Evolutionary algorithms for statistics and finance

Several models in econometrics and finance have been proven to be computationally intractable due to their complexity. In this dissertation, we propose an evolutionary-genetic-algorithm for solving these types of problems. We extend the models so that less restrictive assumptions are required and we cope with the increased complexity by using a modified version of the evolutionary algorithm proposed for the simpler cases. More specifically, we study closer the estimation of switching regression models as introduced by Quandt (1958). The applicability of the proposed algorithms is examined through disequilibrium models; models that provide supply and demand functions for markets, when the price is not adjusted so that the quantity supplied equals the quantity demanded. We focus on the computational aspect of the deterministic switching regression models and we suggest a self-evolving genetic algorithm for solving these types of problems. As an illustration, we present results from Monte Carlo simulations and thereafter we apply the algorithm to the disequilibrium model proposed for the gasoline market during the “energy crisis”. We further extend the “general model” for markets in disequilibrium by incorporating dynamic relationships, and we examine the applicability of the proposed genetic algorithm in this more complex and realistic problem. Subsequently, the proposed genetic algorithm for the markets in disequilibrium is applied to financial models, where the structure and computational complexity are comparable with those of the switching regression models. As example, we apply the algorithm to minimizing portfolio tracking error with respect to a pre-specified index. The proposed genetic algorithm possesses unique characteristics that maximize the fitness of the algorithm itself for each individual problem. This is achieved through a Self-Evolving process that teaches the genetic algorithm what internal parameters improve the algorithm\u27s fitness

Surface modified multifunctional and stimuli responsive nanoparticles for drug targeting: Current status and uses

WOS: 000385525500067PubMed ID: 27589733Nanocarriers, due to their unique features, are of increased interest among researchers working with pharmaceutical formulations. Polymeric nanoparticles and nanocapsules, involving non-toxic biodegradable polymers, liposomes, solid lipid nanoparticles, and inorganic-organic nanomaterials, are among the most used carriers for drugs for a broad spectrum of targeted diseases. In fact, oral, injectable, transdermal-dermal and ocular formulations mainly consist of the aforementioned nanomaterials demonstrating promising characteristics such as long circulation, specific targeting, high drug loading capacity, enhanced intracellular penetration, and so on. Over the last decade, huge advances in the development of novel, safer and less toxic nanocarriers with amended properties have been made. In addition, multifunctional nanocarriers combining chemical substances, vitamins and peptides via coupling chemistry, inorganic particles coated by biocompatible materials seem to play a key role considering that functionalization can enhance characteristics such as biocompatibility, targetability, environmental friendliness, and intracellular penetration while also have limited side effects. This review aims to summarize the state of the art of drug delivery carriers in nanosize, paying attention to their surface functionalization with ligands and other small or polymeric compounds so as to upgrade active and passive targeting, different release patterns as well as cell targeting and stimuli responsibility. Lastly, future aspects and potential uses of nanoparticulated drug systems are outlined

Vegetation and sand characteristics influencing nesting activity of Caretta caretta on Sekania beach

Despite its relatively small length (650 m), Sekania beach on Zakynthos island (Ionian sea) is the single most important Caretta caretta L. nesting beach in the Mediterranean Sea. The aim of this work was to tackle the possible relationships of sand and vegetation characteristics with the nesting activity of sea turtle C. caretta. The vegetation structure and distribution along the sandy beach was studied with the use of line transect method. Grouping of plant species was revealed through an ordination method. Plant groups were distinguished and mapped. Sand texture, pH, and organic matter were measured on the transects. Nesting activity was also mapped on the beach and hatching success was recorded. It was concluded that where sand salinity is high enough to prevent vegetation development, wet sand is located at a threshold depth for excavating an egg chamber. It seems that well-sorted sand grains favor nesting activity on the beach. The increase of fine sand - from east to west - is proportional with the reduction of nesting density. The data collected for this study are organized in a GIS database, which could be the basis for the establishment of an integrated monitoring system for Sekania beach. © 2004 Elsevier Ltd. All rights reserved

Vegetation and sand characteristics influencing nesting activity of Caretta caretta on Sekania beach

Despite its relatively small length (650 m), Sekania beach on Zakynthos island (Ionian sea) is the single most important Caretta caretta L. nesting beach in the Mediterranean Sea. The aim of this work was to tackle the possible relationships of sand and vegetation characteristics with the nesting activity of sea turtle C. caretta. The vegetation structure and distribution along the sandy beach was studied with the use of line transect method. Grouping of plant species was revealed through an ordination method. Plant groups were distinguished and mapped. Sand texture, pH, and organic matter were measured on the transects. Nesting activity was also mapped on the beach and hatching success was recorded. It was concluded that where sand salinity is high enough to prevent vegetation development, wet sand is located at a threshold depth for excavating an egg chamber. It seems that well-sorted sand grains favor nesting activity on the beach. The increase of fine sand - from east to west - is proportional with the reduction of nesting density. The data collected for this study are organized in a GIS database, which could be the basis for the establishment of an integrated monitoring system for Sekania beach. © 2004 Elsevier Ltd. All rights reserved

Commodity Trading Advisors: Risk Performance Analysis and Selection

This book represent a complate course in the hows and whys of investing with CTAs.institutioanal and individual investor would be wise to understand the issuseraised here in order to properly control thier CTA investment