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Short-term Dynamics in the Cyprus Stock Exchange

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  • Gregory Koutmos
  • Andreas Pericli
  • Lenos Trigeorgis

Abstract

This paper investigates the short-term dynamics of stock returns in an emerging stock market namely, the Cyprus Stock Exchange (CYSE). Stock returns are modelled as conditionally heteroscedastic processes with time-dependent serial correlation. The conditional variance follows an EGARCH process, while for the conditional mean three nonlinear specifications are tested, namely: (a) the LeBaron exponential autoregressive model; (b) the Sentana and Wadhwani positive feedback trading model; and finally (c) a model that nests both (a) and (b). There is an inverse relationship between volatility and autocorrelation consistent with the findings from several other stock markets, including the US. This pattern could be the manifestation of a certain form of noise trading namely positive feedback trading or, momentum trading strategies. There is little evidence that market declines are followed with higher volatility than market advances, the so-called 'leverage effect', that has been observed in almost all developed stock markets. In out of sample forecasts, the nonlinear specifications provide better results in terms of forecasting both first and second moments of the distribution of returns.

Suggested Citation

  • Gregory Koutmos & Andreas Pericli & Lenos Trigeorgis, 2006. "Short-term Dynamics in the Cyprus Stock Exchange," The European Journal of Finance, Taylor & Francis Journals, vol. 12(3), pages 205-216.
    • Handle: RePEc:taf:eurjfi:v:12:y:2006:i:3:p:205-216
    DOI: 10.1080/13518470500146074
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    1. Angelidis, Dimitrios & Koulakiotis Athanasios & Kiohos Apostolos, 2018. "Feedback Trading Strategies: The Case of Greece and Cyprus," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 93-99, June.
    2. Kallinterakis, Vasileios & Liu, Fei & Pantelous, Athanasios A. & Shao, Jia, 2020. "Pricing inefficiencies and feedback trading: Evidence from country ETFs," International Review of Financial Analysis, Elsevier, vol. 70(C).
    3. Hou, Yang & Li, Steven, 2014. "The impact of the CSI 300 stock index futures: Positive feedback trading and autocorrelation of stock returns," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 319-337.
    4. Saint Kuttu & Godfred A. Bokpin, 2017. "Feedback Trading and Autocorrelation Patterns in Sub-Saharan African Equity Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(1), pages 213-225, January.
    5. Fotini Economou & Konstantinos Gavriilidis & Bartosz Gebka & Vasileios Kallinterakis, 2022. "Feedback trading: a review of theory and empirical evidence," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 15(4), pages 429-476, February.
    6. Piotr Wdowinski & Marta Malecka, 2010. "Asymmetry in Volatility: A Comparison of Developed and Transition Stock Markets," CESifo Working Paper Series 2974, CESifo.
    7. Shaen Corbet & Yang Hou & Yang Hu & Les Oxley, 2024. "Time varying risk aversion and its connectedness: evidence from cryptocurrencies," Annals of Operations Research, Springer, vol. 338(2), pages 879-923, July.
    8. Kutan, Ali M. & Shi, Yukun & Wei, Mingzhe & Zhao, Yang, 2018. "Does the introduction of index futures stabilize stock markets? Further evidence from emerging markets," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 183-197.
    9. Andrikopoulos, Panagiotis & Cui, Yueting & Gad, Samar & Kallinterakis, Vasileios, 2020. "Feedback trading and the ramadan effect in frontier markets," Research in International Business and Finance, Elsevier, vol. 51(C).

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