Do search engine data improve financial time series volatility predictions in different market periods? An empirical analysis on major world financial indices.
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2015, Vol 14, Issue 5
Abstract
In this paper, we investigate the different influence of search engine data in different market periods on the improvement of the prediction of the financial time series volatility. We use the EGARCH and the EGARCH-SVI model. We analyze weekly data from the Dow Jones, FTSE 100 and Nikkei 225 market indices and the weekly search volume index (SVI) from google trends for market indices keywords. The main contribution of this paper is introducing limitations of the EGARCH-SVI model for forecasting the weekly volatility of the market index. Our results show that i) search engine data improve financial time series volatility predictions of the EGARCH-SVI model in market crisis periods with the bigger price volatility; and ii) search engine data is not improving the prediction of the financial time series volatility of the EGARCH-SVI model in a non-crisis periods with low price volatility in the market. This result also confirms the predictive power of the EGARCH-SVI model in crisis periods for different financial markets.
Authors and Affiliations
Dimche Risteski, Danco Davcev
Keywords
Related Articles
- EP ID EP650719
- DOI 10.24297/ijct.v14i5.5275
- Views 99
- Downloads 0
Mobile Ad Hoc Networks: Comparasion of Multipath Routing Protocols with Unipath Routing Protocols
The latest technology MANETs is being studied widely and attracting a large variety of applications. Due to varying network topology, The most common challenging factor in MANET is routing [1][2]. Future applications of...
Analysis of Frequency Selective with Nonlinear Antenna under Radiations of Bi-Frequency Waves Based on Genetic Algorithm
The more frequency radiation increases, the shorter becomes its wave length. The short wavelength, while hitting to some material, cause vibration and make change the positive and negative poles. As the most common way o...
Color Image Compression by Using Absolute Moment Block Truncation Coding and Hadamard Transform
This paper investigates image data compression as it is applicable to different fields of image processing, in order to reduce the volume of pictorial data which one may need to store or transmit, The research modifies a...
WEB MINING THROUGH CUSTOMIZED MARKOV ALGORITHM
The problem of predicting a user’s behavior on a web site has gained Importance due to the very increases required web network. It also compulsory for market and research of social behavior. Although many approaches ar...
A Biochemical Study to Estimate Malonaldehyde and Ceruloplasmin Oxidase Activity As Parameters Express Oxidation – Antioxidation Balance for Patients With Acute Hepatitis Virus Type C
Oxygen free radicals play an important role in the pathogenesis of tissue damage in many pathological conditions, including liver diseases. Aim of the present study focused on the investigation the possible relationship...