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Portfolio analysis of intraday covariance matrix in the Greek equity market

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  • Vortelinos, Dimitrios I.

Abstract

The intraday nonparametric estimation of the variance–covariance matrix adds to the literature in portfolio analysis of the Greek equity market. This paper examines the economic value of various realized volatility and covariance estimators under the strategy of volatility timing. I use three types of portfolios: Global Minimum Variance, Capital Market Line and Capital Market Line with only positive weights. The estimators of volatilities and covariances use 5-min high-frequency intraday data. The dataset concerns the FTSE/ATHEX Large Cap index, FTSE/ATHEX Mid Cap index, and the FTSE/ATHEX Small Cap index of the Greek equity market (Athens Stock Exchange). As far as I know, this is the first work of its kind for the Greek equity market. Results concern not only the comparison of various estimators but also the comparison of different types of portfolios, in the strategy of volatility timing. The economic value of the contemporary non-parametric realized volatility estimators is more significant than this when the covariance is estimated by the daily squared returns. Moreover, the economic value (in b.p.s) of each estimator changes with the volatility timing.

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Bibliographic Info

Article provided by Elsevier in its journal Research in International Business and Finance.

Volume (Year): 27 (2013)
Issue (Month): 1 ()
Pages: 66-79

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Handle: RePEc:eee:riibaf:v:27:y:2013:i:1:p:66-79

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Web page: http://www.elsevier.com/locate/ribaf

Related research

Keywords: Portfolio analysis; Covariance; Volatility timing; Realized volatility; Greece;

References

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  1. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, 08.
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  8. Kitamura, Yoshihiro, 2010. "Testing for intraday interdependence and volatility spillover among the euro, the pound and the Swiss franc markets," Research in International Business and Finance, Elsevier, vol. 24(2), pages 158-171, June.
  9. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.
  10. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
  11. Kyrtsou, C. & Terraza, V., 2000. "Volatility Behaviour in Emerging Markets: A Case Study of the Athens Stock Exchange, Using Daily and Intra-Daily Data," European Research Studies Journal, European Research Studies Journal, vol. 0(3-4), pages 3-16, July - De.
  12. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
  13. F. M. Bandi & J. R. Russell, 2008. "Microstructure Noise, Realized Variance, and Optimal Sampling," Review of Economic Studies, Oxford University Press, vol. 75(2), pages 339-369.
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