Risk factor extraction with quantile regression method

Firm characteristics based risk factors constitute a large part of the asset pricing literature. These characteristic based factors are constructed using the extreme quantiles of the sorted portfolios based on the firm characteristic in question. Yet to date, there is no consensus on a systematic approach to determine the optimal quantile used for extracting firm characteristic based risk factors. In addition, it is a stylised fact that asset prices exhibit heteroscedastic behavior, and counting on the extreme portfolios to extract the characteristic factors can produce unexpected result. In this study, we use quantile regressions to determine the optimal quantiles used in portfolios sorts to extract characteristic based risk factors used in asset pricing. Quantile regressions are well-suited to identify the quantiles needed to extract firm characteristic based factors, especially when the firm characteristic based factors and stock returns relationship is non-linear. More over, quantile regressions presents the quantile-by-quantile risk-return coefficients, thereby verifying the behavior of the extreme quantiles used in the factor construction. By examining the relationship between common characteristic based factors and stock returns in 23 developed countries, we observed that the optimal quantiles used to construct the common factors may differ between factors, but is similar across the North American, Asia-Pacific and Europe regions.

     

Multi-objective parallel machine scheduling problems by considering controllable processing times

This study examines parallel machine scheduling problems with controllable processing times. The processing time of each job can be between lower and upper bounds, and a cost is associated with the processing of a job on a machine. The processing time of a job can be decreased, which may lower the cycle time, although doing so would incur additional costs. This study develops two multi-objective mathematical models, which consist of two and three inconsistent objective functions, respectively. The first model minimizes the total manufacturing cost (TMC) and the total weighted tardiness (TWT) simultaneously, while the second uses makespan (C_max) as an additional objective function. In contrast to conventional mathematical models, efficient solutions are attained using the lexicographic weighted Tchebycheff method (LWT). Experimental results indicate that the LWT yields better-spread solutions and obtains more non-dominated solutions than its alternative, that is the weighted-sum method, which is a widely used yet promising approach to achieve multi-objective optimization. Results of this study also demonstrate that in purchasing machines, the variation in the fixed costs associated with the processing of jobs on machines is critical to reducing TWT. Moreover, using C_max as an additional objective function typically improves TWT and worsens TMC.     

Modification and stabilizing effects of PEG on resveratrol-loaded solid lipid nanoparticles

Resveratrol-loaded solid lipid nanoparticles (SLNs) modified by polyethylene glycol (PEG2000) (RES–PEG–SLNs) were prepared to study the stabilizing influences of PEG2000 on SLNs properties including loading capacity, particle size, photostability, and release. The micromorphology, particle size distribution, drug–lipid–modifier interaction and crystalline structure were characterized to elucidate stabilizing effects of PEG2000 on SLNs. Compared with ordinary SLNs, SLNs modified by PEG2000 at relatively low amounts of [m(PEG2000):m(lipids) = 1:10] exhibit high drug loading, steady nanoparticle size distributions, photostability and sustained release. According to characterizations, RES–PEG–SLNs formation is dependent on the physical interactions of drug–lipid–modifier. Since PEG2000 is doped into lipid matrix in a non-crystalline state, the lipids crystalline arrangement is disrupted. Additionally, RES–PEG–SLNs are crystallized in a PEG2000/lipid eutectic mixture rather than a simple mixture, inhibiting the lipid polymorphism transformation from α- to β-form, and therefore preventing drug exclusion from the lipid matrix. The PEG2000/lipid matrix contains lattice defects, which allow for the incorporation of more resveratrol and preventing it from photodegradation effectively. In contrast to the burst release of SLNs modified without PEG2000, resveratrol is released more slowly from the lattice defects in lipid matrix of RES–PEG–SLNs, resulting in a sustained release fitted by a two-stage exponential kinetic equation. PEG2000 is distributed on the RES–PEG–SLNs surface, increasing repulsion between nanoparticles and avoiding particles aggregation. These results confirm that both matrix doping effects and surface steric hindrance produced by the presence of PEG2000 play important roles in maintaining high loadings, nanoparticle size, photostability and sustained release.