﻿ 贵金属期货价格的时间序列分析及期货池初期优选方案 Time Series Analysis for Precious Metals’ Futures Price and Pilot for Selecting Futures Pool

Statistics and Application
Vol.07 No.03(2018), Article ID:25667,9 pages
10.12677/SA.2018.73041

Time Series Analysis for Precious Metals’ Futures Price and Pilot for Selecting Futures Pool

Qingyuan Hong, Yilin Zhuo, Yutao Zhong

School of Mathematical Sciences, Shanghai Jiaotong University, Shanghai

Received: Jun. 4th, 2018; accepted: Jun. 18th, 2018; published: Jun. 28th, 2018

ABSTRACT

This paper summarizes the basic statistical characteristics of the time series data of the logarithmic return of precious metals futures in the past 2011~2016 years, establishes the ARMA-GARCH model and EGARCH model, and carries out the risk analysis. Based on these results, a pilot strategy for selecting precious metal futures pool with more profit opportunities is also proposed.

Keywords:Precious Metal, Futures, GARCH Model, VaR

1. 引言

2. 贵金属合约数据的基本统计特征

3. ARMA-GARCH建模

3.1. 示例分析

3.1.1. 沪锌1612 (zn1612)

Figure 1. Skewness and kurtosis

Figure 2. Histogram and experience distribution curve of logarithmic rate of return

Figure 3. Q-Q graph

3.1.2. 沪铝1401 (Al1401)

Figure 4. ACF graph

Figure 5. Histogram and experience distribution curve of logarithmic rate of return

Figure 6. Q-Q graph

Figure 7. ACF graph

3.2. 结果分析

4. EGARCH模型

4.1. 沪锌1612

C(3) = −0.102460在5%水平下显著，该股票杠杆效应不明显。当at1 < 0时，它给条件方差的对数带来的冲击大小为0.138832倍；当at−1 > 0时，它给条件方差的对数带来的冲击大小为−0.066088倍。图8左子图所示的信息冲击曲线可直观看出沪锌1612对利空和利多消息的反应不对称，利空消息产生的波动稍大于利多消息，但都很微弱。

4.2. 沪铝1401

C(3) = 0.219863在5%水平下显著，该股票杠杆效应不明显。当at−1 < 0时，它给条件方差的对数带来的冲击大小为0.011924倍；当at−1 > 0时，它给条件方差的对数带来的冲击大小为0.204672倍。如图8右子图所示的信息冲击曲线可直观看出沪铝1401对利空和利多消息的反应不对称，利多消息产生的波动稍大于利空消息，但都很微弱。

4.3. 结论

5. 风险值(VAR)

Figure 8. Information impact curve

Figure 9. Q-Q graph

Figure 10. Box graph

6. 结论

Time Series Analysis for Precious Metals’ Futures Price and Pilot for Selecting Futures Pool[J]. 统计学与应用, 2018, 07(03): 350-358. https://doi.org/10.12677/SA.2018.73041

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