Grzegorz Perczak , Piotr Fiszeder
ARTICLE

(Polish) PDF

ABSTRACT

This paper examines the problem of calculating the variance of returns of a financial instrument which is based upon the historical opening, closing, high, and low prices. For this purpose the joint distribution of minimum, maximum and final values of arithmetic Brownian motion was used. It gave a possibility to make a comparative analysis of the variance estimators. The formulae of expected values of many random variables, which were used for the construction of these estimators were calculated. Moreover, on the basis of those formulae, the new estimator of variance was proposed. The assumptions that were adopted for the construction of the estimator were examined. The efficiency of the proposed estimator was compared with the efficiency of the well-known estimators of daily volatility.

KEYWORDS

volatility estimator, open price, low price, high price, close price, Brownian motion

REFERENCES

[1] Andersen T. G., Bollerslev T., Diebold F. X., Labys P., (2000), Great Realizations, Risk, March, 105–108.

[2] Bollerslev T., Chou R. Y., Kroner K. F., (1992), ARCH Modelling in Finance: A Review of the Theory and Empirical Evidence, Journal of Econometrics, 52, 5–59.

[3] Bollerslev T., Engle R. F., Nelson D. B., (1994), ARCH Models, w: Engle R. F., McFadden D., (red.), Handbook of Econometrics, 4, Elsevier Science B. V., Amsterdam.

[4] Cox D. R., Miller M. D., (1965), The Theory of Stochastic Processes., Methuen and Co., London.

[5] Doman M., (2011), Mikrostruktura giełd papierów wartościowych, Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu, Poznań.

[6] Doman M., Doman R., (2009), Modelowanie zmienności i ryzyka. Metody ekonometrii finansowej, Wolters Kluwer Polska, Kraków.

[7] Fiszeder P., (2009), Modele klasy GARCH w empirycznych badaniach finansowych, Wydawnictwo UMK, Toruń.

[8] Garman M. B., Klass M. J., (1980), On the Estimation of Security Price Volatilities from Historical Data, The Journal of Business, 53 (1), 67–78.

[9] Harrisson J. M., (1985), Brownian Motion and Stochastic Flow Systems, John Wiley & Sons, New York.

[10] Jakubowski J., Palczewski A., Rutkowski M., Stettner Ł. (2006), Matematyka finansowa, instrumenty pochodne, WNT, Warszawa.

[11] Kunitomo N., Ikeda M., (1992), Pricing Options with Curved Boundaries, Mathematical Finance, 2 (4), 275–298.

[12] Kunitomo N. (1992), Improving the Parkinson Method of Estimating Security Price Volatilities, Journal of Business, 65, 295–302.

[13] Li A., (1999), The Pricing of Double Barrier Options and Their Variations, Advances in Futures and Options Research, 10, 17–41.

[14] Osiewalski J., Pipień M., (2004), Bayesian Comparison of Bivariate ARCH-Type Models for the Main Exchange Rates in Poland, Journal of Econometrics, 123, 371–391.

[15] Oomen R., (2001), Using High Frequency Stock Market Index Data to calculate, Model, European University Institute, Discussion Paper No. 2001/6.

[16] Pajor A., (2010), Wielowymiarowe procesy wariancji stochastycznej w ekonometrii finansowej. Ujęcie bayesowskie, Zeszyty Naukowe, Seria Specjalna: Monografi e 195, Wydawnictwo Uniwersytetu Ekonomicznego w Krakowie.

[17] Parkinson M., (1980), The Extreme Value Method for Estimating the Variance of the Rate of Return, The Journal of Business, 53 (1), 61-65.

[18] Perczak G., (2013), Dodatkowe informacje o cenach minimalnych i maksymalnych w modelach klasy GARCH, rozprawa doktorska przygotowywana pod kierunkiem P. Fiszedera.

[19] Rogers L. C. G., Satchell S. E., (1991) Estimating Variance From High, Low and Closing Prices, The Annals of Applied Probability, 1 (4), 504–512.

[20] Yang D., Zhang Q., (2000), Drift-Independent Volatility Estimation Based on High, Low, Open, and Closing Prices, Journal of Business, 73, 477–491.

Back to top
© 2019–2022 Copyright by Statistics Poland, some rights reserved. Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) Creative Commons — Attribution-ShareAlike 4.0 International — CC BY-SA 4.0