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Stock Market Financial data reflect the day to day decision making of the society

Stock Market

Financial data reflect the day to day decision making of

the society
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Baseline We find that returns from the Google Trends strategies we

Baseline

We find that returns from the Google Trends strategies we tested

are significantly higher overall than returns from the random strategies ( , R . US 5 0.60; t 5 8.65, df 5 97, p , 0.001, onesample t-test).
Assumptions: US users only, mouse click by a foreign Ip does not count
Moving Avg Baseline
Exponential Moving Avg
Jump to GTrends
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Google Trends Search to Sale Quantifying Trading Behavior in Financial Markets

Google Trends

Search to Sale
Quantifying Trading Behavior in Financial Markets Using Google

Trends. By Tobias Preis, Helen Susannah Moat & H. Eugene Stanley, 25th April 2013
Google has begun to provide access to aggregated information on the volume of queries for different search terms and how these volumes change over time
Current state of the stock markets, but may have also been able to anticipate certain future trend. Analyze before buy or sell
We use Google Trends to determine how many searches n(t –1)have been carried out for a specific search term such as debt in week t– 1, where Google defines weeks as ending on a Sunday, relative to the total number of searches carried out on Google during that time.
HOLD relative less interest, BUY, SELL
WEEK TO WEEK
Decrease in search volume prompts us to buy, increase in search to sell
Specific search value terms pointing to buy/sell - Failed
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Results and interpretation Our Google trends algorithm slightly shows much better

Results and interpretation

Our Google trends algorithm slightly shows much better than

the randomn model. It is very close to