This paper explores the use of Google trending data as a indicator for market sentiment. The Google query record on keywords including stock, market, correction, and crash are incorporated into an event based trading model for S&P 500 index in an attempt to identify significantly enhanced risk-profile of the trading results. Our study showed that the collective Google query can be an effective measure of market perception of risk. Furthermore, the collective perception on market risk, either over or under-reacted, can be a prelude indicator of immediate market volatility
<div><p>We live in a computerized and networked society where many of our actions leave a digital tr...
As the empirical studies show, investor sentiment is a significant factor in financial markets. The ...
Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2016.This study explores the effect of Go...
This thesis aims to investigate the usability of Google Trends data for predicting stock market vola...
Crises in financial markets affect humans worldwide. Detailed market data on trading decisions refle...
This project looks to generate forecasting models that can help investors better quantify the risk a...
<div><p>Today´s connected world allows people to gather information in shorter intervals than ever b...
Master's thesis in FinanceWe investigate whether Google search volume index (SVI) can explain and pr...
Today´s connected world allows people to gather information in shorter intervals than ever before, w...
In this paper I test the validity of using multivariate analysis of Google Trends search data on opt...
We live in a computerized and networked society where many of our actions leave a digital trace and ...
In this thesis, we aim to improve forecast accuracy of a heterogenous au- toregressive model (HAR) b...
Oil market pricing is highly susceptible to geopolitical and economic events. With the rapid develop...
The purpose of this thesis is to explore various possibilities of performing online sentiment analys...
This paper analyzes whether web search queries predict stock market activity in a sample of the lar...
<div><p>We live in a computerized and networked society where many of our actions leave a digital tr...
As the empirical studies show, investor sentiment is a significant factor in financial markets. The ...
Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2016.This study explores the effect of Go...
This thesis aims to investigate the usability of Google Trends data for predicting stock market vola...
Crises in financial markets affect humans worldwide. Detailed market data on trading decisions refle...
This project looks to generate forecasting models that can help investors better quantify the risk a...
<div><p>Today´s connected world allows people to gather information in shorter intervals than ever b...
Master's thesis in FinanceWe investigate whether Google search volume index (SVI) can explain and pr...
Today´s connected world allows people to gather information in shorter intervals than ever before, w...
In this paper I test the validity of using multivariate analysis of Google Trends search data on opt...
We live in a computerized and networked society where many of our actions leave a digital trace and ...
In this thesis, we aim to improve forecast accuracy of a heterogenous au- toregressive model (HAR) b...
Oil market pricing is highly susceptible to geopolitical and economic events. With the rapid develop...
The purpose of this thesis is to explore various possibilities of performing online sentiment analys...
This paper analyzes whether web search queries predict stock market activity in a sample of the lar...
<div><p>We live in a computerized and networked society where many of our actions leave a digital tr...
As the empirical studies show, investor sentiment is a significant factor in financial markets. The ...
Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2016.This study explores the effect of Go...