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Infinite-Variance Error Structure in Finance and Economics

Author

Listed:
  • Fatma Ozgu Serttas

    (Assistant Professor of Economics, Ankara Yýldýrým Beyazýt University, Ankara, Turkey.)

Abstract

Many macroeconomic and financial data exhibit large outliers and high volatility so that their returns are usually modeled to follow an infinite-variance stable process. Extreme behaviors in such data tend to exist especially for emerging markets due to frequent existence of high economic turmoil. A relatively new area of research studies that model the financial returns as infinite-variance stable errors exists for emerging markets as well as for industrialized countries. This study aims to briefly introduce the reader the concept of infinite-variance stable distributions, discuss some existing studies on unit root and cointegration tests that assume infinite-variance stable error structure, and then to point out the potential lines of research while showing the significance of this relatively new concept.

Suggested Citation

  • Fatma Ozgu Serttas, 2018. "Infinite-Variance Error Structure in Finance and Economics," International Econometric Review (IER), Econometric Research Association, vol. 10(1), pages 14-23, April.
    • Handle: RePEc:erh:journl:v:10:y:2018:i:1:p:14-23
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    References listed on IDEAS

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    More about this item

    Keywords

    Infinite-Variance Errors; Stable Distributions; Financial Returns; Unit Root Tests; Co-Integration Tests.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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