Some Observations for Portfolio Management Applications of Modern Machine Learning Methods

Jooyoung Park,Seongman Heo,Taehwan Kim,Jeongho Park,Jaein Kim,Kyungwook Park 한국지능시스템학회 2016 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.16 No.1

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users’ sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.

Some Observations for Portfolio Management Applications of Modern Machine Learning Methods

Park, Jooyoung,Heo, Seongman,Kim, Taehwan,Park, Jeongho,Kim, Jaein,Park, Kyungwook Korean Institute of Intelligent Systems 2016 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.16 No.1

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users' sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.

The Relationship between Delirium and Statin Use According to Disease Severity in Patients in the Intensive Care Unit

Jun Yong An(Jun Yong An),Jin Young Park(Jin Young Park),Jaehwa Cho(Jaehwa Cho),Hesun Erin Kim(Hesun Erin Kim),Jaesub Park(Jaesub Park),Jooyoung Oh(Jooyoung Oh) 대한정신약물학회 2023 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.21 No.1

Objective: The aim of this study was to investigate the association between the use of statins and the occurrence of delirium in a large cohort of patients in the intensive care unit (ICU), considering disease severity and statin properties. Methods: We obtained clinical and demographical information from 3,604 patients admitted to the ICU from January 2013 to April 2020. This included information on daily statin use and delirium state, as assessed by the Confusion Assessment Method for ICU. We used inverse probability of treatment weighting and categorized the patients into four groups based on the Acute Physiology and Chronic Health Evaluation II score (group 1: 0−10 - mild; group 2: 11−20 - mild to moderate; group 3: 21−30 - moderate to severe; group 4: > 30 - severe). We analyzed the association between the use of statin and the occurrence of delirium in each group, while taking into account the properties of statins. Results: Comparisons between statin and non-statin patient groups revealed that only in group 2, patients who were administered statin showed significantly higher occurrence of delirium (p = 0.004, odds ratio [OR] = 1.58) compared to the patients who did not receive statin. Regardless of whether statins were lipophilic (p = 0.036, OR = 1.47) or hydrophilic (p = 0.032, OR = 1.84), the occurrence of delirium was higher only in patients from group 2. Conclusion: The use of statins may be associated with the increases in the risk of delirium occurrence in patients with mild to moderate disease severity, irrespective of statin properties.

Physical and Optical Properties of SnO₂/ZnO Film Prepared by an RF Magnetron Sputtering Method

Park, Jooyoung,Lee, Ikjae,Kim, Jaeyong American Scientific Publishers 2016 Journal of Nanoscience and Nanotechnology Vol.16 No.3

<P>Al-, Ga-, and In-doped ZnO thin films are widely used in many technical applications, such as in solar cells and on transparent conducting oxides having high optical transmission and low resistivity values. We prepared SnO2-doped ZnO thin films on quartz substrates by using an RF magnetron sputtering method at a substrate temperature of 350 degrees C. The ratio of SnO2 to ZnO was varied from 0 to 5: 5 to investigate the effects of Sn on structure and physical properties of ZnO film. The samples were synthesized at a base pressure of 1.3x10(-4) Pa with a working pressure of 1.3 Pa and an RF power of 40 W under Ar atmosphere. The results of X-ray diffraction data revealed that pure ZnO films exhibit a strong (002) orientation and a polycrystalline wurzite hexagonal structure. However, as increasing the SnO2 concentration, ZnO transforms to an amorphous phase. The results of the Hall-effect-measurement system revealed that the resistivity values of the films increased as increasing the doping level of SnO2. The AFM data of morphology and microstructure showed that the grain size decreased with increasing SnO2 contents while the total area of grain the boundary increased. The average value of the transmittance of the films in the visible light range was 80 similar to 95% and was shifted toward to the shorter wavelengths of the absorption edges with increasing SnO2 contents.</P>

Development and Implication of a Korean Waste Input-Output Table

( Jooyoung Park ),( Hyungwoo Lim ),( Hye Sook Lim ),( Munsol Ju ) 한국폐기물자원순환학회 2022 ISSE 초록집 Vol.2022 No.-

Korea’s waste policy has focused mainly on managing direct waste generation from households, industries, and construction, putting less attention to indirect waste generation driven by final demands. This lack of attention to indirect waste flows may underestimate the impacts of inter-industry relationships and consumption behavioral changes, and therefore lead to missing opportunities for waste reduction. To understand the patterns of direct and indirect waste generation as well as waste management from the consumption perspective, we constructed the first waste input-output table for Korea and analyzed waste footprint of consumption. Korea’s various waste statistics allowed the construction of waste input-output table (WIO) that covers 33 industrial sectors and 69 waste types for the year 2019. Our preliminary results showed that the waste inducement effect was highest in the water supply and waste management sector and the lowest in the financial and insurance sector. Manufacturing sector contributed the most to the generation of industrial waste, particularly basic metals and non-metallic manufacturing, while service sectors contributed mainly to the generation of non-industrial waste. The share of non-combustible waste generation turned out to be considerably high across all sectors, imposing burdens on waste treatment. We will further analyze waste footprint of household consumption and discuss implications of WIO analysis on the waste reduction policy.

Modern Probabilistic Machine Learning and Control Methods for Portfolio Optimization

Park, Jooyoung,Lim, Jungdong,Lee, Wonbu,Ji, Seunghyun,Sung, Keehoon,Park, Kyungwook Korean Institute of Intelligent Systems 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.2

Many recent theoretical developments in the field of machine learning and control have rapidly expanded its relevance to a wide variety of applications. In particular, a variety of portfolio optimization problems have recently been considered as a promising application domain for machine learning and control methods. In highly uncertain and stochastic environments, portfolio optimization can be formulated as optimal decision-making problems, and for these types of problems, approaches based on probabilistic machine learning and control methods are particularly pertinent. In this paper, we consider probabilistic machine learning and control based solutions to a couple of portfolio optimization problems. Simulation results show that these solutions work well when applied to real financial market data.

A Modified Approach to Density-Induced Support Vector Data Description

Jooyoung Park,Daesung Kang 한국지능시스템학회 2007 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.7 No.1

The SVDD (support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. Recently, with the objective of generalizing the SVDD which treats all training data with equal importance, the so-called D-SVDD (density-induced support vector data description) was proposed incorporating the idea that the data in a higher density region are more significant than those in a lower density region. In this paper, we consider the problem of further improving the D-SVDD toward the use of a partial reference set for testing, and propose an LMI (linear matrix inequality)-based optimization approach to solve the improved version of the D-SVDD problems. Our approach utilizes a new class of density-induced distance measures based on the RSDE (reduced set density estimator) along with the LMI-based mathematical formulation in the form of the SDP (semi-definite programming) problems, which can be efficiently solved by interior point methods. The validity of the proposed approach is illustrated via numerical experiments using real data sets.

An experimental investigation on relationship between PSFs and operator performances in the digital main control room

Park, Jooyoung,Lee, Daeil,Jung, Wondea,Kim, Jonghyun Elsevier 2017 Annals of nuclear energy Vol.101 No.-

<P><B>Abstract</B></P> <P>This study designs an experiment to investigate the relationship between performance shaping factors (PSFs) and operator performances. This study involves selecting three PSFs that are controllable in the experiments: (1) experience, (2) complexity, and (3) urgency. Six scenarios are developed to reflect the PSFs. The experiment involves the participation of licensed operators and the use of an APR1400 simulator. During the experiment, operator performances, such as completion time, error, secondary task, workload, and situation awareness, are measured and collected. The experimental result indicates that the operator’s experience is most effective on the overall performances. The task complexity influences the secondary tasks and situation awareness.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The relationship between performance shaping factors and operator performances are experimentally investigated. </LI> <LI> The experiment includes features of digital main control room. </LI> <LI> The result indicates that the operator’s experience level is the most effective on the performance. </LI> </UL> </P>

Modeling Safety-II based on unexpected reactor trips

Park, Jooyoung,Kim, Ji-tae,Lee, Sungheon,Kim, Jonghyun Elsevier 2018 Annals of nuclear energy Vol.115 No.-

<P><B>Abstract</B></P> <P>Safety-I is defined as a state where as few things as possible go wrong. Until now, the methods for analyzing the safety in nuclear power plants (NPPs), i.e., Probabilistic Safety Assessment and Deterministic Safety Analysis, have been developed from the perspective of Safety-I. However, focusing solely on Safety-I may miss opportunities to 1) learn from successes, and 2) observe how human adaptation contributes to successful outcomes, despite novel circumstances and resource limitations. In this light, a paradigm shift from ensuring that “as few things as possible go wrong (Safety-I)” to ensuring that “as many things as possible go right (Safety-II)” has been suggested. This study aimed to develop a model of Safety-II for unexpected situations in NPPs. Safety-II concentrates on the conditions in which as many things as possible go right. First, this study suggested and characterized a qualitative Safety-II model, which was modified from a resilience model developed by the Électricité de France (EDF). Second, event reports from unplanned reactor trips at Korean NPPs were analyzed based on the elements of this characterized Safety-II model as well as event severity. Third, a quantitative network model of Safety-II was developed by performing a correlation analysis. Finally, a feasibility analysis of Safety-I and Safety-II concepts for explaining event severity was performed. The result of this research suggests a new methodology for the safety assessment of unexpected reactor trips in NPPs, which could complement the conventional probabilistic safety assessments and deterministic safety analyses.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A quantitative network model of Safety-II was developed. </LI> <LI> Event reports from unplanned reactor trips at Korean NPPs were analyzed. </LI> <LI> A feasibility of Safety-I and Safety-II concepts was investigated. </LI> </UL> </P>

Physical Properties of Zinc-Tin-Oxide Thin Films Deposited on Sapphire Substrates by an Rf-Magnetron Sputtering Method

Park, Jooyoung,Lee, Ikjae,Kim, Jaeyong American Scientific Publishers 2017 Science Of Advanced Materials Vol.9 No.2