bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient calculation of transient eddy current response from multi-layer cylindrical conductive media
Authors: Theodoulidis Theodoros , Skarlatos Anastassios
Published: September 2020

The transient response from a transmitter–receiver coil system inside a multi-layer cylindrical conductive configuration is obtained. The particular set-up applies to well logging as well as to eddy current tube testing. In this work, a number of improvements are presented to existing models for an efficient calculation of the induced voltage. These include: domain truncation, novel treatment of arbitrary number of layers in order to avoid computational overflows and efficient time response calculation. The latter is based on a combination of Laplace inversion techniques for short- and long-time transient responses.

This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Capacitive imaging for adhesive bonds and quality evaluation
Authors: Huang Xuhui , Hamilton Ciaron , Li Zonglin , Udpa Lalita , Udpa Satish S. , Deng Yiming
Published: September 2020

Defective adhesive bonds pose significant threats towards structural integrity due to reduced joint strength. The nature of the adhesion of two solids remains poorly understood since the adhesion phenomenon is relevant to so many scientific and technological areas. A concept that has been gaining our attention from the perspective of non-destructive testing is the properties discontinuity of the adhesion. Discontinued properties depend significantly on the quality of the interface that is formed between adhesive and substrate. In this research, discontinued electrical properties at the interface are considered. The simplified model is free from multidisciplinary knowledge of chemistry, fracture mechanics, mechanics of materials, rheology and other subjects. From a practical standpoint, this emphasizes the need to establish a good relationship between electrical properties of adhesive bonds and corresponding measurements. Capacitive imaging (CI) is a technique where the dielectric property of an object is determined from external capacitance measurements. Thus, it is potentially promising since adhesive and substrate differ in terms of dielectric property. At the interface between adhesive and substrate, discontinuity of the dielectric properties causes abrupt changes in electric field spatial distribution and thus alters capacitance measurement by simulating defects in adhesive joints regarding permittivity uncertainties. Further understanding of the cause of degraded adhesion quality can be obtained.

This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Resonant frequency tracking mode on eddy current pulsed thermography non-destructive testing
Authors: Miao Ling , Gao Bin , Li Haoran , Tian Guiyun
Published: September 2020

Eddy current pulsed thermography (ECPT) has been widely used in the field of non-destructive testing due to its safety, non-contact detection, high spatial resolution and intuitive results. Inductive excitation source is an important component of ECPT and provides high-frequency alternating current to drive the excitation coil. However, a resonant frequency distortion phenomenon exists in the excitation source during the detection process, which seriously affects the output power of the excitation source and the sample detection effect. This paper presents a fast resonant frequency tracking loop for full bridge series resonant inverter which is used to search the resonance frequency in real time through direct digital synthesizer (DDS) and all-digital phase-locked loop. Theoretical analysis and simulation are presented to explain the working principle of the loop. Then, an experimental prototype is manufactured which serves as an excitation source for the ECPT experimental system. Compared with traditional excitation sources, the prototype does not need a water-cooled device and the tracking speed can be adjusted by modifying the parameters of DDS. Finally, experiments have been conducted on both artificial slot of 45# steel and natural cracks of rail and stainless steel to investigate the influence of resonant frequency tracking speed on the crack detection. The results revealed that reducing the resonant frequency tracking time can efficiently improve defect detectability and the manufactured prototype showed more application potential.

This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Terahertz smart dynamic and active functional electromagnetic metasurfaces and their applications
Authors: Yaxin Zhang , Hongxin Zeng , Wei Kou , Lan Wang , Mittleman Daniel M. , Ziqiang Yang
Published: September 2020

The demand for smart and multi-functional applications in the terahertz (THz) frequency band, such as for communication, imaging, spectroscopy, sensing and THz integrated circuits, motivates the development of novel active, controllable and informational devices for manipulating and controlling THz waves. Metasurfaces are planar artificial structures composed of thousands of unit cells or metallic structures, whose size is either comparable to or smaller than the wavelength of the illuminated wave, which can efficiently interact with the THz wave and exhibit additional degrees of freedom to modulate the THz wave. In the past decades, active metasurfaces have been developed by combining diode arrays, two-dimensional active materials, two-dimensional electron gases, phase transition material films and other such elements, which can overcome the limitations of conventional bulk materials and structures for applications in compact THz multi-functional antennas, diffractive devices, high-speed data transmission and high-resolution imaging. In this paper, we provide a brief overview of the development of dynamic and active functional electromagnetic metasurfaces and their applications in the THz band in recent years. Different kinds of active metasurfaces are cited and introduced. We believe that, in the future, active metasurfaces will be combined with digitalization and coding to yield more intelligent metasurfaces, which can be used to realize smart THz wave beam scanning, automatic target recognition imaging, self-adaptive directional high-speed data transmission network, biological intelligent detection and other such applications.

This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Cortical response to naturalistic stimuli is largely predictable with deep neural networks
Authors: Khosla Meenakshi , Ngo Gia H. , Jamison Keith , Kuceyeski Amy , Sabuncu Mert R.
Published: September 2020

Naturalistic stimuli, such as movies, activate a substantial portion of the human brain, invoking a response shared across individuals. Encoding models that predict the neural response to a given stimulus can be very useful for studying brain function. However, existing neural encoding models focus on limited aspects of naturalistic stimuli, ignoring the complex and dynamic interactions of modalities in this inherently context-rich paradigm. Using movie watching data from the Human Connectome Project (HCP,N= 158) database, we build group-level models of neural activity that incorporate several inductive biases about information processing in the brain, including hierarchical processing, assimilation over longer timescales and multi-sensory auditory-visual interactions. We demonstrate how incorporating this joint information leads to remarkable prediction performance across large areas of the cortex, well beyond the visual and auditory cortices into multi-sensory sites and frontal cortex. Furthermore, we illustrate that encoding models learn high-level concepts that generalize remarkably well to alternate task-bound paradigms. Taken together, our findings underscore the potential of neural encoding models as a powerful tool for studying brain function in ecologically valid conditions.
Secondary traumatic stress and burnout in healthcare workers during COVID-19 outbreak
Authors: Marzetti F. , Vagheggini G. , Conversano C. , Miccoli M. , Gemignani A. , Ciacchini R. , Panait E. , Orrù G.
Published: September 2020

Aims

To assess the level of professional burnout and secondary traumatic stress, and to identify potential risk or protective factors among health care workers (HCWs) during the coronavirus disease 2019 (COVID-19) outbreak.

Materials and Methods

This cross-sectional study, based on an online survey, collected demographic data and mental distress outcomes from 184 HCWs from May 1st, 2020, to June,15th, 2020, from 45 different countries. The degree of secondary traumatization was assessed using the Secondary Traumatic Stress Scale (STSS), the degrees of perceived stress and burnout were assessed with Perceived Stress Scale (PSS) and Maslach Burnout Inventory Human Service Survey (MBI-HSS) respectively. Stepwise multiple regression analysis was performed to identify potential risk and protective factors for STS.

Results

184 HCWs (M=90; Age mean: 46.45; SD:11.02) completed the survey. A considerable proportion of HCWs had symptoms of secondary traumatic stress (41.3%), emotional exhaustion (56.0%), and depersonalization (48.9%). The prevalence of secondary traumatic stress in frontline HCWs was 47.5% while in HCWs working in other units it was 30.3% (p<.023); additionally, the prevalence of the same outcome was 67.1% for the HCWs exposed to patients’ death and 32.9% for those HCWs which were not exposed to the same condition (p<.001). In stepwise multiple regression analysis, perceived stress, emotional exhaustion and exposure to patients’ death remained as significant predictors in the final model for secondary traumatic stress (adjusted R2 = 0.537, p< 0.001).

Conclusions

During the current COVID-19 pandemic, HCWs facing patients’ physical pain, psychological suffering, and death are more likely to develop secondary traumatization.
AI for radiographic COVID-19 detection selects shortcuts over signal
Authors: DeGrave Alex J. , Janizek Joseph D. , Lee Su-In
Published: September 2020

Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately detect COVID-19 in chest radiographs. However, the robustness of these systems remains unclear. Using state-of-the-art techniques in explainable AI, we demonstrate that recent deep learning systems to detect COVID-19 from chest radiographs rely on confounding factors rather than medical pathology, creating an alarming situation in which the systems appear accurate, but fail when tested in new hospitals.
Global incidence of sudden cardiac arrest in young athletes and military members: a systematic review and meta-analysis
Authors: Lear Aaron , Patel Niraj , Mullen Chanda , Simonson Marian , Leone Vince , Koshiaris Constantinos , Nunan David
Published: September 2020

Objectives

The goals of this review are to evaluate the quality of the evidence on epidemiology of SCA/D in athletes and military members; and to synthesize existing data to estimate annual incidence of SCA/D.

Design

Systematic review and meta-analysis.

Data Sources

MEDLINE, Embase, Cochrane CENTRAL, Web of Science, BIOSIS, Scopus, SPORT discus, PEDro, were searched from inception to date searched between 2/21/19 and 3/1/19, and Clinicaltrials.gov on 7/29/19. All databases were searched without limits on language.

Eligibility for selecting studies

Studies which report incidence, or data from which incidence can be calculated, of SCA/D or both in athletes, or military members age 40.

Results

40 total studies were included. Overall quality of the evidence was judged to be poor. 35 of 40 included studies reported 1,902 events of SCD over 404,268,083 person years and a pooled incidence rate of 1.39events per 100,000 person years (95% CI: 0.80, 2.43) with high heterogeneity (I2=99%). 11 studies reported 219 events of SCA over 13,450,396 person years and a pooled incidence rate of 3.05 events per 100,000 person years (95% CI: 1.42, 6.58) with high heterogeneity (I2=96%).

Conclusion

The worldwide incidence of sudden cardiac death and arrest in young otherwise healthy athletes and military personnel is low. Available subgroup analysis showed incidence rates were highest in males; military members, elite athletes; and soccer athletes. Findings are tempered by unexplained heterogeneity and risk of bias in included studies.

PROSPERO Registration: CRD42019125560
Sensing of COVID-19 Antibodies in Seconds via Aerosol Jet Printed Three Dimensional Electrodes
Authors: Ali Md. Azahar , Hu Chunshan , Jahan Sanjida , Yuan Bin , Saleh Mohammad Sadeq , Ju Enguo , Gao Shou-Jiang , Panat Rahul
Published: September 2020

Rapid diagnosis is critical for the treatment and prevention of diseases. In this research, we report sensing of antibodies specific to SARS-CoV-2 virus in seconds via an electrochemical platform consisting of gold micropillar array electrodes decorated with reduced graphene oxide and functionalized with recombinant viral antigens. The array electrodes are fabricated by Aerosol Jet (AJ) nanoparticle 3D printing, where gold nanoparticles (3-5nm) are assembled in 3D space, sintered, and integrated with a microfluidic device. The device is shown to detect antibodies to SARS-CoV-2 spike S1 protein and its receptor-binding-domain (RBD) at concentrations down to 1pM via electrochemical impedance spectroscopy and read by a smartphone-based user interface. In addition, the sensor can be regenerated within a minute by introducing a low-pH chemistry that elutes the antibodies from the antigens, allowing successive testing of multiple antibody samples using the same sensor. The detection time for the two antibodies tested in this work is 11.5 seconds. S1 protein sensing of its antibodies is specific, which cross-reacts neither with other antibodies nor with proteins such as Nucleocapsid antibody and Interleukin-6 protein. The proposed sensing platform is generic and can also be used for the rapid detection of biomarkers for other infectious agents such as Ebola, HIV, and Zika, which will benefit the public health.
Genome sequencing of sewage detects regionally prevalent SARS-CoV-2 variants
Authors: Crits-Christoph Alexander , Kantor Rose S. , Olm Matthew R. , Whitney Oscar N. , Al-Shayeb Basem , Lou Yue C. , Flamholz Avi , Kennedy Lauren C. , Greenwald Hannah , Hinkle Adrian , Hetzel Jonathan , Spitzer Sara , Koble Jeffery , Tan Asako , Hyde Fred , Schroth Gary , Kuersten Scott , Banfield Jillian F. , Nelson Kara L.
Published: September 2020

Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and near-complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant (SNV) calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the US or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside of CA, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.
A two-site flexible clamp mechanism for RET-GDNF-GFRα1 assembly reveals both conformational adaptation and strict geometric spacing
Authors: Adams Sarah E. , Purkiss Andrew G. , Knowles Phillip P. , Nans Andrea , Briggs David C. , Borg Annabel , Earl Christopher P. , Goodman Kerry M. , Nawrotek Agata , Borg Aaron J. , McIntosh Pauline B. , Houghton Francesca M. , Kjær Svend , McDonald Neil Q.
Published: September 2020

RET receptor tyrosine kinase plays vital developmental and neuroprotective roles in metazoans.GDNF family ligands (GFLs) when bound to cognate GFRα co-receptors recognise and activate RET stimulating its cytoplasmic kinase function. The principles for RET ligand-co-receptor recognition are incompletely understood. Here we report a crystal structure of the cadherin-like module (CLD1-4) from zebrafish RET revealing interdomain flexibility between CLD2-CLD3. Comparison with a cryo-EM structure of a ligand-engaged zebrafish RETECD-GDNF-GFRα1 complex indicates conformational changes within a clade-specific CLD3 loop adjacent to co-receptor. Our observations indicate RET is a molecular clamp with a flexible calcium-dependent arm that adapts to different GFRα co-receptors, while its rigid arm recognises a GFL dimer to align both membrane-proximal cysteine-rich domains. We also visualise linear arrays of RETECD-GDNF-GFRα1 suggesting a conserved contact stabilises higher-order species. Our study reveals ligand-co-receptor recognition by RET involves both receptor plasticity and strict spacing of receptor dimers by GFL ligands.

Highlights

Crystal structure of zebrafish RET cadherin-like module reveals conformational flexibility at the calcium-dependent CLD2-CLD3 interface

Comparison of X-ray and cryo-EM structures indicate conformational differences between unliganded and liganded RET involving a clade-specific CLD3 loop

Strict spatial separation of RETECDC-termini is imposed by each cysteine-rich domain interaction with GFL dimer

Differences in co-receptor engagement and higher-order ligand-bound RET complexes indicate potentially divergent signalling mechanisms
DNA damage and oxidizing conditions activate p53 through differential upstream signaling pathways
Authors: Shi Tao , Polderman Paulien E. , Burgering Boudewijn M.T. , Dansen Tobias B.
Published: September 2020

Stabilization and activation of the p53 tumour suppressor are triggered in response to various cellular stresses, including DNA damaging agents and elevated Reactive Oxygen Species (ROS) like H2O2. When cells are exposed to exogenously added H2O2, ATR/CHK1 and ATM/CHK2 dependent DNA damage signaling is switched on, suggesting that H2O2induces both single and double strand breaks. These collective observations have resulted in the widely accepted model that oxidizing conditions lead to DNA damage that subsequently mediates a p53-dependent response like cell cycle arrest and apoptosis. However, H2O2induces signaling through stress-activated kinases (SAPK, e.g., JNK and p38MAPK) that can activate p53. Here we dissect to what extent these pathways contribute to functional activation of p53 in response to oxidizing conditions. Collectively, our data suggest that p53 can be activated both by SAPK signaling and the DDR independently of each other, and which of these pathways is activated depends on the type of oxidant used. This implies that it could in principle be possible to modulate redox signaling to stimulate p53 without inducing collateral DNA damage, thereby limiting mutation accumulation in both healthy and tumor tissues.
Phospho-β-catenin expression in primary and metastatic melanomas and in tumor-free visceral tissues
Authors: Pinczewski Joel , Obeng Rebecca , Slingluff Craig L. , Engelhard Victor H.
Published: September 2020

β-catenin (βcat) is an important downstream effector in the Wnt signaling pathway and plays an important role in the development and progression of many cancers including melanoma. βcat expression is regulated by GSK-3β-mediated phosphorylation at positions 33, 37 and 41. In normal cells, phosphorylation at these sites triggers proteasomal degradation, which in turn prevents accumulation of free cytoplasmic βcat. In cancer cells, stabilized β-catenin translocates into the nucleus, where it associates with TCF/Lef proteins to activate transcription of genes that promote tumorigenesis and metastasis. It has been suggested that nuclear phospho-βcat (pβcat) staining may be diagnostically useful in differentiating primary from metastatic melanoma. Also, a pβcat peptide (residues 30-39, p33) is naturally presented by melanoma cells as a T-cell target. We evaluated the expression of pS33-βcat in primary and metastatic melanoma tissues by immunohistochemistry. pS33-βcat was detected in primary and metastatic melanomas and was most commonly cytoplasmic and almost never exclusively nuclear. Interestingly, staining with pS33-βcat and pS33/37/T41-βcat antibodies was most intense in mitotic melanoma cells, consistent with prior studies demonstrating changes in the level of βcat during cell division. We observed no significant differences in pβcat staining location or intensity between primary and metastatic melanomas, suggesting that pβcat may have limited diagnostic or prognostic utility in melanoma. However, the high expression in dividing cells suggests promise as an immunotherapeutic target.
X-ray Spectral Imaging Program: XSIP
Authors: Qi Peng , Samadi Nazanin , Chapman Dean
Published: September 2020

Spectral K-edge subtraction imaging and wide-field energy-dispersive X-ray absorption spectroscopy imaging are novel, related, synchrotron imaging techniques for element absorption contrast imaging and element speciation imaging, respectively. These two techniques serve different goals but share the same X-ray optics principles with a bent Laue type monochromator and the same data processing algorithms. As there is a growing interest to implement these novel techniques in synchrotron facilities, Python-based software has been developed to automate the data processing procedures for both techniques. In this paper, the concept of the essential data processing algorithms are explained, the workflow of the software is described, and the main features and some related utilities are introduced.
Volatility Smile Surface for Levy Option Pricing Model
Authors: Lee Jun Hui , Chang Kook Hyun
Published: September 2020

This paper discusses theoretical extensions of the implied volatility method of Dupire (1994) when the stock prices follow the Geometric Levy process. For the extensions of Kolmogorov forward equation for Levy process, this paper uses adjoint operator in L² spaces. This paper obtains similar results of Dupire (1994) and Andersen and Andreasan (2001). However, our results can be applied to more general semi-martingale processes such as well-known VG (Variance Gamma) model and NIG (Normal Inverse Gaussian) model with diffusion processes. This paper also applies the approach to the case of stochastic time changed Levy process, which generates the stochastic volatility models.
The KOSPI200 Index Option Trading Behavior and Performance of Individual Investors
Authors: Chung Jay M. , Kim Jae Keun
Published: September 2020

We examine the argument of the Financial Supervisory Service that the behavior of the Individual Investors to buy an out-of-the-money option is excessively speculative. The FSS reported that the individual investors incurred huge losses in the trading of KOSPI200 index options for the years 2002 and 2003. But since the sample period is relatively short, the argument does not seem fully convincing. Using a longer period data from July 1997 to December 2003, we reconfirm the huge losses of the Individual investors and also find that a tendency of individual investors losing money in association with option trading perSisted during the longer period. The individual investors chose out-of-the money options with short time to maturity, that are cheap and thus are expected to make huge profits with very low probabilities. Finally, we tind that out-ot-the money options with short time to maturity turn out to be in general priced higher than what the Korea Stock Exchange model suggests.

The practice of purchasing out-of-the-money options for the reason of cheap prices and huge profit possibilities can be regarded as being excessively speculative. Due to overpricing, the individual investors persistently incurred some losses.
Investigation for Synthetic Collateralized Debt Obligation
Authors: Kim Mi Ae
Published: September 2020

Recently, domestic market participants have a growing interest in synthetic Collateralized Debt Obligation (CDO) as a security to reduce credit risk and create new profit. Therefore, the valuation method and hedging strategy for synthetic CDO become an important issue. However, there is no won-denominated credit default swap transactions, which are essential for activating synthetic CDO transaction‘ In addition, there is no transparent market information for the default probability, asset correlation, and recovery rate, which are critical variables determining the price of synthetic CDO.

This study first investigates the method of estimating the default probability, asset correlation coefficient, and recovery rate. Next, using five synthetiC CDO pricing models‘ widely used OFGC (One-Factor Non-Gaussian Copula) model. OFNGC (One-Factor Non-Gaussian Copula) model such as OFDTC (One-Factor Double T-distribution Copula) model of Hull and White (2004) or NIGC (Normal Inverse Gaussian Copula) model of Kalemanova et al.(2005), SC<Stochastic Correlation) model of Burtschell et al.(2005), and FL (Forward Loss) model of Bennani (2005), I Investigate and compare three points: 1) appropriateness for portfolio loss distribution, 2) explanation for standardized tranche spread, 3) sensitivity for delta-neutral hedging strategy. To compare pricing models, parameter estimation for each model is preceded by using the term structure of iTraxx Europe index spread and the tranch spreads with different maturities and exercise prices Remarkable results of this study are as follows. First, the probability for loss interval determining mezzanine tranche spread is lower in all models except SC model than OFGC model. This result shows that all mαdels except SC model in some degree solve the implied correlation smile phenomenon, where the correlation coefficient of mezzanine tranche must be lower than other tranches when OFGC model is used. Second, in explaining standardized tranche spread, NIGC model is the best among various models with respect to relative error. When OFGC model is compared with OFDTC model, OFOTC model is better than OFGC model in explaining 5-year tranche spreads. But for 7-year or 10-year tranches, OFDTC model is better with respect to absolute error while OFGC model is better with respect to relative error. Third, the sensitivity sign of senior tranctle spread with respect to asset correlation is sometime negative in NIG model while it is positive in other models. This result implies that a long position may be taken by the issuers of synthet.ic COO as a correlation delta-neutral hedging strategy when OFGC model is used, while a short position may be taken when NIGC model is used.
Sidecar Performance: Evidence from the Korean Stock Market
Authors: Park Jong Won , Eom Yun Sung , Chang Uk
Published: September 2020

In the paper, the effects of sidecar on the Korean stock market are considered. Throughout the study, we could reach the following conclusions. Firstly, the analysis of return dynamics illustrates that there are no price reversals for all sample groups but price continuations after the event. Secondly, the analysis of volatility and liquidity shows that there are some differences in the effects of sidecar on market volatility and liquidity according to the sample periods‘ however, in the post period of widening of the sidecar trigger levels, the mechanism couldn’t play any role of stabilizing the market volatility and resolving the increased order imbalance around the event. From these results, we could infer that sidecar delays the normal price discovery process and undermine the market liquidity. Also, we suggest that the increased market efficiency of Korea stock market after the financial crisis in 1997, especially deregulation in securities markets, can be a good additional factor for explaining the diffrences in the role of sidecar between sample periods.
The Estimation of Pricing Kernel of KOSPI 200 Options Under Stochastic Volatility
Authors: Han Sang Il , Yun Chang Hyun
Published: September 2020

In this paper we make an analysis of KOSPI 200 index options listed in Korea Stock and Futures Exchange whose trading volume is world best these days. We adopt the stochastic volatility model suggested by Heston (1993) for the dynamics of the underlying asset and use EMM to estimate the parameters of option pricing kernel. The SNP distribution of the implied volatility contains AR (2) and ARCH effects, and the skewness of the distribution is much higher than normal distribution. The distribution has thinner left tail and fatter right tail than normal distribution, which is opposite to the case of S&P 500 options market. The result of estimation shows that Implied volatility series of KOSPI 200 options have weak mean reverting property and are almost nonstationary. The correlation coefficient between the implied volatility and returns is estimated to have negligible negative number. These features are also opposite to the case of S&P 500 options market where implied volatility is reported to have strong mean reversion, and the correlation between the implied VIatilIty and retturns is reported to have large negative number.
A Research on Enhancing Forecasting Power for the Realized Volatility of KOSPI200
Authors: Yoo Shiyong , Koh Jung Yang
Published: September 2020

This paper tried to find out whether the information from foreign capital markets can improve the forecasting power for the realized volatility of KOSPI200 index. The realized volatility is estimated by using both daily return series and 5 minutes intraday data of KOSPI200. The volatilities of S&P100 return series and Won/Dollar exchange rate are considered as the information from foreign capital markets, and the volatility of Korean domestic interest rate is introduced as an additional variable to improve the forecasting power for the realized volatility of KOSPI200 returns. It turns out that those additional variables are statistically significant to improve the forecasting power for the realized volatility of KOSPI200.
Latent Factor Analysis of KOSDAQ Markets
Authors: Chang Kook-Hyun , Kim Myung-Jig
Published: September 2020

This paper tries to estimate multivariate latent factor model with jump in order to find common factor and jump risk of KOSDAQ markets. Using five major daily KOSDAQ indexes such as construction, wholesale, transportation, finance, and IT/SW/SVC from January 2 2003 to August 29 2008, this study finds the evidence of significant systematic jump risk in addition to industry-specific idiosyncratic risk. According to the main estimated results of this paper, jump risk comes every 31 trading days in KOSDAQ markets and approximately twenty percent of the common factor of the KOSDAQ market can be explained by the KOSPI market risk.
Covered Interest Rate Arbitrage Trading and Negative Spreads of Interest rate Swap in Korea
Authors: Won Seungyeon
Published: September 2020

This paper empirically shows that the long-term persistence of negative swap spreads, which was unique phenomenon only in Korean interest rate swap market, could be caused by the covered interest rate arbitrage trading by foreign investors in Korean market. It concretely shows the fixed rates of currency swap, whose decreases expand the incentive for arbitrage trading by foreign investors, to positively influence the interest rate swap spreads. The empirical results suggests that the foreign factors might make more effect on the interest rate swap market than the spot bond market, resulting in the negative interest rate swap spreads. The results implies that, the asset pricing for interest rate swap needs to consider the foreign factors under the circumstances of open capital market.
Over-Implied Models from CO2 Emission Allowance Futures Option Market
Authors: Kim Da Hea , Roh Tai-Yong , Byun Suk Joon , Hyun Jung Soon
Published: September 2020

This study examines the empirical performance of emission allowance option pricing models, concentrating on the EU-ETS markets. For option pricing, we use parameters estimated from option market data whereas few papers in the extant literature use parameters from underlying asset data. As results, it is shown that the most appropriate is the one-factor model in which the EUA logarithmic spot prices follow the mean-reverting process of Ornstein-Uhlenbeck type. Also, the addition of jumps is not shown to make any significant improvement in the model performance. These results are quite striking in the sense that existing papers report the addition of jumps is necessary to improve option pricing on the EU-ETS markets. In sum, this paper is meaningful in the sense that it extends the growing empirical literature on the behavior of emission allowance spot prices
Realized Skewness and the Return Predictability
Authors: Sim Myounghwa
Published: September 2020

We explore the cross-section of realized variance, skewness, and kurtosis for stock returns obtained from intraday data. We investigate the properties of the realized higher moments, and more importantly, examine relations between the realized moments and subsequent stock returns. We find evidence of a negative relation between realized skewness and next week’s returns. A strategy buying stocks in the lowest realized skewness quintile and selling stocks in the highest realized skewness quintile earns 0.79 percent per week a risk-adjusted basis. Our results on the realized skewness are robust to controls for various firm characteristics such as size and book-to-market. Little evidence exists that either the realized volatility or the realized kurtosis is significantly related to next week’s returns.
A Study on the Effect of Geographic Diversification of Firms on Hedging Activity Using Derivatives
Authors: Seok Sang Ik , Kim Tae Hyun , Cho Hoon , Kim Tae Joong
Published: September 2020

This paper examines the effect of fund manager replacement on investment performances of mutual funds. In managerial labor market of mutual fund industries with information asymmetry about the type and action of a fund manager, separating compensation may not be achievable due to imperfect evaluation of performances of fund managers. This paper extends contract theory to model the situations where a mutual fund offers pooling compensation contract to a fund manager based on his reputation. Under these environments, the fund manager has an economic incentive to acquire private benefit by manipulating performances and then to turn over to other mutual fund. Fund manager’s replacement is an aspect of adverse selection in the managerial labor market of fund industries. That is, a fund manager with low ability can select and manipulate unsuccessful investment portfolio generating loss to fund while he turns over to hide himself in the reputation under pooling contract mechanism. The empirical analysis of this paper provides the significant evidence that, differently from those of mutual funds of which managers stay in the same mutual funds, the fund performances drop after the fund managers turn over to other mutual funds. These empirical evidences support the theoretical prediction that the fund managers have incentive to manipulate short-term performances to maintain reputation for acquiring favorable compensation contracts.
On the Incompleteness of Korean Stock Index Options Market
Authors: Hyun Jung Soon , Rhee Byung Kun
Published: September 2020

When the Black-Scholes assumptions hold market is instantaneously complete and options are redundant securities. This paper tests whether options are needed for spanning of the pricing kernel in addition to the risk-free bond and underlying asset in Korean stock index options market. Using Hansen's GMM estimation method, we find that pricing kernel cannot be spanned with the risk-free bond and underlying asset. Options are needed for spanning to incorporate the additional risk factor. This result is consistent with previous results using American options market data.
An Empirical Analysis of the Arbitrage Opportunities in the KOSPI200 Futures and Options Markets
Authors: Bae Kee Hong , Chang Su Jae , Cho Jin Wan
Published: September 2020

We investigate the frequency of arbitrage opportunities and the size of their profits in the options and futures markets of KOSPI200 index. A thread of existing studies shows that these opportunities arise frequently, albeit the frequency is decreasing as the market matures. These studies, however, use transaction data in their analysis. Using the transaction data tends to overestimate both the frequency and the size of arbitrage gains, since it ignores the transactions cost imbedded in the bid-ask spread. In this study, we use the quote data to correctly reflect the transactions cost in executing the trades to take advantage of an arbitrage opportunity. By using the data spanning the period from Sep. 3, 2001 to Mar. 29. 2002, we show that both the frequency and size of arbitrage gains are much smaller than those when transaction data are used instead of Quote data. We also find that the Individual traders are the primary source that provide the arbitrage opportunities.
Arbitrage Profitability of Box Spreads in the KOSPI200 Options Market
Authors: Lee Jae Ha , Hahn Deok Hee
Published: September 2020

This study explores the arbitrage profitability of box spread strategies to test the KOSPI200 options market efficiency. using minute-by-minute data for the December 2003 - June 2004 period. The sample consists of 39.445 and 38.318 observations for small discrepancy and large discrepancy in exercise prices. respectively.

In the case of credit box spreads, there were 681 (2%) and 2.293 (6%) arbitrage observations for small and large discrepancies, while debit box spreads showed 831 (2%) and 3.098 (8%) observations for small and large discrepancies. In general, mean profit and median profit were different, and the arbitrage profit varied over time. The time to option expiration did not impact the arbitrage profit.

Also, the arbitrage profit of box spreads was significantly higher on Fridays for large discrepancy, and it varied across weekdays except the case of small-discrepancy debit box spread. Both arbitrage opportunities and profits substantially decreased as execution time increased. Our overall results suggest that the KOSPI200 options market has been efficient.
The Profitability of Technical Trading Rules in the KOSPI200 Futures Market
Authors: Park Cheol Ho
Published: September 2020

This article investigates the profitability of technical trading rules in the KOSPI200 futures market from 1997 through 2006 after accounting for transaction costs, risk. and data-snooping problems. To effectively mitigate data - snooping problems resulted from survivorship bias, we largely expand the full set of technical trading rules handled in the previous literature and measure statistical significance of technical trading performance using White’s (2000) Bootstrap Reality Check (BRC) methodology and Hansen’s (2005) Superior Predictive Ability (SPA) test that can take account of interdependency across individual technical trading rules.

The results indicate that under the net return criterion the best trading rule generates the highest mean net return of about 32% per annum during the sample period but the trading return is statistically insignificant when the effect of data-snooping is considered. Similar results are found under the Sharpe ratio criterion. These findings suggest that substantial technical trading profits may be obtained due to chance rather than the Inherent predictability of technical trading rules.
According to Time-moneyness in Option Market on Stock Price Volatility
Authors: Ohk Ki Yool , Jang Woo Ae
Published: September 2020

The purpose of this study is to examine the impact of the trade-activities in option market on stock market volatility by using KOSPI 200 daily data. First. we divided the option Volume from open interest. then classify the unexpected volume from expected volume to group the trade-activities In option market according to Investor's type. The result of test find that the unexpected volume of call option and the stock volatility have positive relationship. while one of put option and the stock volatility do not have statistically significant relation.

Then. we also divide the option volume Into the classified option volume according to time-maturity. We expect that the informed trader and uninformed trader trade the classified option differently. As a result. in the case of the call ootlon. the trade-activity of the unexpected volume in deep in the money option and deep out 이 the money option has positive relation with the stock volatility. and the at the money option below a month to maturity has positive relation with the stock volatility. This result shows that the informed trader prefer deep in the money option. deep out of the money option and at the money option below a month to maturity among the various option series. But. In the case of put option, it is so hard to find the result of the Informed trader's behavior.
Spot Trading Volume Volatility, Futures Trading Volume Volatility, and the Volatility of Korean Stock Market
Authors: Chang Kook Hyun , Yoon Byung Jo
Published: September 2020

This paper tries to investigate whether the information contained in trading volume volatilities of spot and futures may be statistically useful in explaining the volatility of korean stock market. This paper uses both the component-jump model and the bivariate GJR-GARCH type BEKK model to estimate the trading volume volatilities of spot and futures from 1/2/2001 to 9/30/2010. By using the component-jump model, the volume volatility is decomposed into a permanent component and a transitory component. According to this study, the relative importance of permanent component to the transitory component contained in both trading volume volatilities of spot and futures has been more significant in explaining the volatility of the korean stock markets.
A Priching Model for Inflation-indexed Bonds
Authors: Kim Sang Su
Published: September 2020

This paper derives the theoretical price of nominal bonds and inflation-indexed bonds through extracting the factors, which are assumed that their stochastic property follows the standard O-U process, in the term structure of nominal interest rates and yields of inflation-indexed bonds by the Principal Component Analysis (PCA). In particular, through reflecting the complex structure of inflation-indexed bonds by accurately applying theoretical price, it brought differentiation from other literatures, and applied this pricing model to Japanese Government Inflation-indexed Bond (JGB) data. The empirical results of above model show that explanation of time series and cross section of Janpan's real and nominal interest rates were outstanding and was found that Fisher hypothesis was rejected in further
The Information Content of the Implied Volatility in OTC Individual Stock Options Market
Authors: Park Yuen Jung
Published: September 2020

This paper investigates the information content of implied volatilities inferred from individual stock options quoted over-the-counter (OTC). First, we examine whether the implied volatility has better explanatory power than historical volatility for forecasting future realized volatility of the underlying stock return. Next, we analyze the properties of volatility spreads, the difference between implied volatilities and realized volatilities. Using near-the-money options for 10 firms over the sample period from April 2005 to April 2010, we first demonstrate that the implied volatilities for most firms don’t have additional information beyond what are already contained in historical volatilities. However, the implied volatilities with some specific remaining maturities for two firms dominate historical volatilities in explaining the future realized volatilities. Second, we find that during the period before global financial crisis, the implied volatilities are systematically lower than the future realized volatilities whereas this reversal disappears after the year 2008. This finding suggests that there’s a possibility of the risk loving behavior of the investors in OTC individual stock options market during the pre-global crisis period. Finally, through the comparative analysis of the KOSPI200 index options quoted OTC over the same sample period, we conclude that the OTC individual stock options market has distinctive characteristics like the KRW/USD OTC currency options market.
Jump Risk and Heteroscedasticity of KOSPI200 Intra-day Returns
Authors: Hong Min-Goo , Chang Kook-Hyun
Published: September 2020

This study examines whether KOSPI200 intra-day return has jump risk and heteroscedasticity and we compare the estimation result of intra-day return and that of daily return. The sample covers from January 2, 2004 to July 31, 2014. We use 30-minute intervals for measuring KOSPI200 intra-day return. It seems this study finds the importance of the consideration of the intra-day data in Korean Stock Market. While some of the parameters of the daily returns for the jump are not significant, but those of intra-day returns are significant over the sample period. Also, the intra-day volatility has shown U-shaped or reverse J-shaped curve. In particular the pattern of intra-day volatility seems to come from the jump risk, which is interpreted as the information inflow in the market.
A Simulation Study on Clustering Multivariate Time Series Using Kernel Variant Multi-Way Principal Component Analysis
Authors: Choi Hwanseok , Lee Cheolwoo , Jeon Jin Q
Published: September 2020

Conventional time series modeling may not satisfy the model validity for short-period time series data. In this study, we apply the Kernel Variant Multi-Way Principal Component Analysis (KMPCA) to cluster multivariate time series data which havemultiple dimensions with auto- and cross-correlations. We then check whether this method works well in clustering those data by employing simulation for generalization. Two simulation studies with two different mean structures with nine combinations of auto- and cross-correlations were conducted. The results showed that KMPCA cluster two different mean structure groups over 90% success rates with an appropriate kernel function. We also found that when the mean structures are the same, auto-correlation, the number of temporal points, and the kernel function parameter have the statistically significant effects on clustering performance. The second and third order interaction effects with each of those factors also have effects on clustering success rates. Among the effects of the main factors, the kernel function parameter is the most critical factor to consider for obtaining better performance. A similar error structure may obstruct the clustering performance: strong cross-correlation, weak auto-correlation, and a larger number of temporal points. The paper also discussed some limitations of the KMPCA model and suggested directions for future research that could improve the model.