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Designing volatility indices for Austria, Finland and Spain

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Abstract

The volatility index of the Chicago Board Options Exchange (VIX) was the first to be established, and it has given rise to international imitations worldwide as it is considered to be a barometer of investor fear. Starting from this volatility index, the aim of this paper is threefold. By adopting the VIX methodology, we construct a volatility index for three European countries (Austria, Finland and Spain) which currently do not provide this kind of market information for investors. Second, we investigate the properties of various volatility indices. In particular, we test their ability to act as fear indicators and as predictors of future returns. Moreover, we seek to cast light on the term structure of the proposed volatility indices, by computing spot and forward implied volatility indices for different times to maturity (30, 60 and 90 days). Our results indicate that volatility indices are useful not only for investors to improve their trading decisions, but also for policy-makers to choose the appropriate economic measures to promote stability in the market.

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Data Availability Statement

Data are obtained from the IvyDB Europe database, provided by the University of Modena and Reggio Emilia.

Notes

  1. Historical daily values for VBEL and VFTSE date back to January 2000. However, both indices have been discontinued, in particular in November 2010 and June 2019, respectively (see Fassas and Siriopoulos 2020). The VFTSE was delisted in June 2019 and replaced by the IVUK30.

  2. Gonzalez-Perez and Novales (2011) proposed a model-free version of the Spanish volatility index, the VIBEX-NEW. We build on their methodology by using an interpolation and extrapolation method to cope with truncation and discretization errors.

  3. It is important to point out an additional significant type of error that may affect the results. In particular, Andersen et al. (2015) argue that by averaging an invariant portion of the stock index risk-neutral density, a further approximation error appears as a result of a lack of a coherent time-invariant criterion to select minimum and maximum strikes in the VIX formula. As we extend the domain of strike prices by using a factor u such that \(S/(1+u)\le K\le S(1+u)\), where S is the index value and K is the strike price, we expect the error to be negligible for the current implementation.

  4. The volatility indices for Austria and Finland are computed with options on stock indices while the volatility index for Spain is computed with options on IBEX-35 futures. In particular, for the volatility index for Spain we used the Black (1976) formula to compute implied volatilities and did not apply dividend correction (Table 1).

  5. The variance inflation factor for regressor j is defined as \(\frac{1}{1-R^{2}_{j}}\) where \(R_{j}^{2}\) is the coefficient of multiple correlation between regressor j and the other regressor. As stated in the literature, a value greater than 10 indicates the presence of multicollinearity (see Neter et al. 1990; Cottrell and Lucchetti 2020).

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Acknowledgements

The authors gratefully acknowledge financial support from University of Modena and Reggio Emilia for the FAR2017 and FAR2019 projects. We also wish to extend our thanks to William Bromwich for his painstaking attention to the copy-editing of this paper. The authors thank the Editor and the anonymous reviewers for their helpful and valuable comments.

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Correspondence to Giovanni Campisi.

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Campisi, G., Muzzioli, S. Designing volatility indices for Austria, Finland and Spain. Financ Mark Portf Manag 35, 369–455 (2021). https://doi.org/10.1007/s11408-021-00381-9

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