Stock market and macroeconomic volatility comparison: an US approach

In 2007, as the US subprime mortgage market began to fall down, which reached its peak with the catastrophic collapse of the Lehman Brothers, no one was aware of that this was going to be the worst financial crisis since the Great Depression. Evaluating the advantages and disadvantages connected wit...

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Bibliographic Details
Published in:Quality & quantity 2014, Vol.48 (1), p.217-224
Main Authors: Tokmakcioglu, Kaya, Tas, Oktay
Format: Article
Language:English
Subjects:
Analysis
Balance sheets
Depression (Economics)
Discount rates
Economic Crises
Exports
Financial crisis
Forecasting
Forecasts
GARCH models
Globalization
Great Depression
Investment
Loans
Macroeconomics
Markets
Maximum likelihood method
Methodology of the Social Sciences
Mortgage markets
Net present value
Securities markets
Social Sciences
Stochastic models
Stock Markets
Stocks
Studies
Time series
Time Series Analysis
U.S.A
United States of America
Volatility
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Summary:In 2007, as the US subprime mortgage market began to fall down, which reached its peak with the catastrophic collapse of the Lehman Brothers, no one was aware of that this was going to be the worst financial crisis since the Great Depression. Evaluating the advantages and disadvantages connected with financial globalization demands a pure understanding of the influence of financial volatility. Up to the present few researches focused on analyzing macroeconomic volatility of national economies. Therefore, the aim of the paper is to compare the forecast performance of stock market and macroeconomic volatility of US economy between 2007 and 2010. Accordingly, two different types of financial time series were generated, namely weekly stock returns and quarterly return on investment. Firstly, the appropriate model was determined via time series analysis. Secondly, the relevant ARCH-type model was implemented. Finally, conditional variance forecast performance of models was presented with respect to confidence interval. Furthermore, coefficient of correlation between squared residuals and coefficient of conditional variance was given.
ISSN:0033-5177
1573-7845
DOI:10.1007/s11135-012-9761-9