Abstract
The name econometrics is derived from the ancient Greek word combination: oikonomia = economy and metron = measure, measurement. Econometrics can, therefore, be described as the measurement of economic activity. Formally, econometrics is a social science that uses economic theory and mathematical methods as well as statistical data to quantitatively analyze economic processes and phenomena and empirically test economic theories. In the competition among different economic theoretical hypotheses, econometrics confronts these hypotheses with the reality provided by the data, so that the usefulness of an economic theoretical statement becomes tangible only if it can describe more or less the reality. An accurate description of the reality by an econometric model requires an accurate measurement of the relevant variables and their relationships.
The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Zellner, A. (1996). Past, present and future of econometrics, Journal of Statistical Planning and Inference, 49, pp. 3–8.
- 2.
Krämer, W. (2011). Statistik verstehen—Eine Gebrauchsanweisung. München: Piper Verlag.
- 3.
Krämer W. (2012). Angst der Woche—Warum wir uns vor den falschen Dingen fürchten. Munich: Piper Verlag.
- 4.
Johnstone, D. J. (1986). Tests of significance in theory and practice. The Statistician, 35(5), pp. 491–504.
- 5.
Wasserstein, R. L. & Lazar, N. A. (2016). The ASA’s statement on p-values: context, process, and purpose, The American Statistician, 70 (2), pp. 129–133.
- 6.
Ester, M. & Sander, J. (2000). Knowledge discovery in databases. Techniken und Anwendungen. Berlin: Springer.
- 7.
Feelders, A. (2002). Data mining in economic science. In J. Meij (Ed.), Dealing with the data flood: Mining data, text and multimedia (pp. 165–175). The Hague: STT/Beweton.
- 8.
Basel Committee on Banking Supervision (1996). Supervisory framework for the use of ‘backtesting’ in conjuction with the internal models approach to market risk capital requirements Retrieved from http://www.bis.org/publ/bcbs22.pdf.
- 9.
Jorion, P. (2007). Value at risk. New York: McGraw-Hill.
- 10.
Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation. Econometrica, 50, pp. 987–1008.
- 11.
Fama, E. F. (1963). Mandelbrot and the stable paretian hypothesis. The Journal of Business, 36 (4), pp. 420–429.
- 12.
Note that VaR is a loss measure and thus its values have negative signs.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 Springer Fachmedien Wiesbaden GmbH, part of Springer Nature
About this chapter
Cite this chapter
Halbleib, R. (2023). Measuring and Understanding Financial Risks: An Econometric Perspective. In: Schweiker, M., Hass, J., Novokhatko, A., Halbleib, R. (eds) Measurement and Understanding in Science and Humanities. Palgrave Macmillan, Wiesbaden. https://doi.org/10.1007/978-3-658-36974-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-658-36974-3_10
Published:
Publisher Name: Palgrave Macmillan, Wiesbaden
Print ISBN: 978-3-658-36973-6
Online ISBN: 978-3-658-36974-3
eBook Packages: Religion and PhilosophyPhilosophy and Religion (R0)