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Real-World Application with Our Robust Tools

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Robust Optimization of Spline Models and Complex Regulatory Networks

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

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Abstract

One of the fundamental concepts in finance theory is optimization, and the financial decision making for a rational agent is essentially a question of achieving an optimal trade-off between risk and return. In this way, robustification is starting to draw more attention in finance; in particular, some studies report promising results using robust statistical techniques in financial markets. In the study (A. Özmen, G.-W. Weber and A. Karimov, A new robust optimization tool applied on financial data, to appear in Pacific Journal of Optimization, 9(3), pp. 535–552, 2013), we used data from Istanbul Stock Exchange like ISE 100 index, ISE transaction number and so on, from Turkish economy like TUFE and TEFE indexes, and also data of the Fed Funds Interest Rate and VIX Index which have been obtained from the US market, because of their strong effect on the economy of Turkey. ISE 100 index has been taken as the dependent variable, and others as the independent variables. We put a correlation threshold in order to limit the unnecessary and meaningless calculations and eliminated several variables which do not satisfy this requirement. Afterwards, we applied RCMARS to the remaining independent variables.

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Notes

  1. 1.

    For the ease of representation, here and subsequently, we suppress the index m of the subvectors \(\boldsymbol{x}^{m}\) and just write \(\boldsymbol{x}\).

  2. 2.

    For the ease of representation, here and subsequently, we suppress the index m of the subvectors \(\boldsymbol{x}^{m}\) and just write \(\boldsymbol{x}\).

  3. 3.

    For the ease of representation, here and subsequently, we suppress the index m of the subvectors \(\boldsymbol{t}^{m}\) and just write \(\boldsymbol{t}\).

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Authors and Affiliations

  1. Ankara, Turkey

    Ayşe Özmen

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  1. Ayşe Özmen
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Özmen, A. (2016). Real-World Application with Our Robust Tools. In: Robust Optimization of Spline Models and Complex Regulatory Networks. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-319-30800-5_6

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