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題名:以追蹤資料分量迴歸方法衡量臺灣股市預期報酬與風險關係
書刊名:經濟論文叢刊
作者:陳釗而 引用關係林奎甫
作者(外文):Chen, Jau-erLin, Kuei-fu
出版日期:2015
卷期:43:3
頁次:頁297-331
主題關鍵詞:風險與預期報酬跨期關係跨期資本資產定價模型動態條件相關模型交互效果追蹤資料模型追蹤資料分量迴歸Intertemporal relation between risk and expected returnICAPMDynamic conditional correlationsInteractive-effects panel data modelPanel quantile regression
原始連結:連回原系統網址new window
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本文根據Merton(1973)跨期資本資產定價模型(IntertemporalCapitial Asset Pricing Model, ICAPM)加以計量方法與實際資料探討臺灣股票市場預期報酬與風險的跨期關係,並試圖解釋為何實證文獻對於是否存在高風險高預期報酬的跨期關係眾說紛揉。在Merton ICAPM理論模型及其所對應的條件期望值架構下,風險趨避係數應為正;我們將檢驗ICAPM在臺灣股票市場的適用性。我們先使用動態條件相關模型(Dynamic Conditional CorrelationModels)估計動態條件共變異數作為解釋變數,再由各成份股預期報酬作為被解變數以追蹤資料分量迴歸(PanelQuantile Regression)得出相對風險趨避係數估計值。實證結果顯示,在預期報酬條件期望值及中位數上,風險趨避係數皆顯著為正。我們也另外使用兩種在條件期望值的架構下並考慮序列相關及橫斷面相依特性的計量模型,所估計出的風險趨避係數也皆顯著為正。強韌性檢驗(robustnesschecks)顯示本文的估計結果並不會因解釋變數不同、風險替代變數相異及使用計量方法不一而有太大的差異。
This paper explores intertemporal relationship between risk and expected returns in the Taiwan stock market in the context of the Intertemporal Capital Asset Pricing Model. We first estimate the time-varying conditional covariances by dynamic conditional correlations models, and then treat the estimates as explanatory variables in a second-stage panel quantile regression to explore the shape of the conditional distribution of excess returns. A significant positive intertemporal relation between risk and return is identified at the conditional mean and median of the expected return distribution. This positive risk-return relation coincides with the result implied by interactive-effects panel data models and fits into the conditional expectation framework of the ICAPM allowing for cross-sectional dependence. Robustness checks indicate that our empirical results are robust to the choice of proxies of risk, explanatory variables, and econometric methodologies.
期刊論文
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3.Bai, Jushan、Ng, Serena(2008)。Large Dimensional Factor Analysis。Foundations and Trends in Econometrics,3(2),89-163。  new window
4.Campbell, John Y.(1993)。Intertemporal Asset Pricing without Consumption Data。American Economic Review,83(3),487-512。  new window
5.廖永熙、吳依正(200912)。風險與報酬之關係:亞太平洋股票市場之實證。管理科學研究,6(1),23-38。new window  延伸查詢new window
6.Bai, Jushan(2009)。Panel Data Models with Interactive Fixed Effects。Econometrica,77,1229-1279。  new window
7.Bali, Turan G.、Engle, Robert F.(2010)。The Intertemporal Capital Asset Pricing Model with Dynamic Conditional Correlations。Journal of Monetary Economics,57,377-390。  new window
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13.Campbell, John Y.(1996)。Understanding risk and return。Journal of Political Economy,104(2),289-345。  new window
14.Harvey, Campbell R.(2001)。The Specification of Conditional Expectations。Journal of Empirical Finance,8,573-637。  new window
15.Koenker, R.(2004)。Quantile regression for longitudinal data。Journal of Multivariate Analysis,91,74-89。  new window
16.Parks, Richard W.(1967)。Efficient Estimation of A System of Regression Equations when Disturbances are Both Serially and Contemporaneously Correlated。Journal of the American Statistical Association,62(318),500-509。  new window
17.Turner, Christopher M.、Startz, Richard、Nelson, Charles R.(1989)。A Markov Model of Heteroskedasticity, Risk, and Learning in the Stock Market。Journal of Financial Economics,25,3-22。  new window
18.Goyal, Amit、Santa-Clara, Pedro(2003)。Idiosyncratic Risk Matters!。Journal of Finance,58(3),975-1007。  new window
19.French, Kenneth R.、Schwert, G. William、Stambaugh, Robert F.(1987)。Expected stock returns and volatility。Journal of Financial Economics,19(1),3-29。  new window
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21.Engle, Robert F.(2002)。Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models。Journal of Business & Economic Statistics,20(3),339-350。  new window
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研究報告
1.Fontana, Alessandro(2010)。The Persistent Negative CDS-bond Basis during the 2007/08 Financial Crisis。Department of Economics, CaFoscari University of Venice。  new window
學位論文
1.李美樺(2007)。以橫斷面跨期資本資產定價模型衡量台灣股市報酬與風險之動態關係(碩士論文)。銘傳大學。  延伸查詢new window
2.林庭瑄(2010)。風險報酬之關係--台灣加權股價指數實證(碩士論文)。國立政治大學。  延伸查詢new window
圖書
1.Engle, Robert F.(2009)。Anticipating Correlations。New Jersey:Princeton University Press。  new window
 
 
 
 
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