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Yet if the PSRM fails to achieve its projected electoral success--due either to the incumbent Democratic Party's government use of "administrative resources" or to a shift in electoral preferences--its benefactors in Moscow may intervene to avoid what they would likely perceive as another Western plot to curtail Russia's sphere of influence in the region.
Earlier this year, a prominent Ukrainian security analyst raised concerns about a potential plot by Moldova's largely ceremonial President Dodon to take power away from the government in the context of mass anti-government protests organized by the PSRM on September 24, 2017.
In order to cope with the above-listed problems, we develop a new method for setting futures portfolios' maintenance margins by combining three models, namely, the GARCH (1,1)-t model nested multivariate t-Copula, the peaks over threshold (POT) model, and the power spectral risk measures (PSRM).
Finally, the dynamic risk of the futures portfolio pf is estimated by PSRM, which is an important part of setting the maintenance margins.
Acerbi [15] pointed that PSRM can not only reflect the risk aversion, but also perfectly fit the fact that the absolute risk aversion coefficient decreases progressively while the relative risk aversion coefficient roughly stays as a constant.
PSRM = [[integral].sup.1.sub.0] [X.sub.[alpha]] [phi](p)= [[integral].sup.1.sub.0] [X.sub.[alpha]] (1 - a) [(1 - p).sup.-a] adp, 0 < a < 1, (18)
[17] manifested that PSRM is sensitive to the changes of volatility when the relative risk aversion coefficient a is equal to 0.7.
After determining the parameters of our method, we can calculate the PSRM values based on (18).
where [,t+1] stands for the actual loss rate of futures portfolio on day t +1, [] is the failure rate, [PSRM.sub.t+1,t] is the estimated value by using the PSRM method, and T represents the length of the observation period.
In such cases, when [] is smaller than [p.sup.*], the PSRM method is too conservative so that it overestimates the risk, while when [] is bigger than [p.sup.*], the PSRM method tends to underestimate the risk.
In view of the problems in setting futures portfolios' maintenance margins for the Chinese commodity futures exchanges, we propose a new method that integrates the GARCH (1,1)-t model nested multivariate t-Copula, the POT model, and PSRM. To verify the validity of the method, we firstly construct four kinds of futures portfolios, that is, the Future Portfolios A, B, C, and D, and then by using the new method set the maintenance margins of the Future Portfolios A, B, C, and D.