亞洲匯率指數與指數型基金之預測分析-以ARFIMA-FIAPARCH模型為例

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亞洲匯率指數與指數型基金之預測分析-以ARFIMA-FIAPARCH模型為例

The Forecast of Asian Currency Exchange Index and Exchange-Traded Funds: The Analysis of ARFIMA-FIAPARCH Models

高秀貞 , Masters　　Advisor：陳若暉　　

繁體中文

大中華單一化貨幣； ARFIMA ； RiskMetrics ； ARFIMA-FIGARCH ； ARFIMA- FIAPARCH ； China Currency Unit ； ARFIMA ； RiskMetrics ； ARFIMA-FIGARCH ； ARFIMA- FIAPARCH

Abstract │ Reference (57) │ Altmetrics

Abstract 〈TOP〉

Parallel Abstract 〈TOP〉

The fluctuating exchange rate is violent through the influence at financial crises. This had been impelled the finacial environment during the 1997 Asia financial crisis. As Asia economies particularly hard hit by the crisis, the unstable exchange rate has been much attention. This study refers to the structure of EURO currency basket, and constructs the Chinese Currency Unit（CCU）using the weights based on GDP per capita, export and net reserves of China, Taiwan and Hong Kong to measure Chinese Currency Unification’s central rate from 1992/3 to 2016/2. This paper valuates the exchange rate fluctuation related to Asia and Greater China region among variables including CCU, Bloomberg JPMorgan Asia Dollar Index, iPath GEMS Asia 8 ETN(AYT) , WisdomTree Chinese Yuan Strategy Fund (CYB ETF), China REER, Taiwan REER, and Hong Kong REER.
This study uses RiskMetrics、ARFIMA- FIAPARCH、ARFIMA- FIGARCH Models for empirical analysis, and the results show that the modified CCU(SDR) has CCU stability and  better forecasting than regular CCU. Thus, this is suitable for Greater China region to use CCU(SDR) making monetary policy in future. The results also reveal that the real effective exchange rate of Taiwan and China and the CYB ETF appear the asymmetry of market volatility for having a negative impact on the volatility. The major financial turmoils impact on changing volatility, and the previous returns will have a negative impact on current return. ADXY Index is found to have a long memory characteristic and high stability, and it has positive effect on market volatility. As long as using the historical exchange rate fluctuations properly, policy makers can observe through the influences of various variables and exchange rate of earlier and later periods to stable the changes of currencies in Asia and the Greater China region. The adoption of suitable polices can be reached in advance in response of the shock of the global financial crisis.
This study uses ADXY index and AYT ETN based on the measurements of RiskMetrics, ARFIMA-FIGARCH, FIAPARCH models. From the prospectives of short position and long position to analyze the goodness-of-fit model for Value at Risk (VaR), the comparison of the distribution analysis includes Normal distribution, Student-t distribution, and Skewed- Student- t distribution. That results show that the best goodness-of-fit model and the accuracy of forecasting performance is FIGARCH model and next-best is FIAPARCH model. Among overall distribution, Skewed- Student-t distribution in regression analysis is better than Normal distribution. In addition to CCU and Hong Kong’s real exchange rate variables setting into the Normal distribution, the results of FIGARCH and FIAPARCH models are similar, while the performance of RiskMetrics model is excellent.

Reference ( 57 ) 〈TOP〉

1. 王啟明、陳怡君、蕭倩琳(2009)，「歐洲與亞洲共同貨幣政策之發展: 從比較區域研究角度分析」，全球政治評論，第二十五期，117-150頁。
連結：
2. 呂欣怡(2005)，大中華貨幣單一化與貨幣和貿易政策關聯性之研析，中原大學企業管理學系碩士學位論文。
連結：
3. 呂湘君(2010)，亞洲單一貨幣化與風險值之相關研究，中原大學企業管理學系碩士學位論文。
連結：
4. 杜玉振、魏郁珣(2009)，「多空交易部位之最適風險值模型研究－以股票、商品及外匯市場為例」，創新與管理，第七卷第一期，1-28頁。
連結：
5. 林楚雄、張簡彰程、曾正杰(2008)，「風險矩陣波動修正之風險值估計」，輔仁管理評論，第15卷第2期， 61-82頁。
連結：

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