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Relation Between Expected Return And Volatility At Bucharest Stock Exchange, On Business Cycle Stages

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  • Viorica Chirilă
  • Ciprian Chirilă

Abstract

The study of the relation between risk and return is an important topic for investors in financial assets, which is the reason why many researchers have tackled it. It is only natural for an investor with aversion for risk, who undertakes a higher risk investment, mare to expect be rewarded accordingly, that is to achieve higher return rates. The research conducted on various stock markets had contradictory results, which means that the existence of such a connection is not certain on all stock markets. According to a new hypothesis, tackled by the latest studies, the aversion for risk of rational investors may be related to the stages of the business cycles. This paper deals with the connection between expected return and volatility at Bucharest Stock Exchange, by analyzing the return and volatility of the BET index portfolio. In order to assess this relation, we employed heteroskedastic autoregressive models. The study was conducted between January 2000 and April 2011, as well as during two sub-periods determined by different business cycle phases: economic growth and recession. The results revealed significant differences between the whole analyzed period and the economic growth and recession sub-periods. By studying BSE return throughout the analyzed period, we conclude that there is no relationship between expected return and risk, whereas volatility is asymmetric. Actually, one may witness a relation between return and risk, as well as a non-asymmetric response of volatility to shocks during economic growth, and no risk-return relationship and asymmetric volatility during economic recession. Also, results have shown a positive relationship between return and volatility during economic growth, and a negative relationship between the same during economic recession.

Suggested Citation

  • Viorica Chirilă & Ciprian Chirilă, 2012. "Relation Between Expected Return And Volatility At Bucharest Stock Exchange, On Business Cycle Stages," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(14), pages 1-13.
  • Handle: RePEc:alu:journl:v:1:y:2012:i:14:p:13
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    References listed on IDEAS

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    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
    4. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    5. Harding, Don & Pagan, Adrian, 2001. "Extracting, Using and Analysing Cyclical Information," MPRA Paper 15, University Library of Munich, Germany.
    6. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    9. Sei‐Wan Kim & Bong‐Soo Lee, 2008. "Stock Returns, Asymmetric Volatility, Risk Aversion, And Business Cycle: Some New Evidence," Economic Inquiry, Western Economic Association International, vol. 46(2), pages 131-148, April.
    10. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    11. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    business cycle; return; volatility; return-volatility relation;
    All these keywords.

    JEL classification:

    • G - Financial Economics
    • C - Mathematical and Quantitative Methods

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