The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund
碩士 === 輔仁大學 === 應用統計學研究所 === 94 === The main goal for this research is to evaluate the performance of three different risk models for Taiwan Top50 Tracker Fund which type is Exchange Traded Fund (ETF). The result might be useful and helpful for investors or financial companies to control their risk...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2006
|
Online Access: | http://ndltd.ncl.edu.tw/handle/43359299717320796232 |
id |
ndltd-TW-093FJU00506042 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-093FJU005060422016-06-01T04:14:43Z http://ndltd.ncl.edu.tw/handle/43359299717320796232 The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund 衍生性金融商品風險值估計-以台灣50指數ETF價格為例 Sheng-Yuan Chuang 莊盛元 碩士 輔仁大學 應用統計學研究所 94 The main goal for this research is to evaluate the performance of three different risk models for Taiwan Top50 Tracker Fund which type is Exchange Traded Fund (ETF). The result might be useful and helpful for investors or financial companies to control their risk on ETF investment. Therefore, in this work, two main goals have been set. First, according to the historical data of Taiwan Top50 Tracker Fund, the Value at Risk models are estimated using three moving-window size in combination with three different models. Using the results as the baseline solution, the appropriate VaR model for ETF will be developed from comparison. Second, the trend of ETF can be determined as three different periods, increasing, decreasing and steady. The appropriate VaR models for marketing volatility will be worth to develop and evaluate. The results will offer flexible and forceful methods for administrators to control their risk at investment. Results illustrate the differences between the three methods and highlight the influence of moving-window size on the analysis. There are two findings from this work. First, the appropriate window size suggested for further study is 65 days. It is more sensitive to detect the volatility of VaR of ETF. The other, a comparison of the VaR models of three different trend periods, it is hard to examine the appropriate model for different trend of ETF. However, the administrators can inference the results for further study to detect and diversify the potential risk of ETF. Rwei-Ju Chuang 莊瑞珠 2006 學位論文 ; thesis 84 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 輔仁大學 === 應用統計學研究所 === 94 === The main goal for this research is to evaluate the performance of three different risk models for Taiwan Top50 Tracker Fund which type is Exchange Traded Fund (ETF). The result might be useful and helpful for investors or financial companies to control their risk on ETF investment.
Therefore, in this work, two main goals have been set. First, according to the historical data of Taiwan Top50 Tracker Fund, the Value at Risk models are estimated using three moving-window size in combination with three different models. Using the results as the baseline solution, the appropriate VaR model for ETF will be developed from comparison. Second, the trend of ETF can be determined as three different periods, increasing, decreasing and steady. The appropriate VaR models for marketing volatility will be worth to develop and evaluate. The results will offer flexible and forceful methods for administrators to control their risk at investment.
Results illustrate the differences between the three methods and highlight the influence of moving-window size on the analysis. There are two findings from this work.
First, the appropriate window size suggested for further study is 65 days. It is more sensitive to detect the volatility of VaR of ETF. The other, a comparison of the VaR models of three different trend periods, it is hard to examine the appropriate model for different trend of ETF. However, the administrators can inference the results for further study to detect and diversify the potential risk of ETF.
|
author2 |
Rwei-Ju Chuang |
author_facet |
Rwei-Ju Chuang Sheng-Yuan Chuang 莊盛元 |
author |
Sheng-Yuan Chuang 莊盛元 |
spellingShingle |
Sheng-Yuan Chuang 莊盛元 The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund |
author_sort |
Sheng-Yuan Chuang |
title |
The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund |
title_short |
The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund |
title_full |
The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund |
title_fullStr |
The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund |
title_full_unstemmed |
The VaR Models for financial derivatives : The case of Taiwan Top50 Tracker Fund |
title_sort |
var models for financial derivatives : the case of taiwan top50 tracker fund |
publishDate |
2006 |
url |
http://ndltd.ncl.edu.tw/handle/43359299717320796232 |
work_keys_str_mv |
AT shengyuanchuang thevarmodelsforfinancialderivativesthecaseoftaiwantop50trackerfund AT zhuāngshèngyuán thevarmodelsforfinancialderivativesthecaseoftaiwantop50trackerfund AT shengyuanchuang yǎnshēngxìngjīnróngshāngpǐnfēngxiǎnzhígūjìyǐtáiwān50zhǐshùetfjiàgéwèilì AT zhuāngshèngyuán yǎnshēngxìngjīnróngshāngpǐnfēngxiǎnzhígūjìyǐtáiwān50zhǐshùetfjiàgéwèilì AT shengyuanchuang varmodelsforfinancialderivativesthecaseoftaiwantop50trackerfund AT zhuāngshèngyuán varmodelsforfinancialderivativesthecaseoftaiwantop50trackerfund |
_version_ |
1718286822464815104 |