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Journal of Economics and Finance

Erschienen in:

01.04.2011

The exchange traded funds’ pricing deviation: analysis and forecasts

verfasst von: Richard A. DeFusco, Stoyu I. Ivanov, Gordon V. Karels

Erschienen in: Journal of Economics and Finance | Ausgabe 2/2011

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Abstract

In this paper, we study the pricing deviations of the three most liquid Exchange Traded Funds from the price of the underlying index. We examine Spider, Diamonds, and Cubes and find that their price deviation is predictable and nonzero. Therefore, the pricing deviation can be considered an additional cost of administering an Exchange Traded Fund. The reason for the predictability of the pricing deviation stems from its stationarity. The reasons for the pricing deviation being nonzero are the specific price discovery processes and dividend accumulation and distribution for this asset class. The pricing deviation can be used as a performance metric of Exchange Traded Funds and might motivate arbitrage strategies.

Vorheriger Artikel The wisdom of the few or the wisdom of the many? An indirect test of the marginal trader hypothesis

Nächster Artikel Timing of price clustering and trader behavior in the foreign exchange market: evidence from Taiwan

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The ETFs analyzed in this study are all Unit Investment Trusts.

Diamonds are an exception, they pay accumulated dividends monthly.

The NAV is calculated as of 4:00 p.m. and the ETF price as of 4:15 p.m.

Discussed in detail in Elton et al. (2002).

The Jarque-Berra normality test is calculated by using the skewness (S) and kurtosis (K) in the following way: \( JB = n\left( {\frac{{S^2 }}{6} + \frac{{\left( {K - 3} \right)^2 }}{24}} \right) \approx \chi^2 (2) \).

A standard test for ARCH is based on the statistic \( LM = nR^2 \) where the R² is from the auxiliary testing regression of \( e_t^2 = \alpha_0 + \alpha_1 e_{t - 1}^2 + \ldots + \alpha_p e_{t - p}^2 + \xi_t \).

We test for the presence of GARCH Model with Normally Distributed Residuals (Bollerslev 1986); GARCH Model with t-Distributed Residuals; GARCH-M Model Square Root Function Specification; GARCH-M Model Linear Function Specification (French et al. 1987); GARCH-M Model Logarithmic Function Specification; EGARCH Model (Nelson 1991); QGARCH Model (Sentana 1995), GJR-GARCH Model (Glosten et al. 1993), and TGARCH Model (Rabemananjara and Zakoian 1993).

The specification of the conditional variance in the EGARCH Model by Nelson (1991) is as follows: \( \log \left( {\sigma_t^2 } \right) = \omega + \sum\limits_{j = 1}^q {\beta_j \log \left( {\sigma_{t - j}^2 } \right) + \sum\limits_{i = 1}^p {\alpha_i } \left| {\frac{{\varepsilon_{t - i} }}{{\sigma_{t - i} }}} \right| + \sum\limits_{k = 1}^r {\gamma_k } \frac{{\varepsilon_{t - k} }}{{\sigma_{t - k} }}} \), the presence of asymmetric leverage EGARCH effects are tested with \( \gamma_k \ne 0 \).

Alexander C, Barbosa A (2005) The Spider in the Hedge. ISMA Centre Finance Discussion Paper No. DP2005-05. Available at SSRN: http://ssrn.com/abstract=706261. Accessed 15 Mar 2001

Bollerslev T (1986) Generalized autoregressive conditional heteroskedasticity. J Econom 31:307–327. doi:10.1016/0304-4076(86)90063-1 CrossRef

Broom KD, Van Ness RA, Warr RS (2007) Cubes to Quads: The Move of The QQQ ETF from AMEX to NASDAQ. J Econ Bus 59:520–535. doi:10.1016/j.jeconbus.2007.01.002 CrossRef

Campbell JY, Lo AW, MacKinlay AC (1997) The Econometrics of Financial Markets. Princeton University Press

Chou RK, Chung H (2006) Decimalization, trading costs, and information transmission between ETFs and index futures. J Futures Mark 26:131–151. doi:10.1002/fut.20189 CrossRef

Elton MJ, Gruber MJ, Comer G, Li K (2002) Spider: Where are the bugs? J Bus 75:453–472. doi:10.1086/339891 CrossRef

Enders W (2004) Applied Econometric Time Series. Wiley Series in Probability and Statistics

Engle RF (2001) GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics. J Econ Perspect 15:157–168CrossRef

Engle RF, Granger CWJ (1987) Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica 55:251–276. doi:10.2307/1913236 CrossRef

Engle RF, Sarkar D (2006) Premiums-Discounts and Exchange Traded Funds. J Deriv 13:27–45CrossRef

French KR, Schwert GW, Stambaugh RF (1987) Expected stock returns and volatility. J Financ Econ 19:3–29. doi:10.1016/0304-405X(87)90026-2 CrossRef

Gastineau GL (2004) The Benchmark Index ETF Performance Problem: A Simple Solution. J Portf Manag 30:96–103CrossRef

Glosten LR, Jagannathan R, Runkle DE (1993) On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. J Finance 48:1779–1801. doi:10.2307/2329067 CrossRef

Hasbrouck J (1995) One Security, Many Markets: Determining the Contributions to Price Discovery. J Finance 50:1175–1199. doi:10.2307/2329348 CrossRef

Heij C, De Boer P, Franses PH, Kloek T, Van Dijk HK (2004) Econometric Methods with Applications in Business and Economics. Oxford University Press

Kawaller IG (1991) Determining the Relevant Fair Value(s) of S&P 500 Futures: A Case Study Approach. J Futures Mark 11:453–460. doi:10.1002/fut.3990110405 CrossRef

Martens M (1998) Price Discovery in High and Low Volatitlity Periods: Open Outcry versus Electronic Trading. J Int Financ Mark Inst Money 8:243–260. doi:10.1016/S1042-4431(98)00044-4 CrossRef

Nelson D (1991) Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica 59:347–370CrossRef

Rabemananjara R, Zakoian JM (1993) Threshold Arch Models and Asymmetries in Volatility. J Appl Econ 8:31–49. doi:10.1002/jae.3950080104 CrossRef

Sentana E (1995) Quadratic ARCH Models. Rev Econ Stud 62:639–661CrossRef

Yu L (2005) Basket Securities, Price Formation, and Informational Efficiency. Working Paper. Available at SSRN: http://ssrn.com/abstract=862604. Accessed 15 Mar 2001

Titel: The exchange traded funds’ pricing deviation: analysis and forecasts
verfasst von: Richard A. DeFusco
Stoyu I. Ivanov
Gordon V. Karels
Publikationsdatum: 01.04.2011
Verlag: Springer US
Erschienen in: Journal of Economics and Finance / Ausgabe 2/2011
Print ISSN: 1055-0925
Elektronische ISSN: 1938-9744
DOI: https://doi.org/10.1007/s12197-009-9090-6

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