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Volatility risk premia and financial connectedness

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  • Andrea Cipollini
  • Iolanda Lo Cascio
  • Silvia Muzzioli

Abstract

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. Therefore, we estimate and invert a Fractionally Integrated VAR model to compute the cross forecast error variance shares necessary to obtain the index of total connectedness and the net contribution of each series to total connectedness. The results show that, over January 2000-August 2013, the index of total connectedness among volatility risk premia has been relatively stable with an increasing role played by France and with a positive (but decreasing) role played by Germany and the Netherlands. Non EMU countries such as the UK and Switzerland are negative net contributors to the index.

Suggested Citation

  • Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Center for Economic Research (RECent) 109, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  • Handle: RePEc:mod:recent:109
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    1. Jonathan E. Ogbuabor & God’stime O. Eigbiremolen & Gladys C. Aneke & Manasseh O. Charles, 2018. "Measuring the dynamics of APEC output connectedness," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 32(1), pages 29-44, May.

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    More about this item

    Keywords

    volatility risk premium; long memory; FIVAR; financial connectedness;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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