Book Review - Blood, Bone and Marrow: A Biography of Harry Crews

A book review of Blood, Bone and Marrow: A Biography of Harry Crews by Ted Geltner. This is the first biography of writer Harry Crews. It covers his life as an author of several books and articles and a teacher of creative writing

Least Median of Squares Estimation by Optimization Heuristics with an Application to the CAPM and Multi Factor Models

For estimating the parameters of models for financial market data, the use of robust techniques is of particular interest. Conditional forecasts, based on the capital asset pricing model, and a factor model are considered. It is proposed to consider least median of squares estimators as one possible alternative to ordinary least squares. Given the complexity of the objective function for the least median of squares estimator, the estimates are obtained by means of optimization heuristics. The performance of two heuristics is compared, namely differential evolution and threshold accepting. It is shown that these methods are well suited to obtain least median of squares estimators for real world problems. Furthermore, it is analyzed to what extent parameter estimates and conditional forecasts differ between the two estimators. The empirical analysis considers daily and monthly data on some stocks from the Dow Jones Industrial Average Index (DJIA).LMS, CAPM, Multi Factor Model, Differential Evolution, Threshold Accepting

Optimized U-type Designs on Flexible Regions

The concept of a flexible region describes an infinite variety of symmetrical shapes to enclose a particular region of interest within a space. In experimental design, the properties of a function on the region of interest is analyzed based on a set of design points. The choice of design points can be made based on some discrepancy criterion. This paper investigates the generation of design points on a flexible region. It uses a recently proposed new measure of discrepancy for this purpose, the Central Composite Discrepancy. The optimization heuristic Threshold Accepting is used to generate low discrepancy Utype designs. The proposed algorithm is capable to construct optimal U-type designs under various flexible experimental regions in two or more dimensions. The illustrative results for the two dimensional case indicate that using an optimization heuristic in combination with an appropriate discrepancy measure, it is possible to produce high quality experimental designs on flexible regions.Central composite discrepancy, Experimental design, Flexible regions, Threshold accepting, U-type design