QQ客服 官方微博 反馈留言

	不同频率数据在金融市场VaR测度中的对比研究——基于低频、高频与超高频数据模型; Measuring Financial Risks Using Different Frequency Data——Based on Ultra-high Frequency,High Frequency and Low Frequency Data Model
	苗晓宇
	2011
关键词	风险测度 高频数据 已实现波动 UHF-GARCH模型 risk measure high frequency data realized volatility UHF-GARCH
英文摘要	首先计算了已实现波动率和超高频波动率,然后使用ArfIMA(0,d,0)-SkST模型计算了条件波动,最后对条件波动调整后的收益率进行了拟合并计算出了VAr值。实证结果发现,使用高频数据甚至超高频数据测量金融风险的准确性并不比低频数据高很多,如果选用模型恰当,完全能够使用低频数据得到高频数据的精度。; Firstly,this paper calculate the realized volatility and the ultra-high frequency volatility,and then use the ARFIMA(0,d,0)-SKST model to calculate the conditional volatility,finally the author calculates and compare the VAR which was calculated by asset return adjusted by conditional volatility.The empirical results show that the use of high-frequency data and even ultra-high frequency data did not improve the accuracy of measurement of financial risk significantly,if selected sensibly,using low frequency data can also get the precision of high-frequency data,the article finally analyzes the applicability of the high-frequency data.
语种	zh_CN
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/111746]
专题	经济学院－已发表论文
推荐引用方式 GB/T 7714	苗晓宇. 不同频率数据在金融市场VaR测度中的对比研究——基于低频、高频与超高频数据模型, Measuring Financial Risks Using Different Frequency Data——Based on Ultra-high Frequency,High Frequency and Low Frequency Data Model[J],2011.
APA	苗晓宇.(2011).不同频率数据在金融市场VaR测度中的对比研究——基于低频、高频与超高频数据模型..
MLA	苗晓宇."不同频率数据在金融市场VaR测度中的对比研究——基于低频、高频与超高频数据模型".(2011).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。