• Journal of Korean Society of Forest Science
• /
• v.105 no.1
• /
• pp.149-156
• /
• 2016

Forest museums can be defined as facilities for the collection, exhibition, and education of the forest or forest related artifacts or data. This study was performed to measure the educational value of Gyeongnam state forest museum's forest and its environment. The tool used was the Contingent Valuation Methods (CVM) which is well known as a value estimation tool of environmental goods. The study for the value estimation is performed from April, 2014 to October of the same year through selection of the subject, decision of proposed price, and orientation of the survey staffs and total of 386 surveys were used in analysis. The value estimation tool used the DBDC logit model and the input parameters were number of visit (time), degree of environmental education (contri), the environment conservation effort of the respondent (execu), the education level of the respondent (edu), and income of the respondent (inc) and trimmed mean (WTPtruncated) was used. The estimated value of flora and environment education per each person per visit is 23,338 won. When applied to the average annual visitors deducted from 2010 to 2014, which is 430,000 per year, the environmental value that Gyeongnam state forest museum is providing to visitors each year is about 10 billion won. The result of this study is significant to propose the value of forest education and environment that the forest museum is offering to the visitors in the current currency. This is an evidence to directly determine the value of the forest museum and therefore proposing an opportunity change the recognition toward the forest and environment education.

• Korean Journal of Environment and Ecology
• /
• v.30 no.2
• /
• pp.253-260
• /
• 2016

This research aimed to quantitatively measure the environmental values of Taebaeksan, Naksan, and Gyeongpo provincial parks located in Gangwon-do. The research was based on the CVM technique which estimates the economic values for all kinds of ecosystem. Also, the estimated value of environment goods can suggest the magnitude of additional utility other than the cost people pay when they visit the provincial parks. Such result can be used as basic data in addition to information on natural ecology or cultural landscape to decide whether the park should be promoted as a national park. The questionnaires-collected from Taebaeksan(180 copies), Naksan(179 copies), and Gyeongpo(180 copies) provincial parks were used to measure the environmental value of each provincial park. Variables that affect the response of 'yes(Y)' or 'no(N)' to the cost suggestion for the economic valuation of environment are estimated under the catagories of environment conservation status (env.), degree of park management (manage.), environmental conservation effort, education (edu.), and income (inc.) of the respondents (execu.), pertaining to the 3 provincial parks in Gangwon-do. The value of natural environment to 1 visitor to the 3 Gangwon provincial parks was estimated by the Logit method that Hanemann proposed using the average of inserted variables. The results showed that the additional environmental value that 1 visitor can gain is 44,060 won for Taebaeksan Provincial Park, 41,191 won for Naksan, and 41,844 won for the Gyeongpo Provincial Park. Taebaeksan Provincial Park's environmental value is estimated at the highest as the respondents judge that its natural environment is well preserved and the facilities are managed well.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.1
• /
• pp.1-10
• /
• 2010

A regional climate model (RCM) can be a powerful tool to enhance spatial resolution of climate and weather information (IPCC, 2001). In this study we conducted dynamical downscaling using Weather Research and Forecasting Model (WRF) as a RCM in order to obtain high resolution regional agroclimate indices over the Korean Peninsula. For the purpose of obtaining detailed high resolution agroclimate indices, we first reproduced regional weather for the period of March to June, 2002-2008 with dynamic downscaling method under given lateral boundary conditions from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data. Normally, numerical model results have shown biases against observational results due to the uncertainties in the modelis initial conditions, physical parameterizations and our physical understanding on nature. Hence in this study, by employing a statistical method, the systematic bias in the modelis results was estimated and corrected for better reproduction of climate on high resolution. As a result of the correction, the systematic bias of the model was properly corrected and the overall spatial patterns in the simulation were well reproduced, resulting in more fine-resolution climatic structures. Based on these results, the fine-resolution agro-climate indices were estimated and presented. Compared with the indices derived from observation, the simulated indices reproduced the major and detailed spatial distributions. Our research shows a possibility to simulate regional climate on high resolution and agro-climate indices by using a proper downscaling method with a dynamical weather forecast model and a statistical correction method to minimize the model bias.

• The Korean Journal of Financial Management
• /
• v.8 no.1
• /
• pp.179-197
• /
• 1991

선도환의 가격을 결정하는 접근방법에는 2차자산(derivative assets)이라는 선도계약의 기본특성에 기초한 재정거래(arbitrage)에 의한 방법이 가장 많이 이용되고 있다. 재정거래방식에는 선도환과 현물외환가격간의 상호관련성에 의하여 선도환가격을 이자율평가설(covered interest rate parity : CIRP), 즉 현물가격과 양국간의 이자율차이의 합으로 표시하고 있다. 특히 현물가격과 이자율은 모두 현재시점에서 의사결정자에게 알려져 있기때문에 선도환가격은 확실성하에서 결정되어 미래에 대한 예측이나 투자자의 위험회피도와는 관계없이 결정된다는 것이 특징이다. 이자율평가설에 관한 많은 실증연구는 거래 비용을 고려한 경우 현실적으로 적절하다고 보고 있다(Frenkel and Levich ; 1975, 1977). 다른 방법으로는 선도환의 미래예측기능에만 촛점을 맞추어 가격결정을 하는 투기, 예측접근방법(speculative efficiency approach : 이하에서는 SEA라 함)이 있다. 이 방법 중에서 가장 단순한 형태로 표시된 가설, 즉 '선도환가격은 미래기대현물가격과 같다'는 가설은 대부분의 실증분석에서 기각되고 있다. 이에 따라 SEA에서는 선도환가격이 미래에 대한 기대치뿐만 아니라 위험프리미엄까지 함께 포함하고 있다는 새로운 가설을 설정하고 이에 대한 실증분석을 진행한다. 이 가설은 이론적 모형에서 출발한 것이 아니기 때문에, 특히 기대치와 위험프레미엄 모두가 측정 불가능하다는 점으로 인하여 실증분석상 많은 어려움을 겪게 된다. 이러한 어려움을 피하기 위하여 많은 연구에서는 이자율평가설을 이용하여 선도환가격에 포함된 위험프레미엄에 대해 추론 내지 그 행태를 설명하려고 한다. 이자율평가설을 이용하여 분석모형을 설정하고 실증분석을 하는 것은 몇가지 근본적인 문제점을 내포하고 있다. 먼저, 앞서 지적한 바와 같이 이자율평가설을 가정한다는 것은 SEA에서 주된 관심이 되는 미래예측이나 위험프레미엄과는 관계없이 선도가격이 결정 된다는 것을 의미한다. 따라서 이자율평가설을 가정하여 설정된 분석모형은 선도환시장의 효율성이나 균형가격결정에 대한 시사점을 제공할 수 없다는 것을 의미한다. 즉, 가정한 시장효율성을 실증분석을 통하여 다시 검증하려는 것과 같다. 이러한 개념적 차원에서의 문제점 이외에도 실증분석에서의 추정상의 문제점 또한 존재한다. 대부분의 연구들이 현물자산의 균형가격결정모형에 이자율평가설을 추가로 결합하기 때문에 이러한 방법으로 설정한 분석모형은 그 기초가 되는 현물가격모형과는 달리 자의적 조작이 가능한 형태로 나타나며 이를 이용한 모수의 추정은 불필요한 편기(bias)를 가지게 된다. 본 연구에서는 이러한 실증분석상의 편기에 관한 문제점이 명확하고 구체적으로 나타나는 Mark(1985)의 실증연구를 재분석하고 실증자료를 통하여 위험회피도의 추정치에 편기가 발생하는 근본원인이 이자율평가설을 부적절하게 사용하는데 있다는 것을 확인 하고자 한다. 실증분석결과는 본문의 <표 1>에 제시되어 있으며 그 내용을 간략하게 요약하면 다음과 같다. (A) 실증분석모형 : 본 연구에서는 다기간 자산가격결정모형중에서 대표적인 Lucas (1978)모형을 직접 사용한다. $$1={\beta}\;E_t[\frac{U'(C_{t+1})\;P_t\;s_{t+1}}{U'(C_t)\;P_{t+1}\;s_t}]$$ (2) $U'(c_t)$와 $P_t$는 t시점에서의 소비에 대한 한계효용과 소비재의 가격을, $s_t$와 $f_t$는 외환의 현물과 선도가격을, $E_t$와 ${\beta}$는 조건부 기대치와 시간할인계수를 나타낸다. Mark는 위의 식 (2)를 이자율평가설과 결합한 다음의 모형 (4)를 사용한다. $$0=E_t[\frac{U'(C_{t+1})\;P_t\;(s_{t+1}-f_t)}{U'(C_t)\;P_{t+1}\;s_t}]$$ (4) (B) 실증분석의 결과 위험회피계수 ${\gamma}$의 추정치 : Mark의 경우에는 ${\gamma}$의 추정치의 값이 0에서 50.38까지 매우 큰 폭의 변화를 보이고 있다. 특히 비내구성제품의 소비량과 선도프레미엄을 사용한 경우 ${\gamma}$의 추정치의 값은 17.51로 비정상적으로 높게 나타난다. 반면에 본 연구에서는 추정치가 1.3으로 주식시장자료를 사용한 다른 연구결과와 비슷한 수준이다. ${\gamma}$추정치의 정확도 : Mark에서는 추정치의 표준오차가 최소 15.65에서 최대 42.43으로 매우 높은 반면 본 연구에서는 0.3에서 0.5수준으로 상대적으로 매우 정확한 추정 결과를 보여주고 있다. 모형의 정확도 : 모형 (4)에 대한 적합도 검증은 시용된 도구변수(instrumental variables)의 종류에 따라 크게 차이가 난다. 시차변수(lagged variables)를 사용하지 않고 현재소비와 선도프레미엄만을 사용할 경우 모형 (4)는 2.8% 또는 2.3% 유의수준에서 기각되는 반면 모형 (2)는 5% 유의수준에서 기각되지 않는다. 위와같은 실증분석의 결과는 앞서 논의한 바와 같이 이자율평가설을 사용하여 균형자산가격 결정모형을 변형시킴으로써 불필요한 편기를 발생시킨다는 것을 명확하게 보여주는 것이다.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.9 no.2
• /
• pp.154-164
• /
• 1998

Medication is widely accepted as an effective method to reduce the problem of attention deficit, hyperactivity, impulsivity, resistance and violence of ADHD children. However, it does not provide us with the solution on the conflicting routinized behavioral patterns to gain a high level of self-control and acceptable behavior. As a way of replacing medication, this study applies the social skills training program for ADHD children and measures the level of improvement of social skills and the change of the behavioral patterns. The experiment is carried out on 16 children ranged from 6 to 13 years of age for 10 weeks. The patients are divided into three groups：a pure ADHD group, an ADHD group with conduct disorder, an ADHD group with mental retardation and other symptoms. The change of symptoms and the change of social skills are measured by the Child Behavior Checklist(CBCL), the ADD-H Comprehensive Teacher’s Rating Scale(ACTeRS) and the Social Skills Rating Scale(SSRS), and finally Mastson Evaluation of Social Skills for Youth(MESSY). Wilcoxon signed ranks test is used to evaluate the effect of the treatment, and Kruskal-Wallis test is also used to measure the change after the treatment in each of the three groups. In the ADHD group with conduct disorder, the examination of the effect of the treatment shows a significant reduction of violence in the area of behavior(p<.05), and a significant difference of activity and social skills in the area of social competent(p<.001). In the ADHD group with mental retardation and other symptoms, a significant rise of social skills is found in the area of social skills evaluation (p<.05). However, there is no significant difference of effect by the treatment among the three groups. In addition, the current examination shows that the social skills training program does not make a statistically significant contribution to the social skills of the ADHD children. On the other hand, the training helps some children, when it is suitable for the characteristics and accompanying symptoms of the children：it reduces the level of violence in the ADHD group with conduct disorder, and it raises the social skills in the ADHD group with mental retardation. In other words, the social skills training program will reduce the conduct disorder and helps peer relation for ADHD children.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.4
• /
• pp.256-266
• /
• 2022

Empirical models including the Angstrom-Prescott (AP) model have been used to estimate solar radiation at sites, which would support a wide use of crop models. The objective of this study was to estimate two sets of solar radiation estimates using the AP coefficients derived for climate zone (AP_Frere) and specific site (AP_Choi), respectively. The daily solar radiation was estimated at 18 sites in Korea where long-term measurements of solar radiation were available. In the present study, daily solar radiation and sunshine duration were collected for the period from 2012 to 2021. Daily weather data including maximum and minimum temperatures and rainfall were also obtained to prepare input data to a process-based crop model, CERES-Rice model included in Decision Support System for Agrotechnology Transfer (DSSAT). It was found that the daily estimates of solar radiation using the climate zone specific coefficient, SFrere, had significantly less error than those using site-specific coefficients S_Choi (p<0.05). The cumulative values of S_Frere for the period from march to September also had less error at 55% of study sites than those of S_Choi. Still, the use of S_Frere and S_Choi as inputs to the CERES-Rice model resulted in slight differences between the outcomes of crop growth simulations, which had no significant difference between these outputs. These results suggested that the AP coefficients for the temperate climate zone would be preferable for the estimation of solar radiation. This merits further evaluation studies to compare the AP model with other sophisticated approaches such as models based on satellite data.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.135-149
• /
• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.