An Empirical Study of Nifty 50 Option Time Spreads

Authors

  •   Ronald T. Slivka Adjunct Professor (Corresponding Author), New York University – Tandon School of Engineering, Department of Finance and Risk Engineering, 1 Metrotech Center, 10th Fl. Brooklyn, NY 11201
  •   Yuxing Liang NYU MSc Graduate – Financial Engineering, New York University – Tandon School of Engineering, Department of Finance and Risk Engineering, 1 Metrotech Center, 10th Fl. Brooklyn, NY 11201
  •   Jieqi Xue NYU MSc Graduate – Financial Engineering, New York University – Tandon School of Engineering, Department of Finance and Risk Engineering, 1 Metrotech Center, 10th Fl. Brooklyn, NY 11201

DOI:

https://doi.org/10.17010/ijf/2020/v14i8-9/154944

Keywords:

SSE50 options

, Nifty 50 options, time spreads, calendar spreads, horizontal spreads

JEL Classification

, G10, G11, G13, G14, G15

Paper Submission Date

, December 30, 2019, Paper sent back for Revision, June 15, 2020, Paper Acceptance Date, June 30, 2020

Abstract

The objective of this study was to identify and test preliminary rules for trading call option time spreads and then to assess opportunities for further research to improve on those rules. To do so, the theoretical and empirical properties of near-the-money time spreads were used to develop four rules for profitably trading in India’s Nifty 50 (NSE 50) call options. Day-end pricing for 2015 – 2019 included periods of rising, falling, and stable volatility. The resulting four rule algorithm produced positive results on out-of-sample data and outperformed a buy and hold strategy. As the general procedure followed for rule development was not country specific, it was applied to options on China’s SSE 50 index, where the algorithm was found to outperform a hold-to-expiry strategy in every year tested. These related studies of NSE 50 and SSE 50 option time spreads provide a helpful addition to the growing knowledge about the developing derivatives markets in India and China. Opportunities for further research are described.

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Published

2020-09-01

How to Cite

Slivka, R. T., Liang, Y., & Xue, J. (2020). An Empirical Study of Nifty 50 Option Time Spreads. Indian Journal of Finance, 14(8-9), 8–19. https://doi.org/10.17010/ijf/2020/v14i8-9/154944

References

Cretien, P. D. (2012, January). Eurodollar options: Interest rate forecasts and calendar spreads. Futures Magazine, pp. 28 – 29, 33. Retrieved from http://www.futuresmag.com

Cretien, P. D. (2013, April). Seize the day with forex calendar spreads. Futures Magazine, pp. 20 – 21, 27. Retrieved from http://www.futuresmag.com

Koshiyama, A. S., Firoozye, N., & Treleaven, P. (2019). A derivatives trading recommendation system : The mid-curve calendar spread case. Intelligent Systems in Accounting, Finance & Management, 26(2), 83 – 103. https://doi.org/10.1002/isaf.1445

Schneider, L., & Tavin, B. (2018). From the Samuelson volatility effect to a Samuelson correlation effect : An analysis of crude oil calendar spread options. Journal of Banking and Finance, 95, 185 – 202. http://dx.doi.org/10.1016/j.jbankfin.2016.12.001

Seok, J., Brorsen, B. W., & Niyibizi, B. (2018). Modeling calendar spread options. Agricultural Finance Review, 78(5), 551 – 570. https:// DOI 10.1108/AFR-09-2017-0088

Slivka, R. T., & Wang, R. (2019). Time spreads in China SSE 50 Options. Indian Journal of Research in Capital Markets, 6(4), 7 – 19. https://doi.org/10.17010/ijrcm/2019/v6/i4/150268