A New Method for Setting Futures Portfolios’ Maintenance Margins: Evidence from Chinese Commodity Futures Markets
Table 2
Descriptive statistics of return series.
Parameters
Number 1 soybeans
Copper cathode
Cotton
Crude soybean oil
Portfolio A
Portfolio B
Portfolio C
Portfolio D
Mean
0.0004
0.0003
−0.0001
0.0002
0.0002
0.0003
0.0001
0.0002
Maximum
0.0612
0.0791
0.1079
0.0768
0.0377
0.0738
0.0437
0.0519
Minimum
−0.0583
−0.1061
−0.1343
−0.1316
−0.0449
−0.0664
−0.0915
−0.0827
Std-Dev
0.0115
0.0184
0.0121
0.0162
0.0093
0.0103
0.0095
0.0118
Kurtosis
8.8896
5.4383
4.0254
8.3548
5.8681
6.1527
5.8674
6.4317
Skewness
−0.1825
−0.4028
−0.2069
−0.8634
−0.4438
−0.5167
−0.6872
−0.7105
Jarque-Bera
1976.0640 (0.0000)
1746.2950 (0.0000)
2510.1400 (0.0000)
1435.2574 (0.0000)
511.5199 (0.0000)
1176.0864 (0.0000)
987.1367 (0.0000)
1039.5378 (0.0000)
ARCH(1)-LM
123.9881 (0.0000)
44.7033 (0.0009)
31.8447 (0.0000)
36.2749 (0.0000)
72.3283 (0.0000)
83.1259 (0.0000)
46.8973 (0.0000)
93.6217 (0.0000)
ADF
−18.8755 (0.0000)
−19.3994 (0.0000)
−22.0336 (0.0000)
−21.7358 (0.0000)
−19.0045 (0.0000)
−19.8639 (0.0000)
−20.1693 (0.0000)
−19.9476 (0.0000)
Notes: the figures in parenthesis denote values of statistics. Std-Dev stands for the standard deviation. The Jarque-Bera statistic tests for the null hypothesis of normality distribution. The ARCH(1)-LM statistic tests for the null hypothesis of the inexistence of heteroscedasticity until the lag order is equal to 1. For the ADF test, the number of lags is estimated through the Akaike Information Criterion (AIC).
