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A Continuing Approach, From Financial Economics To Financial Econometrics Or The Econometric Thinking Applied To Financial Economics

Author

Listed:
  • Gheorghe SAVOIU

    (University of Pitesti)

  • Constantin MANEA

    (University of Pitesti)

Abstract

The main aim of this paper is to attempt a theoretical delineation of a new econoscience now known as financial econometrics, which is as a result of a dual approach, one originally from economics to econometrics, followed by another one, articulate, from financial economics to financial econometrics, both purely theoretical, simultaneously stressing the importance of economic and financial modelling, historically detailing the emergence and development of this new econoscience, outlining its subject and objectives, and describing some of the most commonly used methods and models, while noting the presence of increasingly sharp competition of econophysics, sociophysics and economy quantum, in the universe of modelling the processes and phenomena in classical economics and financial economics.

Suggested Citation

  • Gheorghe SAVOIU & Constantin MANEA, 2013. "A Continuing Approach, From Financial Economics To Financial Econometrics Or The Econometric Thinking Applied To Financial Economics," Romanian Statistical Review, Romanian Statistical Review, vol. 61(3), pages 66-76, April.
    • Handle: RePEc:rsr:journl:v:61:y:2013:i:3:p:66-76
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    References listed on IDEAS

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    1. Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
    2. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
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