An Analysis on the Statistical Properties between the Sukuk and non-Sukuk in Financial Market
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Economic and financial time series sometimes exhibittrending behavior or non-stationary stochastic processin themean. An important econometric task is determining the mostappropriate form of the trend and analyzing the stationary andlong memory in the data. This study investigated the statisticaldifference between the yield of Sukuk issued on Sharia andthat of commercial bank bond in financial market. We found serial correlation in the residuals of the yield ofSukuk and PBMK bond because shock and innovation has longrange dependence on time. We found that the series of Sukukyield issued on Sharia principle are stationary, but the levelseries of commercial bank bond yield are non-stationary, theyield of commercial bank is determined by market participants. In particular the commercial bank yield displays strong volatilityclustering features. Once volatility has entered the market it isquite persistent. Persistence of shocks was infinite for nonstationaryseries. The impact of any past shock on price seriesdoes not decay over time and has strong memory. Next, weconclude that there is no evidence of a cointegrationrelationship between the Bank bond and GII yield series. Inother words, we find no arbitrage opportunity as Sukuk– bondbasis arbitrage, because there is no long-run relationshipbetween the yields of commercial non-Sukuk bond and theSukuk. Malaysia government and Bank Negara (central bank) hasregulated Sukuk GII and MITB were issued to allow Islamicbanks to hold liquid papers that meet their statutory andregulatory liquidity requirements based on Shariah principles asthey are prohibited to purchase or trade in MGS, MTB or other interest-bearing credit bonds using Sukuk.
Abstract
Economic and financial time series sometimes exhibittrending behavior or non-stationary stochastic processin themean. An important econometric task is determining the mostappropriate form of the trend and analyzing the stationary andlong memory in the data. This study investigated the statisticaldifference between the yield of Sukuk issued on Sharia andthat of commercial bank bond in financial market. We found serial correlation in the residuals of the yield ofSukuk and PBMK bond because shock and innovation has longrange dependence on time. We found that the series of Sukukyield issued on Sharia principle are stationary, but the levelseries of commercial bank bond yield are non-stationary, theyield of commercial bank is determined by market participants. In particular the commercial bank yield displays strong volatilityclustering features. Once volatility has entered the market it isquite persistent. Persistence of shocks was infinite for nonstationaryseries. The impact of any past shock on price seriesdoes not decay over time and has strong memory. Next, weconclude that there is no evidence of a cointegrationrelationship between the Bank bond and GII yield series. Inother words, we find no arbitrage opportunity as Sukuk– bondbasis arbitrage, because there is no long-run relationshipbetween the yields of commercial non-Sukuk bond and theSukuk. Malaysia government and Bank Negara (central bank) hasregulated Sukuk GII and MITB were issued to allow Islamicbanks to hold liquid papers that meet their statutory andregulatory liquidity requirements based on Shariah principles asthey are prohibited to purchase or trade in MGS, MTB or other interest-bearing credit bonds using Sukuk.
참고문헌 (28)
- Baum, L. E., "Statistical inference for probabilistic functions of finitestate Markov chains", Annals of Mathematical Statistics, 37, pp.1554~1563 (1966)
- Campbell, J. Y., "Equity Volatility and Corporate Bond Yields", Journal of Finance, 58(6), pp.2321~2350 (2003)
- Duffie, D., "Transform analysis and asset pricing for affine jump diffusions", Econometrica, 68, pp.1343~1376 (2000)
- Dickey, D., "Distribution of the Estimators for Autoregressive TimeSeries with a Unit Root", Journal of the American Statistical Association, 74, pp.427~431 (1979)
- Dickey, D. A., "Likelihood ratio statistics for autoregressive time series with a unit root", Econometrica, 49(4), pp.1057~1072 (1981)
- Dolado, J., "Cointegration and unit roots", Journal of Economic Surveys, 4(3), pp.249~273 (1990)
- Engle, R., "Autoregressive conditional heteroscedasticity with estimates of the variance of the U.K. inflation", Econometrica, 50, pp.987~1008 (1982)
- Engle, R. F., "Multivariate Simultaneous Generalized ARCH", Econometric Theory, 11, pp.122~150 (1995)
- Engle, R. F., "Measuring and Testing the Impact of News on Volatility", Journal of Finance, 48(5), pp.1749~1778 (1993)
- Fleming, J., "Information and Volatility Linkages in the Stock, Bond, and Money Markets", Journal of Financial Economics, 49(1), pp.111~137 (1998)
- Granger, C. W. J., "Investigating Causal Relations by Econometric Models and Cross-spectral Methods", Econometrica, 37(3), pp.424~438 (1969)
- Gallant, A. R., "Estimation of stochastic volatility models with diagnostics", Journal of Econometrics, 81(1), pp.159~192 (1997)
- Hamilton, J., "A new approach to the economic analysis of nonstationary time series and the business cycle", Econometrica, 57, pp.357~384 (1989)
- Johansen, S., "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models", Econometrica, 59(6), pp.1551~1580 (1991)
- 정상률, "카타르의 금융정책 분석", 중동문제연구, 11(4), pp.51~76 (2012), 중동문제연구소
- Kroner, K. F., "Modeling Asymmetric Comovements of Asset Returns", Review of Financial Studies, 11(4), pp.817~844 (1998)
- MacKinnon, J. G., "Long-Run Economic Relationships: Readings in Cointegration", pp.266~276 (1991), Oxford University Press
- Mcleod, A.I., "Diagnostic Checking ARMA Time Series Models Using Squared-Residual Autocorrelation", Journal of Time Series Analysis, 4, pp.269~273 (1983)
- Kwiatkowski, D., "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root", Journal of Econometrics, 54, pp.159~178 (1992)
- Ng, S., "Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag", Journal of the American Statistical Association, 90, pp.268~281 (1995)
- Ng, S., "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power", Econometrica, 69, pp.1519~1554 (2001)
- Nelson, C. R., "Trends and random walks in macroeconomic time series", Journal of Monetary Economics, 10(2), pp.139~162 (1982)
- Osterwald-Lenum, M., "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics", Oxford Bulletin of Economics and Statistics, 54(3), pp.461~471 (1992)
- Perron, P., "Trends and random walks in macroeconomic time series", Journal of Economic Dynamics and Control, 12(12), pp.297~332 (1988)
- Perron, P., "Useful Modifications to Some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties", Review of Economic Studies, 63, pp.435~463 (1996)
- Phillips, P.C.B., "Testing for Unit Roots in Time Series Regression", Biometrika, 75, pp.335~346 (1988)
- Stock, J.H., "Handbook of Econometrics, Volume IV" (1994), North Holland
- Tsay, R. S., "Analysis of Financial Time Series, third ed" (2010), Wiley