导　　师： 杨立洪

学科专业： 070103

授予学位： 硕士

作　　者： ;

机构地区： 华南理工大学

摘　　要： 波动率是资产收益率的条件方差。刻画和预测资产收益率波动率的研究是当前金融领域非常重要的内容，无论是在资产定价、风险管理还是在资产组合。人民币汇率作为金融时间序列的一种，其多元波动率的研究还处于初始阶段。由于K个不同国家对人民币汇率的协方差矩阵的自由变量有K/(K+1/)//2个，若对每个自由变量都构造一个时间序列模型，则会造成大量的模型参数要估计。在这种背景下，基于独立成分分析的多元波动率模型得到很好的应用。 本文主要研究了基于独立成分分析的多元波动率模型，通过对IC-GARCH模型进行推广，得到IC-GJRGARCH模型和IC-IGARCH模型。重点研究了传统模型、改进前模型与改进后的模型在多元人民币汇率波动率预测的MAD对比。研究结果表明，基于独立成分分析的IC-GARCH优于OGARCH和CCC模型，而且经推广后的IC-IGARCH和IC-GJRGARCH模型预测效果要优于IC-GARCH。 本文有如下主要研究成果： /(1/)研究了基于独立成分分析的多元波动率模型IC-GJRGARCH模型和IC-IGARCH模型。首先用FASTICA算法对多元人民币汇率收益率进行独立成分分析，提取出条件不相关的独立成分，然后对各个条件不相关的独立成分构建GJRGARCH模型和IGARCH模型，并对模型进行检验和参数估计。用多国家对人民币汇率的中间价的1194条数据进行实证分析，给出了实证分析的结果。 /(2/)对改进后模型IC-IGARCH模型进行不同残差分布下的研究。研究了IC-IGARCH模型残差类型分别在高斯分布、广义误差分布和t分布的预测效果MAD对比。研究结果显示，改进后模型IC-IGARCH模型的残差类型为广义误差分布和t分布是的预测效果优于其在高斯分布下的预测效果。 最后，简单探讨了基于独立成分分析的多元波动率模型的降维技术和各模型的预测效果对比的评价标准，提出未来的研究方向。 The volatility is the conditional variance of return on assets. Characterization and theprediction of volatility of return on assets is a very important element of the financial sector,whether in asset pricing, risk management or portfolio. RMB exchange rate as a financial timeseries, research on multiple volatility is still in its initial stage. As free variables of K differentcountries against the RMB exchange rate covariance matrix are K/(K+1/)//2, Construct a timeseries model for each free variable will result in a large number of model parameters toestimate. So in this context, multivariate volatility models based on independent componentanalysis are widely used. This paper studies a multivariate volatility model based on independent componentanalysis, improving the IC-GARCH model to get IC-GJRGARCH model and IC-IGARCHmodel. Focus on the MAD comparison of RMB exchange rate volatility forecast for thetraditional model, improving the former model and the improved model. The results show that,based on independent component analysis of IC-GARCH better than OGARCH and CCCmodels, but also through the promotion of the IC-IGARCH and IC-GJRGARCH model,prediction is superior to the IC-GARCH. This article has the following main research achievements: 1. Research multivariate volatility model IC-GJRGARCH model and IC-IGARCHmodel based on independent component analysis. Firstly conduct the independent componentanalysis for the return of the RMB exchange rate using FASTICA algorithm. Secondly, buildthe GJR GARCH model and the IGARCH model for the conditional independent componentsand do model testing and parameter estimation. The Empirical Analysis and its result of the1194records from many countries against RMB exchange rate is conducted. 2. Carry out research on the residual distribution of the improved model IC-IGARCHmodel. Compare the MAD of RMB exchange rate volatility forecast with the residuals in theGaussian distribution, generalized error distribution and t distribution. The results show thatthe forecast of the improved model IC-IGARCH model with residual type of generalized errordistribution and t distribution is better than its prediction with the Gaussian distribution. Finally, a brief discussion of the evaluation criteria of the multivariate volatility modelbased on independent component analysis for dimension reduction techniques and modelprediction, proposed future research directions.

关 键 词： 人民币汇率 多元波动率 独立成分分析

分 类 号： [F224 F832.6]

领　　域： [经济管理] [经济管理]