Page 278 - Contributed Paper Session (CPS) - Volume 6

CPS1929 Takayuki M.
where we regard qi,j,t as the short run correlation between assets i and j,
whereas ρi,j,t is a slowly moving long run correlation. Rewriting the first
equation of system as

conveys the idea of short run fluctuations around a time-varying long run
relationship. The idea captured by the DCC-MIDAS model is similar to that
underlying GARCH-MIDAS. In the GARCHMIDAS the short run component is
a GARCH component, based on daily returns, that moves around a long-run
component driven by realized volatilities computed over a monthly basis, see

Colacito et al. (2011).

3. Empirical Analysis
We apply the DCC-MIDAS with GARCH-MIDAS-EPU model to Nikkei225
and TOPIX100 data listed on TSE from June 1988 to April 2016 in order to
investigate the relation between economic policy uncertainty and financial
market volatility in Japanese financial market. Here is an example of the results
of our empirical analysis. Table 1 shows the result of GARCH-MIDAS-EPU for
NK225 from January 1991 to April 2016. Figures below show the plots of
estimated short- and long-run variances and correlations for Japan Tobacco
(JT) Inc. (2914) and Nikkei225.

Table 1 Result of GARCH-MIDAS-EPU for NK225 from January 1991 to April 2016

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