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Deriving Trading Signals from Google Trends and
Wikipedia Page ViewsThomas Wiecki
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This is Joe.He is worried about the debt ceiling.
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What does he do?
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After gathering information he calls his broker.
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Who sells all of his clients stock.
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Stock market 101
The price is the result of the trading decisions of many individuals.
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Decision Making:Multiple stages
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Motivation
Quantify information gathering behavior that precedes investment decisions.
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● Stock prices follow news.● News can't be predicted ⇒ Random walk.● However: Stocks do not follow random walk.● What about bubbles?● More and more research casting doubt...
Efficient Market Hypothesis
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Quantitative Behavioral Finance
● Online chat activity predicts books sales [1]● Blog sentiment analysis predicts movie sales
[2].● Google search queries predict disease
infection and consumer spending [3].● ⇒ News impact markets, but so does public
mood and sentiment.
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Cognitive Bias: Loss Aversion
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Subject of recent research
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Simple investment strategy based on Google search volumefor t in [1:T]:
avg_search_vol = mean(search_vol[t-2:t-5])
if search_vol[t-1] > avg_search_vol:
short DJIA for one week
if search_vol[t-1] < avg_search_vol:
long DJIA for one week
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Quantopian Demo:Google Trends
https://www.quantopian.com/posts/google-search-terms-predict-market-movements
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Top predictors
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Bottom predictors
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Quantopian Demo:Wikipedia
https://www.quantopian.com/posts/deriving-trading-signals-from-wikipedia-page-views-
new-feature
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Twitter Sentiment Analysis
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Can Twitter move the market?
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Cautionary Tale
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● Founded February 2011● Closed after one month in service...● However: return of 1.86% (beating the
market and average hedge fund)
Twitter Fund (Derwent Capital Markets)
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● Preliminary evidence that information gathering can be quantified and exploited.
● Quantopian - Reproducibility Science● Mountains of data, waiting to be explored!
Departing thoughts...
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Image sources and references● http://www.ng.all.biz/img/ng/service_catalog/502.jpeg● http://www.123rf.com/photo_10037927_businessman-or-stock-broker-with-cellphone.html● http://www.financetwitter.com/wp-content/uploads/2011/08/SP500_Crash_4Aug2011.jpg● http://lydiakimblesellsvegas.com/images/buy-sell-keyboard.jpg● http://venturebeat.com/2012/05/28/twitter-fueled-hedge-fund-bit-the-dust-but-it-actually-worked/● Gilbert, E & Karahalios, K. (2010) Widespread worry and the stock market.● [11] Gruhl, D, Guha, R, Kumar, R, Novak, J, & Tomkins, A. (2005) The predictive power of online
chatter. (ACM, New York, NY, USA), pp. 78–87.● Mishne, G & Glance, N. (2006) Predicting Movie Sales from Blogger Sentiment. AAAI 2006
Spring Symposium on Computational Approaches to Analysing Weblogs● S. Asur and B. A. Huberman 2010 Predicting the Future with Social Media arXiv:1003.5699v1● Choi, H & Varian, H. (2009) Predicting the present with google trends., (Google), Technical
report.● Liu, Y, Huang, X, An, A, & Yu, X. (2007) ARSA: a sentiment-aware model for predicting sales
performance using blogs. (ACM, New York, NY, USA), pp. 607–614.