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Big Data in Financial Markets: Using Search Volume Data for Market Trading Strategies

Johnson, Timothy LU (2014) NEKN01 20142
Department of Economics
Abstract
This paper examines the relationship between Big Data and two financial assets. This is achieved through replication of the portfolio method proposed by Preis, Moat and Stanley (2013) which examines and tests the relationship between search engine query volumes and financial markets. Collecting data from 98 different search terms, this paper extends the study by applying the strategy to two new financial assets, gold and the United States dollar, through the use of exchange traded funds. The results show statistically significant and positive returns for domestic United States search volumes and statistically insignificant results for global search volumes.
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author
Johnson, Timothy LU
supervisor
organization
course
NEKN01 20142
year
type
H1 - Master's Degree (One Year)
subject
keywords
Big Data, Google Trends, Gold, United States Dollar, Exchange Traded Funds
language
English
id
4729964
date added to LUP
2014-11-03 10:24:28
date last changed
2014-11-03 10:24:28
@misc{4729964,
  abstract     = {This paper examines the relationship between Big Data and two financial assets. This is achieved through replication of the portfolio method proposed by Preis, Moat and Stanley (2013) which examines and tests the relationship between search engine query volumes and financial markets. Collecting data from 98 different search terms, this paper extends the study by applying the strategy to two new financial assets, gold and the United States dollar, through the use of exchange traded funds. The results show statistically significant and positive returns for domestic United States search volumes and statistically insignificant results for global search volumes.},
  author       = {Johnson, Timothy},
  keyword      = {Big Data,Google Trends,Gold,United States Dollar,Exchange Traded Funds},
  language     = {eng},
  note         = {Student Paper},
  title        = {Big Data in Financial Markets: Using Search Volume Data for Market Trading Strategies},
  year         = {2014},
}