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Portfolio analysis of intraday covariance matrix in the Greek equity market

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Listed author(s):
  • 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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File URL: http://www.sciencedirect.com/science/article/pii/S0275531912000360
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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
DOI: 10.1016/j.ribaf.2012.06.003
Contact details of provider: Web page: http://www.elsevier.com/locate/ribaf

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

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  1. repec:hal:journl:peer-00815564 is not listed on IDEAS
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  10. 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.
  11. N. A. Niarchos & C. A. Alexakis, 2003. "Intraday stock price patterns in the Greek stock exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 13(1), pages 13-22.
  12. Panayiotis Diamandis & Anastassios Drakos & Argyrios Volis, 2007. "The impact of stock incremental information on the volatility of the Athens stock exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 413-424.
  13. 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.
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Cited by:

  1. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
  2. Sharma, Prateek & Vipul,, 2015. "Performance of risk-based portfolios under different market conditions: Evidence from India," Research in International Business and Finance, Elsevier, vol. 34(C), pages 397-411.
  3. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.

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