Translated Title

Forecasting Volatility of Shanghai Composite Index Using Markov-Switching Multifractal Model with the Fat-tailed Innovation Distributions

Translated Abstract

The　Markov-switching　multifractal　model　of　asset　returns　with　generalized　error　distribution　(MSM-GED　henceforth)　is　introduced　as　an　extension　to　the　Markov-switching　multifractal　model　of　asset　returns(MSM).Issues　of　parameters　estimation　and　volatility　forecasting　were　also　discussed.The　forecasting　capability　of　MSM-GED　is　evaluated　empirically　in　a　forecasting　analysis　using　daily　returns　of　Shanghai　Composite　Index.The　analysis　shows　that　multifractility　indeed　emerge　in　daily　return　series　of　Shanghai　Composite　Index.Compared　with　GARCH　and　FIGARACH　model,MSM　performs　better　in　volatility　forecasting,especially　in　predicting　the　medium　and　long　term　volatility.Overall,MSM-GED　dominates　GARCH　and　FIGARACH　model　and　is　a　good　alternative　volatility　modelling　for　asset　pricing　and　risk　management.

Translated Keyword

fat-tailed innovations
markov-switching multifractal model
volatility forecasting

Conference Name

第十六届中国管理科学学术年会

Organizers

中国优选法统筹法与经济数学研究会

Place

太原

Date

2014-10-17

Sponsor

Classification

Type

Project Name

Project No.

Access Number

WF:confartical8503102

Language

Chinese

Corresponding s email

Author Info