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The relation between implied and realised volatility in the Danish option and equity markets

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  • Charlotte Strunk Hansen

Abstract

We show that the conclusions to be drawn concerning the informational efficiency of illiquid options markets depend critically on whether one carefully recognises and appropriately deals with the econometrics of the errors‐in‐variables problem. This paper examines the information content of options on the Danish KFX share index. We consider the relation between the volatility implied in an option’s price and the subsequently realised index return volatility. Since these options are traded infrequently and in low volumes, the errors‐in‐variables problem is potentially large. We address the problem directly using instrumental variables techniques. We find that when measurement errors are controlled for, call option prices even in this very illiquid market contain information about future realised volatility over and above the information contained in historical volatility.

Suggested Citation

  • Charlotte Strunk Hansen, 2001. "The relation between implied and realised volatility in the Danish option and equity markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 41(3), pages 197-228, November.
    • Handle: RePEc:bla:acctfi:v:41:y:2001:i:3:p:197-228
    DOI: 10.1111/1467-629X.00059
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    Cited by:

    1. Puja Padhi & Imlak Shaikh, 2014. "On the relationship of implied, realized and historical volatility: evidence from NSE equity index options," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(5), pages 915-934, November.
    2. Steven Li & Qianqian Yang, 2009. "The relationship between implied and realized volatility: evidence from the Australian stock index option market," Review of Quantitative Finance and Accounting, Springer, vol. 32(4), pages 405-419, May.
    3. Yu, Wayne W. & Lui, Evans C.K. & Wang, Jacqueline W., 2010. "The predictive power of the implied volatility of options traded OTC and on exchanges," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 1-11, January.
    4. Asgharian, Hossein & Sikström, Sverker, 2013. "Predicting Stock Price Volatility by Analyzing Semantic Content in Media," Knut Wicksell Working Paper Series 2013/16, Lund University, Knut Wicksell Centre for Financial Studies.
    5. Peter Carr & Liuren Wu, 2004. "Variance Risk Premia," Finance 0409015, University Library of Munich, Germany.
    6. Imlak Shaikh & Puja Padhi, 2013. "On the Linkages among Ex-ante and Ex-post Volatility: Evidence from NSE Options Market (India)," Global Business Review, International Management Institute, vol. 14(3), pages 487-505, September.
    7. Yanhui Chen & Kin Lai, 2013. "Examination on the Relationship Between VHSI, HSI and Future Realized Volatility With Kalman Filter," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(2), pages 200-216, December.
    8. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.
    9. Tanuj Nandan & Puja Agrawal, 2016. "Pricing Efficiency in CNX Nifty Index Options Using the Black–Scholes Model: A Comparative Study of Alternate Volatility Measures," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 10(2), pages 281-304, May.
    10. Yanhui Chen & Kin Keung Lai, 2013. "Examination on the Relationship Between VHSI, HSI and Future Realized Volatility With Kalman Filter," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(2), pages 200-216, December.
    11. Imlak Shaikh & Puja Padhi, 2015. "On the Relationship of Ex-ante and Ex-post Volatility: A Sub-period Analysis of S&P CNX Nifty Index Options," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 14(2), pages 140-175, August.

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