Consistent estimator of ex-post covariation of discretely observed diffusion processes and its application to high frequency financial time series

First chapter of my thesis reviews recent developments in the theory and practice of volatility measurement. We review the basic theoretical framework and describe the main approaches to volatility measurement in continuous time. In this literature the central parameter of interest is the integrated variance and its multivariate counterpart. We describe the measurement of these parameters under ideal circumstances and when the data are subject to measurement error, microstructure issues. We also describe some common applications of this literature. In the second chapter, we propose a new estimator of multivariate ex-post volatility that is robust to microstructure noise and asynchronous data timing. The method is based on Fourier domain techniques. The advantage of this method is that it does not require an explicit time alignment, unlike existing methods in the literature. We derive the large sample properties of our estimator under general assumptions allowing for the number of sample points for different assets to be of different order of magnitude. We show in extensive simulations that our method outperforms the time domain estimator especially when two assets are traded very asynchronously and with different liquidity. In the third chapter, we propose to model high frequency price series by a timedeformed L´evy process. The deformation function is modeled by a piecewise linear function of a physical time with a slope depending on the marks associated with intra-day transaction data. The performance of a quasi-MLE and an estimator based on a permutation-like statistic is examined in extensive simulations. We also consider estimating the deformation function nonparametrically by pulling together many time series. We show that financial returns spaced by equal elapse of estimated deformed time are homogenous. We propose an order execution strategy using the fitted deformation tim

Estimating the quadratic covariation matrix for an asynchronously observed continuous time signal masked by additive noise

We propose a new estimator of multivariate ex-post volatility that is robust to microstructure noise and asynchronous data timing. The method is based on Fourier domain techniques, which have been widely used in discrete time series analysis. The advantage of this method is that it does not require an explicit time alignment, unlike existing methods in the literature. We derive the large sample properties of our estimator under general assumptions allowing for the number of sample points for different assets to be of different order of magnitude. The by-product of our Fourier domain based estimator is that we have a consistent estimator of the instantaneous co-volatility even under the presence of microstructure noise. We show in extensive simulations that our method outperforms the time domain estimator especially when two assets are traded very asynchronously and with different liquidity and when estimating the high dimensional integrated covariance matrix

Optimization of Li1.17[Mn0.6Ni0.2Co0.2]0.83O2 Cathode Materials for Li-ion batteries

Department of Energy Engineering(Battery Science and Technology)In the face of growing green energy needs and pressure on the environment, lithium ion batteries have been paid lots of attention. Recently, with growing needs of energy have been significantly increased due to electric vehicles and energy storage system, bigger scale batteries are getting more important than before. Lithium rich materials with higher reversible capacity than 240 mAh/g is regarded the most encouraging cathode material to solve low energy density which is one of the biggest limits of commercialized LIBs cathode materials. However, there have been several problems needed to overcome for commercialization of lithium rich cathode materials. First of all, to achieve high tap density, preparation of powder is important. Co-precipitation method has been known as the best way to produce uniform distribution of powders with spherical shape which are key factors to have a high tap density, but this method is really hard to optimize because there are too many factors to optimize co-precipitation condition such as pH, the amount of chelating agent and stirring speed. Also, lithium rich cathode materials have several drawbacks on electrochemical properties. For example, this cathode material has low initial coulombic efficiency, which is the main problem of full-cell operation, compared to other cathode materials due to the activation process of Li2MnO3 component. Herein, to solve these problems of lithium rich cathode materials, we suggest the optimized co-precipitation condition under oxygen inert atmosphere for high tap density, and blending lithium rich with nickel rich cathode materials to overcome the drawbacks of electrochemical properties.ope

mTOR signalling and cellular metabolism are mutual determinants in cancer

Oncogenic signalling and metabolic alterations are interrelated in cancer cells. mTOR, which is frequently activated in cancer, controls cell growth and metabolism. mTOR signalling regulates amino acid, glucose, nucleotide, fatty acid and lipid metabolism. Conversely, metabolic inputs, such as amino acids, activate mTOR. In this Review, we discuss how mTOR signalling rewires cancer cell metabolism and delineate how changes in metabolism, in turn, sustain mTOR signalling and tumorigenicity. Several drugs are being developed to perturb cancer cell metabolism. However, their efficacy as stand-alone therapies, similar to mTOR inhibitors, is limited. Here, we discuss how the interdependence of mTOR signalling and metabolism can be exploited for cancer therapy

A Comparison of Intensive Care Unit Mortality Prediction Models through the Use of Data Mining Techniques

OBJECTIVES: The intensive care environment generates a wealth of critical care data suited to developing a well-calibrated prediction tool. This study was done to develop an intensive care unit (ICU) mortality prediction model built on University of Kentucky Hospital (UKH)\u27s data and to assess whether the performance of various data mining techniques, such as the artificial neural network (ANN), support vector machine (SVM) and decision trees (DT), outperform the conventional logistic regression (LR) statistical model. METHODS: The models were built on ICU data collected regarding 38,474 admissions to the UKH between January 1998 and September 2007. The first 24 hours of the ICU admission data were used, including patient demographics, admission information, physiology data, chronic health items, and outcome information. RESULTS: Only 15 study variables were identified as significant for inclusion in the model development. The DT algorithm slightly outperformed (AUC, 0.892) the other data mining techniques, followed by the ANN (AUC, 0.874), and SVM (AUC, 0.876), compared to that of the APACHE III performance (AUC, 0.871). CONCLUSIONS: With fewer variables needed, the machine learning algorithms that we developed were proven to be as good as the conventional APACHE III prediction

Information communication technology accessibility and mental health for older adults during the coronavirus disease in South Korea

IntroductionAs society ages and the digital economy continues to develop, accessibility to information and communication technology (ICT) has emerged as a critical factor influencing the mental health of older adults. Particularly, in the aftermath of the COVID-19 pandemic, the need for non-face-to-face communication has significantly increased older adults’ reliance on ICT for accessibility. This transition from a self-motivated engagement to a more socially passive mode of interaction highlights the importance of creating a digitally inclusive aging society.MethodsThis empirical study used pooled cross-sectional data from the Digital Gap Survey conducted in South Korea in 2018 and 2020. It aimed to analyze the association between ICT accessibility and the mental health of older adults during the COVID-19 pandemic.ResultsA significant positive relationship was found between ICT and mental health among older adults in South Korea. However, this positive association weakened during the COVID-19 period. Furthermore, the analysis revealed heterogeneity among older adults by age, sex, and place of residence, with older females in their 70s living in rural areas experiencing the greatest weakening.DiscussionThese results highlight the need for tailored interventions and support mechanisms for specific demographic groups of older adults. We recommend that the South Korean government implement various policies to facilitate the post-COVID-19 digital landscape. These include initiatives such as ICT-related education programs, development of user-friendly e-government systems, and creation of social media platforms designed to accommodate the needs and preferences of older adults

Who Are Better Informed Before Analysts’ Forecast Changes?

Using Korean data, we investigate information asymmetry among investors before analysts change their stock recommendations. By comparing trading activities between individuals, institutions, and foreign investors, we find that there is information asymmetry before analysts change their recommendations. Institutional investors buy/sell the stock before recommendation upgrades/downgrades, but individuals and foreign investors do not anticipate the upcoming news. We also document that the trade imbalance of institutional investors are associated with stock returns upon the announcements of recommendation changes. This result indicates that institutions take advantage of their superior information around the recommendation changes.     

Understanding How People with Binge Eating Disorder and Bulimia Interact with Digital Food Content

A large body of research has focused on understanding how online content and disordered eating behaviors are associated. However, there is a lack of comprehensive studies investigating digital food content's influence on individuals with eating disorders. We conducted two rounds of studies (N=23 and 22, respectively) with individuals with binge eating disorder (BED) or bulimia nervosa (BN) to understand their motivations and practices of consuming digital food content. Our study reveals that individuals with BED and BN anticipate positive effects from food media to overcome their condition, but in practice, it often exacerbates their disorder. We also discovered that many individuals have experienced a cycle of quitting and returning to digital food content consumption. Based on these findings, we articulate design implications for digital food content and multimedia platforms to support vulnerable individuals in everyday online platform interactions.Comment: 28 pages, 6 figure

Application of optogenetic glial cells to neuron–glial communication

Optogenetic techniques combine optics and genetics to enable cell-specific targeting and precise spatiotemporal control of excitable cells, and they are increasingly being employed. One of the most significant advantages of the optogenetic approach is that it allows for the modulation of nearby cells or circuits with millisecond precision, enabling researchers to gain a better understanding of the complex nervous system. Furthermore, optogenetic neuron activation permits the regulation of information processing in the brain, including synaptic activity and transmission, and also promotes nerve structure development. However, the optimal conditions remain unclear, and further research is required to identify the types of cells that can most effectively and precisely control nerve function. Recent studies have described optogenetic glial manipulation for coordinating the reciprocal communication between neurons and glia. Optogenetically stimulated glial cells can modulate information processing in the central nervous system and provide structural support for nerve fibers in the peripheral nervous system. These advances promote the effective use of optogenetics, although further experiments are needed. This review describes the critical role of glial cells in the nervous system and reviews the optogenetic applications of several types of glial cells, as well as their significance in neuron–glia interactions. Together, it briefly discusses the therapeutic potential and feasibility of optogenetics

Measuring Habitual Arm Use Post-stroke With a Bilateral Time-Constrained Reaching Task

Background: Spontaneous use of the more-affected arm is a meaningful indicator of stroke recovery. The Bilateral Arm Reaching Test (BART) was previously developed to quantify arm use by measuring arm choice to targets projected over a horizontal hemi-workspace. In order to improve clinical validity, we constrained the available movement time, thereby promoting more spontaneous decision making when selecting between the more-affected and less affected arm during the BART.Methods: Twenty-two individuals with mild to moderate hemiparesis were tested with the time-based BART in three time-constraint conditions: no-time constraint, medium, and fast conditions. Arm use was measured across three sessions with a 2-week interval in a spontaneous choice block, in which participants were instructed to use either the more-affected or the less-affected arm to reach targets. We tested the effect of time-constraint condition on the more-affected arm use, external validity of the BART with the Actual Amount of Use Test (AAUT), and test-retest reliability across the three test sessions.Results: The fast condition in the time-based BART showed reduced use of the more-affected arm compared to the no-time constraint condition P < 0.0001) and the medium condition P = 0.0006; Tukey post hoc analysis after mixed-effect linear regression). In addition, the fast condition showed strong correlation with the AAUT r = 0.829, P < 0.001), and excellent test-retest reliability (ICC = 0.960, P < 0.0001).Conclusion: The revised BART with a time-restricted fast condition provides an objective, accurate, and repeatable measure of spontaneous arm use in individuals with chronic stroke hemiparesis