Browse

Wavelet-Based Time Series Modeling For The Exchange Rates

Cited 0 time in Web of Science Cited 0 time in Scopus
Authors
유혜진
Advisor
오희석
Major
자연과학대학 통계학과
Issue Date
2016-08
Publisher
서울대학교 대학원
Keywords
WaveletsDWTMRAEbayesThreshExchange rates
Description
학위논문 (석사)-- 서울대학교 대학원 : 통계학과, 2016. 8. 오희석.
Abstract
This paper proposes a new approach to analyze the exchange rates. Two kinds of methods, based on the wavelet theory, are applied to the time series and fitted using ARIMA modeling. First method is Wavelet Decomposition. The series are decomposed into wavelet coefficients by Multiresolution Analysis (MRA). One of significant wavelet coefficients is fitted by ARIMA model. Second method is EbayesThresh package. Series with removed noise through threshold are also fitted. To illustrate the usefulness of our methodology, we carry out an empirical application using the Korean exchange rates relatives to US dollar, Yen and Euro. By comparing models after two treatments with the model of raw data, this paper will find how effectively wavelet decomposition and EbayesThresh work to explain the data. Therefore, we conclude that MRA and EbayesThresh extract important information from the original data and help us to look into the data with a new angle.
Language
English
URI
http://hdl.handle.net/10371/131316
Files in This Item:
Appears in Collections:
College of Natural Sciences (자연과학대학)Dept. of Statistics (통계학과)Theses (Master's Degree_통계학과)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse