BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Author
Patev Plamen, Kanaryan Nigokhos, Lyroudi Katerina
Title
Modelling and Forecasting the Volatility of Thin Emerging Stock Markets : the Case of Bulgaria
Modelowanie i prognozowanie zmienności na wschodzących rynkach giełdowych : przypadek Bułgarii
Source
Comparative Economic Research, 2009, vol. 12, nr 4, s. 47-60, rys., tab., bibliogr. 19 poz.
Keyword
Analiza ryzyka, Indeks giełdowy, Szacowanie ryzyka, Giełda papierów wartościowych, Wskaźniki giełdowe
Risk analysis, Stock market indexes, Risk estimating, Stock market, Stock market indices
Note
summ., streszcz.
Country
Bułgaria
Bulgaria
Abstract
Przedmiotem artykułu jest modelowanie i prognozowanie wskaźników giełdowych. Szczególna uwaga poświęcona jest analizie ryzyka na bułgarskiej giełdzie papierów wartościowych. Celem tej analizy jest opracowanie wiarygodnego modelu oceny i prognozowania ryzyka na bułgarskiej giełdzie papierów wartościowych. Przeprowadzone analizy wskazują, że indeks giełdowy SOFIX charakteryzuje się typowymi cechami: wysokim ryzykiem autokorelacji i nienormalnym rozczłonkowaniem. W celu oszacowania i oceny ryzyka giełdy w Bułgarii wykorzystano trzy modele: RiskMetrics, EWMA oraz zmodyfikowany model EWMA. Z analiz wynika, że dwa ostatnie modele dosyć dokładnie szacują ryzyko na bułgarskiej giełdzie papierów wartościowych. (abstrakt oryginalny)

Modern Portfolio Theory associates the stock market risk with the volatility of return. Volatility is measured by the variance of the returns' distribution. However, the investment community does not accept this measure, since it weights equally deviations of the average returns, whereas most investors determine the risk on the basis of small or negative returns. In the last few years the measure Value at Risk (VaR) has been established and adopted widely by practitioners. The issue of modelling and forecasting thin emerging stock markets' risk is still open. The subject of this present paper is the risk of the Bulgarian stock market. The aim of this research is to give the investment community a model for assessing and forecasting the Bulgarian stock market risk. The result of this research shows that the SOFIX index has basic characteristics that are observed in most of the emerging stock markets, namely: high risk, significant autocorrelation, non-normality and volatility clustering. Three models have been applied to assess and estimate the Bulgarian stock market risk: RiskMetrics, EWMA with t-distributed innovations and EWMA with GED distributed innovations. The results revealed that the EWMA with t-distributed innovations and the EWMA with GED distributed innovations evaluate the risk of the Bulgarian stock market adequately. (original abstract)
Accessibility
The Library of University of Economics in Katowice
The Main Library of the Wroclaw University of Economics
Full text
Show
Bibliography
Show
  1. Aggarwal, R., C. Inclan and, R. Leal, (1999), Volatility in Emerging Stock Markets, Journal of Financial and Quantitative Analysis, 34, pp. 33-55
  2. Bank for International Settlements, 1996, Amendment to the Capital Accord to Incorporate Market Risk", Basel, Switzerland
  3. Balaban, E., A. Bayar, and, R. Faff, (2003), Forecasting Stock Market Volatility: Evidence from 14 Countries, 10th Global Finance Conference 2003, Frankfurt/Main, June 15-17, 2003
  4. Bams, D. and, J. L. Wielhouwer, (2001), Empirical Issues in Value-at-Risk, Canadian Economic Association, 35-th Annual Conference, May-31 June 3, 2001
  5. Bekaert, G. C. B. Erb, C. R. Harvey, and, T. E. Viskanta, (1998), Distributional characteristics of emerging market returns and asset allocation, Journal of Portfolio Management, Winter, pp. 102-116
  6. Bollerslev, T., (1986), Generalized Autoregressive Conditional Heteroskedastisity, Journal of Econometrics, 31, pp. 307-327
  7. Deloitte and Touche, Tohmatsu, (2002), Global Risk Management Survey
  8. Dimson, E. and, P. Marsh, (1990), Volatility forecasting without data-snooping, Journal of Banking and Finance, 14, pp. 399-421
  9. Glimore, C. G. and McManus, G. M., (2001), Random-Walk and Efficiency of Central European Equity Markets, Presentation at the 2001 European Financial Management Association, Annual Conference, June 2001 in Lugano, Switzerland
  10. Guermat, C. and, R. D. F. Harris, (2002), Forecasting value at risk allowing for time variation in the variance and kurtosis of portfolio returns, International Journal of Forecasting, 18, pp. 409-419
  11. Harvey, C. R., (1995a), The Risk Exposure of Emerging Equity Markets, World Bank Economic Review, 9, pp. 18-50
  12. Harvey, C. R., (1995b), Predictable Risk and Returns in Emerging Markets, Review of Financial Studies, 8, pp. 773-81
  13. Jorion, P., (1997), VaR: The New Benchmark for Controlling Market Risk, R. Irwin Co.
  14. Kasch-Haroutounian, M. and Price, S., (2001), Volatility in transition market of Central Europe, Applied Financial Economics, 11, pp. 93-105
  15. Kupiec, P., (1995), Techniques for Verifying the Accuracy of Risk Measurement Models, Journal of Derivatives, 3, pp. 73-84
  16. Morgan, JP, (1996), RiskMetrics Technical Document, 4th ed., New York
  17. Murinde, V. and Poshakwale, S., (2002), Volatility in the Emerging Stock Markets in Central and Eastern Europe: Evidence on Croatia, Czech Republic, Hungary, Poland, Russia and Slovakia, Forthcoming in European Research Studies Journal, 4, pp. 73-101
  18. Nelson, D., (1995), Conditional Heteroskedasticity in Asset Returns: A New Approach. in R. Engle (ed.), ARCH: Selected Readings, Oxford University Press
  19. Poshakwale, S. and Murinde, V., (2001), Modelling the Volatility in East European Emerging Stock Markets: Evidence on Hungary and Poland, Applied Financial Economics, 11, pp. 445-456
Cited by
Show
ISSN
1508-2008
Language
eng
URI / DOI
https://doi.org/10.2478/v10103-009-0021-8
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu