Predicting Financial Markets with Google Trends and Not so Random Keywords

Quantifying Trading Behavior in Financial Markets Using Google Trends

Crises in financial markets affect humans worldwide. Detailed market data on trading decisions reflect some of the complex human behavior that has led to these crises. We suggest that massive new data sources resulting from human interaction with the Internet may offer a new perspective on the behavior of market participants in periods of large market movements. By analyzing changes in Google q...

Predicting the direction of stock markets using optimized neural networks with Google Trends

Financial Market Prediction using Google Trends

Financial decisions are among the most significant life-changing decisions that individuals make. There is a strong correlation between financial decision making and human behavior. In this research the relationship between what people think and how stock market moves is investigated. The data from 2010 to 2015 of some of business, political and financial events which directly impact the local ...

Predicting IMDB movie ratings using Google Trends

Movie ratings are influenced by many factors, so accurate prediction of new movie ratings can be challenging. In recent years, various semantic analysis techniques were successfully applied to analyzing user reviews, which in turn were applied to predict IMDB movie ratings (based on IMDB reviews, youtube movie trailer reviews etc). To the best of our knowledge there has been no research done on...

Why Are Gambling Markets Organised so Differently from Financial Markets?*

The market for sports gambling is structured very differently from the typical financial market. In sports betting, bookmakers announce a price, after which adjustments are small and infrequent. Bookmakers do not play the traditional role of market makers matching buyers and sellers but, rather, take large positions with respect to the outcome of game. Using a unique data set, I demonstrate tha...