299 research outputs found
The Stochastics of Threshold Accepting: Analysis of an Application to the Uniform Design Problem
No full textThreshold Accepting (TA) is a powerful optimization heuristic from the class of stochastic local search algorithms. It has been applied successfully to different optimization problems in statistics and econometrics, including the uniform design problem. Using the latter application as example, the stochastic properties of a TA implementation are analyzed. We provide a formal framework for the analysis of optimization heuristics like TA, which can be used to estimate lower bounds and to derive convergence results. It is also helpful for tuning real applications. Based on this framework, empirical results are presented for the uniform design problem. In particular, for two problem instances, the rate of convergence of the algorithm is estimated to be of the order of a power of -0.3 to -0.7 of the number of iterations. --Heuristic optimization,Threshold Accepting,Stochastic analysis of heuristics
Robust Portfolio Optimization with a Hybrid Heuristic Algorithm
No full textEstimation errors in both the expected returns and the covariance matrix hamper the constructing of reliable portfolios within the Markowitz framework. Robust techniques that incorporate the uncertainty about the unknown parameters are suggested in the literature. We propose a modification as well as an extension of such a technique and compare both with another robust approach. In order to eliminate oversimplifications of Markowitz’ portfolio theory, we generalize the optimization framework to better emulate a more realistic investment environment. Because the adjusted optimization problem is no longer solvable with standard algorithms, we employ a hybrid heuristic to tackle this problem. Our empirical analysis is conducted with a moving time window for returns of the German stock index DAX100. The results of all three robust approaches yield more stable portfolio compositions than those of the original Markowitz framework. Moreover, the out-of-sample risk of the robust approaches is lower and less volatile while their returns are not necessarily smaller.Hybrid heuristic algorithm, Markowitz, Robust optimization, Uncertainty sets.
Optimal Lag Structure Selection in VEC-Models
No full textFor 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. However, the resulting finite-sample estimates may depend strongly on the specification of the model dynamics. We propose a method for automatic identification of the dynamic part of VEC-models. Model selection is based on a modified information criterion. The lag structure of the model is selected according to this objective function allowing for "holes". The resulting complex discrete optimization problem is tackled using a hybrid heuristic combining ideas from threshold accepting and memetic algorithms. We present the algorithm and the results of a simulation study showing the method's performance both with regard to the dynamic structure and the rank selection in the VEC-model. The results indicate that the selection of the cointregation rank might depend strongly on the specification of the dynamic part of the VEC-modelModel selection; cointegration rank; reduced rank regression
The convergence of optimization based estimators : theory and application to a GARCH-model
No full textThe convergence of estimators, e.g. maximum likelihood estimators, for increasing sample size is well understood in many cases. However, even when the rate of convergence of the estimator is known, practical application is hampered by the fact, that the estimator cannot always be obtained at tenable computational cost. This paper combines the analysis of convergence of the estimator itself with the analysis of the convergence of stochastic optimization algorithms, e.g. threshold accepting, to the theoretical estimator. We discuss the joint convergence of estimator and algorithm in a formal framework. An application to a GARCH-model demonstrates the approach in practice by estimating actual rates of convergence through a large scale simulation study. Despite of the additional stochastic component introduced by the use of an optimization heuristic, the overall quality of the estimates turns out to be superior compared to conventional approaches. --GARCH,Threshold Accepting,Optimization Heuristics,Convergence
Forecasting Russian Foreign Trade Comparative Advantages in the Context of a Potential WTO Accession
No full textFor the private and public sector in any particular country it is crucial to know, which industries may exhibit comparative advantages, that for some reasons are not realized. This can efficiently help all current and potential actors to improve their economic strategy both at the micro- and macroeconomic level. In this paper we propose an approach of forecasting comparative advantages dynamics in foreign trade. The instrument is based on relative price differences and is efficient for countries in the process of economic liberalization. An empirical analysis based on the example of Central and East European countries confirms a good performance in the sense of predictive power of this instrument. On the example of Russia, experiencing a period of economic liberalization and with the prospect to join the WTO agreements, we demonstrate which sectors are most likely to contain comparative advantages in the near future.comparative advantage, economy in transition, Balassa index, Lafay index
Results of ANOVA and MANOVA, testing the effects of taxonomy on genetic and phenotypic divergence using only reciprocally monophyletic populations (and excluding lineages already considered full species) for comparisons (details in Table H in S1 File).
No full textResults of ANOVA and MANOVA, testing the effects of taxonomy on genetic and phenotypic divergence using only reciprocally monophyletic populations (and excluding lineages already considered full species) for comparisons (details in Table H in S1 File).</p
Diet and seed dispersal in two species of tanagers (Habia) from two types of vegetation in Los Tuxtlas, Ceracruz, Mexico
No full textFecal samples from mist-netted birds were used to determine the diet of the Red-throated (Habia fuscicauda) and Red-crowned (H. rubica) ant-tanagers in secondary vegetation and rainforest. The diet of both species is comprised mainly of various fruit species (65.9% and 66.6%) with animal prey making up a minor proportion (24.1% and 21.2%). Both species are considered dietary generalists and opportunists. In Los Tuxtlas, their diets are remarkably similar. The two species occur with equal frequency in the two types of studied vegetation and disperse seeds of several species of plant pioneers. These seeds are of great importance in the formation of seed banks that permit the development of secondary vegetation and, in the long run, the regeneration of the rainforest
- …
