AND STOCHASTIC OPTIMIZATION ALGORITHMS FOR UNIFORM DESIGNS WITH THREE OR FOUR LEVELS (2008)
Lower Bounds, Kai-tai Fang, Dietmar Maringer, Yu Tang, Peter Winker
Abstract. New lower bounds for three- and four-level designs under the centered L2-discrepancy are provided. We describe necessary conditions for the existence of a uniform design meeting these lower...
Optimization of Cardinality Constrained Portfolios with an Hybrid Local Search Algorithm (2001)
Hans Kellerer Dietmar, Dietmar Maringer
this paper we suggest a hybrid local search algorithm which combines principles of Simulated Annealing and Evolutionary Strategies and which proved to highly e#ciently approach this problem
Optimal Lag Structure Selection in VEC-Models
Dietmar Maringer, Peter Winker
For modelling economic and financial time series, multivariate linear and nonlinear systems of equations have become a standard tool. These models can also be applied to non-stationary processes....
Distribution assumptions and risk constraints in portfolio optimization
Empirical distributions are often claimed to be superior to parametric distributions, yet to also increase the computational complexity and are therefore hard to apply in portfolio optimization. In...
Smooth Transition Autoregressive (STAR) Models
Non-linear modeling approaches, including Smooth Transition Autoregressive (STAR) models, have attracted a great deal of attention over the last two decades. The empirical application of these...
APT At Work: Finding The Relevant Risk Factors For Asset Pricing
APT, Combinatorial Optimization, Risk Management, Heuristics
Smooth Transition Autoregressive Models -- New Approaches to the Model Selection Problem
It has been shown in the literature that the task of estimating the parameters of nonlinear models may be tackled with optimization heuristics. Thus, we attempt to carry these intuitions over to the...
The convergence of estimators based on heuristics: theory and application to a GARCH model
Peter Winker, Dietmar Maringer
GARCH, Threshold accepting, Optimization heuristics, Convergence,