Quantifying Trading Behavior in Financial Markets Using Google Trends
نویسندگان
چکیده
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 query volumes for search terms related to finance, we find patterns that may be interpreted as "early warning signs" of stock market moves. Our results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior.
منابع مشابه
BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era
Digital currencies have emerged as a new fascinating phenomenon in the financial markets. Recent events on the most popular of the digital currencies--BitCoin--have risen crucial questions about behavior of its exchange rates and they offer a field to study dynamics of the market which consists practically only of speculative traders with no fundamentalists as there is no fundamental value to t...
متن کاملFinancial 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 ...
متن کاملInvestment Strategies Used as Spectroscopy of Financial Markets Reveal New Stylized Facts
We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset all...
متن کاملPredictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets
The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric m...
متن کاملChapter 28 Individual Investor Trading
Individual investors trade stocks in a way very different from what mainstream financial economic theory would predict: they generate too much trading volume and yet obtain belowbenchmark performance. This chapter overviews major 'puzzles' of individual investor trading. The extant literature suggests that behavioral biases and psychological explanations are largely responsible for many of the ...
متن کامل