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Estimating Probability of Informed Trading on the Bucharest Stock Exchange

Author

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  • Cosmin Octavian Cepoi

    (Bucharest Academy of Economic Studies)

  • Filip Mihai Toma

    (Bucharest Academy of Economic Studies)

Abstract

Informed trading is a major concern within the domain of financial markets microstructure, as it represents a proxy for the efficient functioning of a market during a specific timeframe. The implications of whether information asymmetries occur on financial markets are important. From a trading perspective, excess information events can lead to efficiency biases and can also be associated with spikes in intraday volatility, as well as sharp modifications of intraday liquidity. The probability of informed trading (PIN) metric can provide a viable mean for noise traders in understanding rapid fluctuations in microstructure indicators, such as those indicated above. Even though PIN estimation has been covered in the academic literature from a microstructure vantage point, to our knowledge there are no studies assessing the relationship between macroeconomic variables and the PIN. We find that the exchange rate, the interest rate and the oil price are better suited than microstructure indicators to explain the PIN on the Bucharest Stock Exchange. The current study brings insight into the dynamics of certain macroeconomic indicators and informational asymmetries on the Bucharest Stock Exchange. Furthermore, estimating the PIN on this stock market has not yet been tackled in the current literature.

Suggested Citation

  • Cosmin Octavian Cepoi & Filip Mihai Toma, 2016. "Estimating Probability of Informed Trading on the Bucharest Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(2), pages 140-160, April.
  • Handle: RePEc:fau:fauart:v:66:y:2016:i:3:p:140-160
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    References listed on IDEAS

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    More about this item

    Keywords

    probability of informed trading; market microstructure; liquidity; volatility; macroeconomic variables; information asymmetry;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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