正依賴性，不對稱性與槓桿效應在房地產指數股票型基金（ETFs）之存在

Existence of Positive Dependence, Asymmetry and Leverage Effects in Real Estate Exchange-traded Funds (ETFs)

10.6840/cycu201400253

阮海遵

房地產交易所買賣基金 ； 長期記憶模型 ； 不對稱性與槓桿效應 ； long-memory models ； real estate exchange-traded funds ； volatility asymmetry and leverage effects

中原大學國際商學碩士學位學程學位論文

2014年

碩士

狄強

英文

摘要 本研究通過比較房地產投資信託基金（REITs）的指數股票型基金（ETFs）兩個項目，即美國REIT ETF 及全球REIT ETF 探討了含有長期記憶，不對稱波動，以及槓桿效應的回報和波動性模型的性能. 本論文使用兩個短內存模型，自回歸滑動平均-指數自回歸條件異方差（ARMA-EGARCH）;與自回歸滑動平均-非對稱力量自回歸條件異方差（ARMA-APARCH）; 以及兩個長記憶模型，自回歸分數整合滑動平均- 小幅集成指數廣義自回歸條件異方差（ARFIMA-FIEGARCH）與自回歸分數整合滑動平均- 小幅集成功率不對稱自回歸條件異方差（ARFIMA-FIAPARCH）. 這個研究在美國REIT ETF 及全球REIT ETF 發現波動聚類，槓桿效應以及波動性不對稱現象的存在。此外，長記憶模型表現使用落後的回報和波動性特徵的未來值，比基於最大似然值短的內存模型更好。雖然這項研究還確定了在這兩個ETF 的波動積極的長期依賴，但是未能得出結論雙長記憶過程。儘管如此，本研究還可以在法瑪的弱式有效市場假說（EMH）（1970 年）構成挑戰，因為REIT ETF 的歷史價值仍然可以用來預測他們的未來值。最後，美國REIT ETF 被看作为比他們更平穩環球房地產投資信託基金的ETF 相當物更不穩定。美國和全球REIT ETF 的正確模型可以為了交易員，基金經理和投資者提供創造良好定義的交易策略。調查結果還可以幫研究院院士與研究員更加了解這種類型的ETF 的性質, 並打開研究未來的渠道。

This research examines the performance of return and volatility models containing long-memory, asymmetric volatility, and leverage effects by comparing two categories of Real Estate Investment Trusts (REITs) Exchange-traded Funds (ETFs), namely, US REIT ETFs and Global REIT ETFs. This thesis utilizes two short-memory models, the autoregressive moving average – exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); and autoregressive moving average – asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH); and two long-memory models, autoregressive fractionally-integrated moving average – fractionally-integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIEGARCH); and autoregressive fractionally-integrated moving average – fractionally-integrated asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-FIAPARCH). The study finds presence of volatility clustering, leverage effects and volatility asymmetry phenomena in both US and Global REIT ETFs. Also, long memory models are better in characterizing future values using lagged returns and volatilities compared to short memory models based on the maximum log-likelihood values. The research also identifies positive long-term dependence in the volatilities of both ETFs, however, fails to conclude dual long memory processes. Nevertheless, the research still can pose a challenge on the weak-form efficient market hypothesis (EMH) of Fama (1970), because historical values of REIT ETFs can still be used to predict their future values. Lastly, US REIT ETFs are seen to be more unstable than their more stationary Global REIT ETFs counterparts. The proper modeling of US and Global REIT ETFs can provide traders, fund managers and investors in creating well-defined trading strategies. Findings can also offer more understanding in the properties of this type of ETFs, and open future channels of research to academicians and researchers.

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