RMARS: Robustification of multivariate adaptive regression spline under polyhedral uncertainty

2014-03-15
Ozmen, Ayse
Weber, Gerhard Wilhelm
Since, with increased volatility and further uncertainties, financial crises translated a high "noise" within data from financial markets and economies into the related models, recent years' events in the financial world have led to radically untrustworthy representations of the future. Hence, robustification started to attract more attention in finance. The presence of noise and data uncertainty raises critical problems to be dealt with on the theoretical and computational side. For immunizing against parametric uncertainties, robust optimization has gained greatly in importance as a modeling framework from both a theoretical and a practical point of view. Consequently, we include the existence of uncertainty considering future scenarios in the multivariate adaptive regression spline (MARS) that has an apparent success in modeling real-life data in a variety of application fields, and robustify it through robust optimization proposed to cope with data and resulting model parameter uncertainty. We represent the new Robust MARS (RMARS) in theory and method and apply RMARS on financial market data. We demonstrate its good performance with a simulation study and a numerical experience that refers to basic economic indicators. Results indicate that models from RMARS have much less variability in parameter estimates and in accuracy measures, to the cost of just a slightly lower accuracy than MARS.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

Suggestions

Analysis of volatility feedback and leverage effects on the ISE30 index using high frequency data
Inkaya, A.; Okur, Y. Yolcu (Elsevier BV, 2014-03-15)
In this study, we employ the techniques of Malliavin calculus to analyze the volatility feedback and leverage effects for a better understanding of financial market dynamics. We estimate both effects for a general semimartingale model applying Fourier analysis developed in Malliavin and Mancino (2002) [10]. We further investigate their joint behaviour using 5 min data of the ISE30 index. On the basis of these estimations, we look for the evidence that volatility feedback effect rate can be employed in the s...
Stochastic processes adapted by neural networks with application to climate, energy, and finance
Giebel, Stefan; Rainer, Martin (Elsevier BV, 2011-10-01)
Local climate parameters may naturally effect the price of many commodities and their derivatives. Therefore we propose a joint framework for stochastic modeling of climate and commodity prices. In our setting, a stable Levy process is drift augmented to a generalized SDE. The related nonlinear function on the state space typically exhibits deterministic chaos. Additionally, a neural network adapts the parameters of the stable process such that the latter produces increasingly optimal differences between si...
On the correlation of the supremum and the infimum and of maximum gain and maximum loss of Brownian motion with drift
Vardar Acar, Ceren; Szekely, Gabor J. (Elsevier BV, 2013-08-15)
Investors are naturally interested in the supremum and the infimum of stock prices, also in the maximum gain and the maximum loss over a time period. To shed light on these relatively complicated aspects of sample paths, we consider Brownian motion with and without drift. We provide explicit calculations of the correlation between the supremum and the infimum of Brownian motion with drift. We establish a number of results concerning the distributions of maximum gain and maximum loss. We present simulation s...
Stochastic volatility and stochastic interest rate model with jump and its application on General Electric data
Celep, Betül; Hayfavi, Azize; Department of Financial Mathematics (2011)
In this thesis, we present two different approaches for the stochastic volatility and stochastic interest rate model with jump and analyze the performance of four alternative models. In the first approach, suggested by Scott, the closed form solution for prices on European call stock options are developed by deriving characteristic functions with the help of martingale methods. Here, we study the asset price process and give in detail the derivation of the European call option price process. The second appr...
Scalar curvature and connected sums of self-dual 4-manifolds
Kalafat, Mustafa (European Mathematical Society Publishing House, 2011-01-01)
Under a reasonable vanishing hypothesis, Donaldson and Friedman proved that the connected sum of two self-dual Riemannian 4-manifolds is again self-dual. Here we prove that the same result can be extended to the positive scalar curvature case. This is an analogue of the classical theorem of Gromov-Lawson and Schoen-Yau in the self-dual category. The proof is based on twistor theory.
Citation Formats
A. Ozmen and G. W. Weber, “RMARS: Robustification of multivariate adaptive regression spline under polyhedral uncertainty,” JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, pp. 914–924, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56444.