Korea\u27s Online Stock Trading Boom: Facts and Implications

The Asian financial crisis of 1997-98 was a major setback for Korea, one of the world’s most successful economies in the post-war era. Nevertheless, the financial crisis has led to some positive changes in Korea’s financial system. The Korean government, in conjunction with the IMF, is carrying out comprehensive structural reforms in the financial system. In the meantime, online stock trading has grown explosively since 1998 to the extent that Korea now has the world’s highest penetration rate in this area. In our paper, we analyze the fundamental factors driving the rapid growth of online stock trading in Korea. We then examine the implications of such growth on the competitive environment of Korea’s retail brokerage industry as well as the liquidity, volatility, cost structure and efficiency of the stock market. We also look at the relationship between financial reform and online trading. In addition to exploring possible changes in the value propositions of brokerage firms, we also examine new regulatory issues that have emerged in line with the rapid growth of online trading. In short, our main objective is to study the causes and effects of Korea’s online trading boom

Competitive Environment and Business Strategies for Online Brokerage Firms in Korea

Korea has recently experienced explosive growth in online stock trading, to the extent that the country is now one of the global leaders in this area. In this paper, we examine the implications of this phenomenon on the competitive environment facing retail brokerage firms in Korea as well as their potential strategic responses. Online trading entails low entry barriers and more demanding customers, and thus creates intense competitive pressures. Only those brokers that adapt their business models flexibly and quickly to the new environment, in particular by relying more on customized, fee-based services and less on trading commissions, will make the grade. Although our study is focused on Korea, most of its lessons, particularly those relating to strategic responses for brokers, are applicable to other markets as well

approaches to discover the functional impact of non-synonymous single nucleotide polymorphisms in selective sweep regions of the Landrace genome

Objective The aim of this study was to discover the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) that were found in selective sweep regions of the Landrace genome Methods Whole-genome re-sequencing data were obtained from 40 pigs, including 14 Landrace, 16 Yorkshire, and 10 wild boars, which were generated with the Illumina HiSeq 2000 platform. The nsSNPs in the selective sweep regions of the Landrace genome were identified, and the impacts of these variations on protein function were predicted to reveal their potential association with traits of the Landrace breed, such as reproductive capacity. Results Total of 53,998 nsSNPs in the mapped regions of pigs were identified, and among them, 345 nsSNPs were found in the selective sweep regions of the Landrace genome which were reported previously. The genes featuring these nsSNPs fell into various functional categories, such as reproductive capacity or growth and development during the perinatal period. The impacts of amino acid sequence changes by nsSNPs on protein function were predicted using two in silico SNP prediction algorithms, i.e., sorting intolerant from tolerant and polymorphism phenotyping v2, to reveal their potential roles in biological processes that might be associated with the reproductive capacity of the Landrace breed. Conclusion The findings elucidated the domestication history of the Landrace breed and illustrated how Landrace domestication led to patterns of genetic variation related to superior reproductive capacity. Our novel findings will help understand the process of Landrace domestication at the genome level and provide SNPs that are informative for breeding

A Model for Sustainable Courier Services: Vehicle Routing with Exclusive Lanes

In Southeast Asian cities, it is common for logistic companies to operate a heterogeneous fleet of delivery vehicles with motorcycles being the preferred vehicle to handle the final phase of delivery. In such scenarios, heterogeneous fleet vehicle routing problem (HFVRP) is generally applied to plan an optimal delivery. However, in many downtown cores of large and rapidly developing Southeast Asian cities, HFVRP is neither viable nor reliable because of road usage restrictions. The purpose of this article is to develop and test a different approach that accurately takes these restrictions into account and provides viable and more sustainable results. Restrictions in this paper refer to situations of urban areas in Vietnam where (i) certain vehicle types are prohibited in specified areas or where narrow alleyways limit the utilization of vehicles that exceed the road capacity and (ii) certain roads are exclusive to certain vehicle types. In networks, limited access and exclusive lanes are represented as links, or arcs, exclusive to one or another. Taking these limitations into consideration, we have developed a unique model, which we have termed Vehicle Routing Problem with Exclusive Links (VRP-EL). The model was validated and tested for its performance on scenarios with varying ratios of exclusive links. Scenarios up to 500 customers were tested on a meta-heuristic algorithm, simulated annealing. VRP-EL produces realistic outcomes. Limiting certain links to be selected according to vehicle types increases overall travel distance. However, this increase outweighs the cost of re-planning and rerouting had they not been constrained initially. The reduction in traveling distance leads to fossil fuel reduction for the overall system. The estimation of reduced carbon emissions through applying the proposed model is presented. Considering the severe traffic congestion and carbon emissions caused by motorcycles in Vietnam, the proposed model leads to a sustainable road environment. Document type: Articl

Fine-Grained Socioeconomic Prediction from Satellite Images with Distributional Adjustment

While measuring socioeconomic indicators is critical for local governments to make informed policy decisions, such measurements are often unavailable at fine-grained levels like municipality. This study employs deep learning-based predictions from satellite images to close the gap. We propose a method that assigns a socioeconomic score to each satellite image by capturing the distributional behavior observed in larger areas based on the ground truth. We train an ordinal regression scoring model and adjust the scores to follow the common power law within and across regions. Evaluation based on official statistics in South Korea shows that our method outperforms previous models in predicting population and employment size at both the municipality and grid levels. Our method also demonstrates robust performance in districts with uneven development, suggesting its potential use in developing countries where reliable, fine-grained data is scarce

Negative moments of orthogonal polynomials

If a sequence indexed by nonnegative integers satisfies a linear recurrence without constant terms, one can extend the indices of the sequence to negative integers using the recurrence. Recently, Cigler and Krattenthaler showed that the negative version of the number of bounded Dyck paths is the number of bounded alternating sequences. In this paper, we provide two methods to compute the negative versions of sequences related to moments of orthogonal polynomials. We give a combinatorial model for the negative version of the number of bounded Motzkin paths. We also prove two conjectures of Cigler and Krattenthaler on reciprocity between determinants

Genome analysis of Yucatan miniature pigs to assess their potential as biomedical model animals

Objective Pigs share many physiological, anatomical and genomic similarities with humans, which make them suitable models for biomedical researches. Understanding the genetic status of Yucatan miniature pigs (YMPs) and their association with human diseases will help to assess their potential as biomedical model animals. This study was performed to identify non-synonymous single nucleotide polymorphisms (nsSNPs) in selective sweep regions of the genome of YMPs and present the genetic nsSNP distributions that are potentially associated with disease occurrence in humans. Methods nsSNPs in whole genome resequencing data from 12 YMPs were identified and annotated to predict their possible effects on protein function. Sorting intolerant from tolerant (SIFT) and polymorphism phenotyping v2 analyses were used, and gene ontology (GO) network and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed. Results The results showed that 8,462 genes, encompassing 72,067 nsSNPs were identified, and 118 nsSNPs in 46 genes were predicted as deleterious. GO network analysis classified 13 genes into 5 GO terms (p<0.05) that were associated with kidney development and metabolic processes. Seven genes encompassing nsSNPs were classified into the term associated with Alzheimer’s disease by referencing the genetic association database. The KEGG pathway analysis identified only one significantly enriched pathway (p<0.05), hsa04080: Neuroactive ligand-receptor interaction, among the transcripts. Conclusion The number of deleterious nsSNPs in YMPs was identified and then these variants-containing genes in YMPs data were adopted as the putative human diseases-related genes. The results revealed that many genes encompassing nsSNPs in YMPs were related to the various human genes which are potentially associated with kidney development and metabolic processes as well as human disease occurrence

Effects of exercise on myokine gene expression in horse skeletal muscles

Objective To examine the regulatory effects of exercise on myokine expression in horse skeletal muscle cells, we compared the expression of several myokine genes (interleukin 6 [IL-6], IL-8, chemokine [C-X-C motif] ligand 2 [CXCL2], and chemokine [C-C motif] ligand 4 [CCL4]) after a single bout of exercise in horses. Furthermore, to establish in vitro systems for the validation of exercise effects, we cultured horse skeletal muscle cells and confirmed the expression of these genes after treatment with hydrogen peroxide. Methods The mRNA expression of IL-6, IL-8, CXCL2, and CCL4 after exercise in skeletal muscle tissue was confirmed using quantitative-reverse transcriptase polymerase chain reactions (qRT-PCR). We then extracted horse muscle cells from the skeletal muscle tissue of a neonatal Thoroughbred. Myokine expression after hydrogen peroxide treatments was confirmed using qRT-PCR in horse skeletal muscle cells. Results IL-6, IL-8, CXCL2, and CCL4 expression in Thoroughbred and Jeju horse skeletal muscles significantly increased after exercise. We stably maintained horse skeletal muscle cells in culture and confirmed the expression of the myogenic marker, myoblast determination protein (MyoD). Moreover, myokine expression was validated using hydrogen peroxide (H2O2)-treated horse skeletal muscle cells. The patterns of myokine expression in muscle cells were found to be similar to those observed in skeletal muscle tissue. Conclusion We confirmed that several myokines involved in inflammation were induced by exercise in horse skeletal muscle tissue. In addition, we successfully cultured horse skeletal muscle cells and established an in vitro system to validate associated gene expression and function. This study will provide a valuable system for studying the function of exercise-related genes in the future