Synthetic versus Physical Exchange Traded Funds. Spillover and Asymmetric -Volatility Effects

  • Askar KOSHOEV Department of Accounting Chung Yuan Christian University, Taiwan


Earning popularity synthetic exchange-traded funds which track their benchmarks by taking positions in derivative contracts are subjects of many debates concerning potential negative effects they may cause. At the moment, available empirical results are scarce and ambiguous. This research investigates the impact of synthetic funds on the stock market by comparing them to their physical alternatives. The spillover and asymmetric volatility effects were identified and analyzed by the deployment of the EGARCH-M-ARMA model. Local legislation on the Chinese market caused the creation of several physical and synthetic ETFs which track same benchmarks. This unique conditions can be employed in order to examine the effects of synthetic ETFs on the market. The sample of this study comprises ETFs which track Chinese A-shares but are listed or cross-listing in Hong Kong or New York stock exchanges. This study broadens the knowledge about synthetic ETFs and their relationships with the markets. Spillover and asymmetric-volatility effects are tested for ETFs, their respective benchmark indices, and general markets indices. The results do not reveal clear evidence that Synthetic ETFs have an impact on the stock markets.


[1] Chen, J.H. and Diaz, J. F. 2012. Spillover and asymmetric-volatility effects of leveraged and inverse leveraged exchange traded funds. Journal of Business and Policy Research, 7(3):1-10.
[2] Chen, J.H. and Huang, C.Y. 2010. An analysis of the spillover effects of exchange-traded funds. Applied Economics, 42(9): 1155-1168. DOI:
[3] Chen, J.H., Diaz, J.F.T. and Chen, C.S. 2014. The seasonal and spillover effects of Real Estate Investment Trusts (REIT) Exchange-Traded Funds (ETFS). International Journal of Research in Finance and Marketing, 4(9): 1-13.
[4] Chen, J. and Malinda, M. 2014. The Study of the Spillover and Leverage Effects of Financial Exchange Traded Funds (ETFs), Frontiers in Finance and Economics, Forthcoming, 11 (2): 41-59.
[5] Chu, P.K.K. 2011. Study on the tracking errors and their determinants: evidence from Hong Kong exchange traded funds, Applied Financial Economics, 21(5): 309-315. DOI:
[6] Elia, M. 2012. Tracking Error of Traditional and Synthetic European Exchange-Traded Funds. DOI:
[7] Gutierrez, J.A., Martinez, V. Tse, Y. 2009. Where does return and volatility come from? The case of Asian ETFs, International Review of Economics & Finance, 18(4): 671-679. DOI:
[8] Hu, J.W.S. and Koshoev, A. 2017. Specifics of Investor Sentiments: Analysis of Chinese Market. International Journal of Research In Commerce & Management, 8(3).
[9] Mateus, C. and Rahmani, Y. 2014. Physical Versus Synthetic Exchange Traded Funds. Which One Replicates Better? DOI:
[10] Maurer, F. and Williams, S.O. 2014. Physically Versus Synthetically Replicated Trackers: Is There a Difference in Terms of Risk? Journal of Applied Business Research, 31(1): 131-146. DOI:
[11] Meinhardt, C., Mueller, S. and Schoene, S. 2015. Physical and Synthetic Exchange Traded Funds: The Good, the Bad or the Ugly? The Journal of Investing, 24 (2): 35-44, DOI:
[12] Naumenko, K., Chystiakova, O. 2015. An Empirical Study on the Differences between Synthetic and Physical ETFs. International Journal of Economics and Finance, 7(3): 24-34. Available at: https://pdfs.semantic DOI:
[13] Rompotis, G.G. 2009. Performance and trading characteristics of iShares: An evaluation. IUP Journal of Applied Finance, 15(7): 24-34.
How to Cite
KOSHOEV, Askar. Synthetic versus Physical Exchange Traded Funds. Spillover and Asymmetric -Volatility Effects. Journal of Advanced Studies in Finance, [S.l.], v. 9, n. 1, p. 15-23, oct. 2018. ISSN 2068-8393. Available at: <>. Date accessed: 20 jan. 2019. doi:
Journal of Advanced Studies in Finance