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Big Data in Financial Markets: Using Search Volume Data for Market Trading Strategies
| Content Provider | Semantic Scholar |
|---|---|
| Author | Johnson, Timothy |
| Copyright Year | 2014 |
| 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://lup.lub.lu.se/luur/download?fileOId=4729966&func=downloadFile&recordOId=4729964 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
