The Effects of Economic Variables on Swedish Stock Market Volatility A GARCH-MIDAS Approach
(2018) NEKP03 20162Department of Economics
- Abstract
- This thesis applies the GARCH-MIDAS model to investigate the effects of macroeconomic variables, sentimental indicators, and financial variables on Swedish stock market volatility for the period January 2002 to December 2016. The GARCH-MIDAS framework allows the incorporation of data at different frequencies into the same model and decomposes volatility into two components. A short-term component and a long-term component of volatility. The findings show that some of the investigated variables affect stock market volatility. Among the investigated variables, the realized volatility is, in terms of variance ratios, considered the best determinant of volatility, followed by the level specification of the producer price index, unemployment... (More)
- This thesis applies the GARCH-MIDAS model to investigate the effects of macroeconomic variables, sentimental indicators, and financial variables on Swedish stock market volatility for the period January 2002 to December 2016. The GARCH-MIDAS framework allows the incorporation of data at different frequencies into the same model and decomposes volatility into two components. A short-term component and a long-term component of volatility. The findings show that some of the investigated variables affect stock market volatility. Among the investigated variables, the realized volatility is, in terms of variance ratios, considered the best determinant of volatility, followed by the level specification of the producer price index, unemployment and the term spread, and the volatility specification of the purchasing manager’s index, exchange rate, and the industrial confidence. (Less)
- Popular Abstract
- This thesis applies the GARCH-MIDAS model to investigate the effects of macroeconomic variables, sentimental indicators, and financial variables on Swedish stock market volatility for the period January 2002 to December 2016. The GARCH-MIDAS framework allows the incorporation of data at different frequencies into the same model and decomposes volatility into two components. A short-term component and a long-term component of volatility. The findings show that some of the investigated variables affect stock market volatility. Among the investigated variables, the realized volatility is, in terms of variance ratios, considered the best determinant of volatility, followed by the level specification of the producer price index, unemployment... (More)
- This thesis applies the GARCH-MIDAS model to investigate the effects of macroeconomic variables, sentimental indicators, and financial variables on Swedish stock market volatility for the period January 2002 to December 2016. The GARCH-MIDAS framework allows the incorporation of data at different frequencies into the same model and decomposes volatility into two components. A short-term component and a long-term component of volatility. The findings show that some of the investigated variables affect stock market volatility. Among the investigated variables, the realized volatility is, in terms of variance ratios, considered the best determinant of volatility, followed by the level specification of the producer price index, unemployment and the term spread, and the volatility specification of the purchasing manager’s index, exchange rate, and the industrial confidence. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8957965
- author
- Kejlberg, Sebastian LU
- supervisor
- organization
- course
- NEKP03 20162
- year
- 2018
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- GARCH, MIDAS, stock market, volatility, macroeconomic, OMXSB, Sweden
- language
- English
- id
- 8957965
- date added to LUP
- 2018-09-24 13:59:04
- date last changed
- 2018-09-24 13:59:04
@misc{8957965,
abstract = {{This thesis applies the GARCH-MIDAS model to investigate the effects of macroeconomic variables, sentimental indicators, and financial variables on Swedish stock market volatility for the period January 2002 to December 2016. The GARCH-MIDAS framework allows the incorporation of data at different frequencies into the same model and decomposes volatility into two components. A short-term component and a long-term component of volatility. The findings show that some of the investigated variables affect stock market volatility. Among the investigated variables, the realized volatility is, in terms of variance ratios, considered the best determinant of volatility, followed by the level specification of the producer price index, unemployment and the term spread, and the volatility specification of the purchasing manager’s index, exchange rate, and the industrial confidence.}},
author = {{Kejlberg, Sebastian}},
language = {{eng}},
note = {{Student Paper}},
title = {{The Effects of Economic Variables on Swedish Stock Market Volatility A GARCH-MIDAS Approach}},
year = {{2018}},
}