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The Comparative Risk And Performance Analysis Of Hungarian And Romanian Exchange Indices


  • Tarnaczi Tibor

    () (University of Debrecen, Faculty of Applied Economics and Rural Development, Debrecen, Hungary, University of Debrecen, Faculty of Applied Economics and Rural Development, Debrecen, Hungary)

  • Kulcsar Edina

    () (University of Oradea, Faculty of Economic Sciences, Oradea, Romania, University of Debrecen, Faculty of Applied Economics and Rural Development, Debrecen, Hungary)


Nowadays, the most dominant characteristics of the financial environment are instability, variability, riskiness and uncertainty. It is difficult to find a field where the decision making process is risk-free. This statement is especially true in case of financial investments according to which risk taking is rewarded. But it is also true that the financial market participants cannot be completely avoided risks, but there are many options for managing and minimizing them. One of the most well-known theories of financial instruments' risk minimization is the modern portfolio theory, which is the collection of tools and techniques by which a risk-averse investor may construct an optimal portfolio. In portfolio theory it is also known the possibility of risky assets diversification to obtain the optimal return/risk ratio. Consequently, this paper aims to examine the efficient portfolio alternatives by determination of performance ratios based on CAPM model and modern portfolio theory, such as Sharpe ratio, Jensenâ€(tm)s alpha and Treynor ratio and risk measuring methods, such as Value at Risk, or Expected Shortfall. In present research we concentrate to a comparative analysis of portfolios consist in main stock indices shares of two neighboring countries from Central and Eastern Europe: Hungary and Romania. The analysis was performed on the Romanian BET and Hungarian BUX stock market indices using the six-month daily closing prices. Data of the analysis were downloaded from the official websites of Romanian and Hungarian stock exchanges. The statistical analysis was made in R statistical system. Using such tools to uncover information and ask better questions will support the investors to make better and better investment decisions. The results of present research show a greater performance level for Romanian portfolio, but also a higher level of risk, with lower volatility toward market changes and major specific risk. For the Hungarian portfolio, the performance is more temperate, the level of risk is also smaller and the volatility to market factors is more relevant, so the specific risk is moderate in this case.

Suggested Citation

  • Tarnaczi Tibor & Kulcsar Edina, 2013. "The Comparative Risk And Performance Analysis Of Hungarian And Romanian Exchange Indices," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 451-462, December.
  • Handle: RePEc:ora:journl:v:1:y:2013:i:2:p:451-462

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    References listed on IDEAS

    1. Chen, Nan-Kuang, 2001. "Bank net worth, asset prices and economic activity," Journal of Monetary Economics, Elsevier, vol. 48(2), pages 415-436, October.
    2. Kiyotaki, Nobuhiro & Moore, John, 1997. "Credit Cycles," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 211-248, April.
    3. Michael B. Devereux & James Yetman, 2010. "Leverage Constraints and the International Transmission of Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(s1), pages 71-105, September.
    4. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
    5. Ross Levine & Norman Loayza & Thorsten Beck, 2002. "Financial Intermediation and Growth: Causality and Causes," Central Banking, Analysis, and Economic Policies Book Series,in: Leonardo Hernández & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.), Banking, Financial Integration, and International Crises, edition 1, volume 3, chapter 2, pages 031-084 Central Bank of Chile.
    6. Gertler, Mark & Kiyotaki, Nobuhiro, 2010. "Financial Intermediation and Credit Policy in Business Cycle Analysis," Handbook of Monetary Economics,in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 11, pages 547-599 Elsevier.
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    More about this item


    diversification; portfolio theory; risk; efficient portfolio; return; performance analysis;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G19 - Financial Economics - - General Financial Markets - - - Other


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