},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.ijefm.20140201.11},
  url = {https://doi.org/10.11648/j.ijefm.20140201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20140201.11},
  abstract = {This paper examines the relationship of asset price determination via Google data. To capture this relation, I create a model and estimate several time series’ regressions. I use weekly data from 2004 to 2010 from 30 international banks. To my knowledge this is the first study which differentiates between Google’s search volume and Google’s search clicks. I show that asset prices are positively related to the rate of change in Google’s search volume, trading volume and the level of Google search clicks. Secondly, I demonstrate that the absolute level of Google’s search volume and Google’s search clicks behave differently regarding the asset price dynamics. Google’s search volume, which measures long-run searches, is negatively related while Google’s search clicks have a positive relationship to asset prices. Hence, Google’s data offer new insights on both measuring attention and pricing financial assets.},
 year = {2013}
}

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TY - JOUR
T1 - Google’s Search Data and its Application in Finance
AU - Bodo Herzog
Y1 - 2013/12/10
PY - 2013
N1 - https://doi.org/10.11648/j.ijefm.20140201.11
DO - 10.11648/j.ijefm.20140201.11
T2 - International Journal of Economics, Finance and Management Sciences
JF - International Journal of Economics, Finance and Management Sciences
JO - International Journal of Economics, Finance and Management Sciences
SP - 1
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PB - Science Publishing Group
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AB - This paper examines the relationship of asset price determination via Google data. To capture this relation, I create a model and estimate several time series’ regressions. I use weekly data from 2004 to 2010 from 30 international banks. To my knowledge this is the first study which differentiates between Google’s search volume and Google’s search clicks. I show that asset prices are positively related to the rate of change in Google’s search volume, trading volume and the level of Google search clicks. Secondly, I demonstrate that the absolute level of Google’s search volume and Google’s search clicks behave differently regarding the asset price dynamics. Google’s search volume, which measures long-run searches, is negatively related while Google’s search clicks have a positive relationship to asset prices. Hence, Google’s data offer new insights on both measuring attention and pricing financial assets.
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Author Information

Bodo Herzog

ESB Business School, Reutlingen, Germany； Institute of Finance and Economics (IFE), Germany； Reutlingen Research Institute, Reutlingen University, Germany

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APA Style

Bodo Herzog. (2013). Google’s Search Data and its Application in Finance. International Journal of Economics, Finance and Management Sciences, 2(1), 1-7. https://doi.org/10.11648/j.ijefm.20140201.11

Copy | Download

ACS Style

Bodo Herzog. Google’s Search Data and its Application in Finance. Int. J. Econ. Finance Manag. Sci. 2013, 2(1), 1-7. doi: 10.11648/j.ijefm.20140201.11

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AMA Style

Bodo Herzog. Google’s Search Data and its Application in Finance. Int J Econ Finance Manag Sci. 2013;2(1):1-7. doi: 10.11648/j.ijefm.20140201.11

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@article{10.11648/j.ijefm.20140201.11,
  author = {Bodo Herzog},
  title = {Google’s Search Data and its Application in Finance},
  journal = {International Journal of Economics, Finance and Management Sciences},
  volume = {2},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.ijefm.20140201.11},
  url = {https://doi.org/10.11648/j.ijefm.20140201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20140201.11},
  abstract = {This paper examines the relationship of asset price determination via Google data. To capture this relation, I create a model and estimate several time series’ regressions. I use weekly data from 2004 to 2010 from 30 international banks. To my knowledge this is the first study which differentiates between Google’s search volume and Google’s search clicks. I show that asset prices are positively related to the rate of change in Google’s search volume, trading volume and the level of Google search clicks. Secondly, I demonstrate that the absolute level of Google’s search volume and Google’s search clicks behave differently regarding the asset price dynamics. Google’s search volume, which measures long-run searches, is negatively related while Google’s search clicks have a positive relationship to asset prices. Hence, Google’s data offer new insights on both measuring attention and pricing financial assets.},
 year = {2013}
}

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