• Title/Summary/Keyword: 지수가중이동평균법

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A numerical study on portfolio VaR forecasting based on conditional copula (조건부 코퓰라를 이용한 포트폴리오 위험 예측에 대한 실증 분석)

  • Kim, Eun-Young;Lee, Tae-Wook
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1065-1074
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    • 2011
  • During several decades, many researchers in the field of finance have studied Value at Risk (VaR) to measure the market risk. VaR indicates the worst loss over a target horizon such that there is a low, pre-specified probability that the actual loss will be larger (Jorion, 2006, p.106). In this paper, we compare conditional copula method with two conventional VaR forecasting methods based on simple moving average and exponentially weighted moving average for measuring the risk of the portfolio, consisting of two domestic stock indices. Through real data analysis, we conclude that the conditional copula method can improve the accuracy of portfolio VaR forecasting in the presence of high kurtosis and strong correlation in the data.

물가지수의 가중치 추정모형: 물가지수체계의 연관분석적 평가법(속)

  • 김준보
    • Journal of the Korean Statistical Society
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    • v.5 no.2
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    • pp.109-118
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    • 1976
  • 현행 일반적으로 쓰여지고 있는 물가지수 산식은 기준시점의 거래량(또는 거래금액)을 상품별 가중치(weight)로 삼는 가중총합방식(weighted aggregate formula, 또는 가중산술평균산식)으로서의 Laspeyres식이라 함은 주지하는 바와 같다. 그것이 상품별로 유통면의 중요성을 분명히 감안하여 있고, 비교시점의 가격변동만이 계산에 반영된다는 점에 있어서 물가지수로서의 실용성이 널리 인정되어 있는 산식이다. 그러나 Lasperyres식의 난점을 또한 많은 것이니 그 가운데 특히 가중치의 고정성과 관련하여 기준시점의 이동에 따른 전후 물가지수의 비연결성은 결정적 결함이라 할 수 있다. 여기에 이 식의 지수적 허구성이 흔히 논의되고, 이른바 Paasche check라 하여 수시로 조사한 거래량(또는 거래금액)에 의하여 물가지수의 가중치로 삼아서 전자를 검정하는 방법도 쓰여지는 형편이다. 필지는 일찌기(1973년) Laspeyres식의 상품별 가중치에 관한 객관적 평가법의 하나로서 산업(따라서 상품)의 연관분석적 수단에 의한 약간의 시안을 발표한 바 없지 않았다. 그것은 요약컨대 산업연관분석에 쓰이는 투입계수표를 중심삼아 한 상품가격이 다른 상품가격에 미치는 파급효과, 따라서 물가에 미치는 파급력을 계산하고, 나아가서 각 상품의 수요 및 공급함수를 도입하여 그들 계수를 추정함으로써 가중치의 객관화를 꾀해 본 것이 전고의 골자이다.

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Study on load forecasting for battergy energy storage system using Artificial Neural Network (인공신경회로망을 이용한 BESS의 부하 예측 기법에 관한 연구)

  • Park, Hyang-A;Kim, Seul-Ki;Cho, Kyeong-Hee;Kim, Eung-Sang
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.621-622
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    • 2015
  • 최근 늘어나는 전력 수요에 따라, 세계적으로 전력에너지 절감을 통한 수요자원 확보 및 활용을 위한 부하 예측의 중요성이 증가하고 있다. 본 논문에서는, 수요관리용 전지전력저장시스템을 효율적으로 운영하고 계획하는데 필수적인 부하예측의 정확성을 높이기 위하여 이동평균법, 지수가중이동평균법, 최소자승법, 인공신경망 방법을 적용하였다. 시계열 데이터인 부하 데이터를 분석하여 최대부하일, 근무일, 토요일, 공휴일로 분류하였고, 각각의 방법으로 예측한 부하를 적용시켜 전기요금 절감을 목표로 하는 전지전력저장시스템의 최적 충 방전 운전계획을 세웠으며, 이를 이용하여 산출된 전기요금과 실제 전기요금을 비교 분석하였다.

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The Study of Prediction Model of Gas Accidents Using Time Series Analysis (시계열 분석을 이용한 가스사고 발생 예측 연구)

  • Lee, Su-Kyung;Hur, Young-Taeg;Shin, Dong-Il;Song, Dong-Woo;Kim, Ki-Sung
    • Journal of the Korean Institute of Gas
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    • v.18 no.1
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    • pp.8-16
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    • 2014
  • In this study, the number of gas accidents prediction model was suggested by analyzing the gas accidents occurred in Korea. In order to predict the number of gas accidents, simple moving average method (3, 4, 5 period), weighted average method and exponential smoothing method were applied. Study results of the sum of mean-square error acquired by the models of moving average method for 4 periods and weighted moving average method showed the highest value of 44.4 and 43 respectively. By developing the number of gas accidents prediction model, it could be actively utilized for gas accident prevention activities.

Exponential Smoothing with an Adaptive Response to Random Level Changes (임의의 수준변화에 적절히 반응할 수 있는 지수이동가중평균법)

  • Jun, Duk-Bin
    • Journal of Korean Institute of Industrial Engineers
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    • v.16 no.2
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    • pp.129-134
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    • 1990
  • Exponential smoothing methods have enjoyed a long history of successful applications and have been used in forecasting for many years. However, it has been long known that one of the deficiencies of the method is an inability to respond quickly to interventions to interruptions, or to large changes in level of the underlying process. An exponential smoothing method adaptive to repeated random level changes is proposed using a change-detection statistic derived from a simple dynamic linear model. The results are compared with Trigg and Leach's and the exponential smoothing methods.

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The Study for Software Future Forecasting Failure Time Using Time Series Analysis. (시계열 분석을 이용한 소프트웨어 미래 고장 시간 예측에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.11 no.3
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    • pp.19-24
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    • 2011
  • Software failure time presented in the literature exhibit either constant monotonic increasing or monotonic decreasing, For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

Run-to-Run Process Control and the Analysis of Process Parameters using Design of Experiment in Surface Finishing (실험계획법에 의한 파라미터 분석과 Run to Run 제어를 이용한 폴리싱 공정 제어)

  • 안병운;박성준;이상조;윤종학
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.92-96
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    • 2004
  • In this paper, polishing method using bonded magnetic abrasive particle has been applied to the micro mold polishing. Through process control using the Run-to-Run control, it tried to form the surface roughness In order to grasp the influence of the surface roughness which is reached by selection of control factor and the factor, a design of experiment was been processed. The study is processed with a purpose of to embody and to maintain the surface roughness of nano scale by the basis of an influence between a control factor and the factors which has been selected in this way. As a result, the result of the process control converged at a target value of surface roughness Ra 10nm and Rmax 50nm

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A Study of Digital filter for context-awareness using multi-sensor built in the smart-clothes (멀티센서 기반 스마트의류에서 상황인지를 위한 디지털필터연구)

  • Jeon, Byeong-chan;Park, Hyun-moon;Park, Won-Ki;Lee, Sung-chul
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.911-913
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    • 2013
  • The user's context awareness is important to the reliability of sensors data. The sensor data is constantly change to external temp, internal& external environment and vibration. This noise environment is affecting that the data collected information from sensors. Of course this method of digital filter and inference algorithm specifically request for the use of ripple noise and action inference. In this paper, experiment was a comparison of the KF(Kalman Filter) and WMAF(Weight Moving Average Filter) for noise decrease and distortion prevention according to user behavior. And, we compared the EWDF(Extended Weight Dual Filter) with several filer. In an experiment, in contrast to other filter, the proposed filter is robust in a noise-environment.

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Optimal portfolio and VaR of KOSPI200 using One-factor model (원-팩터 모형을 이용한 KOSPI200지수 구성종목의 최적 포트폴리오 구성 및 VaR 측정)

  • Ko, Kwang Yee;Son, Young Sook
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.323-334
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    • 2015
  • he current VaR model based on the J.P. Morgan's RiskMetrics structurally can not reflect the future economic situation. In this study, we propose a One-factor model resulting from the Wiener stochastic process decomposed into a systematic risk factor and an idiosyncratic risk factor. Therefore, we are able to perform a preemptive risk management by means of reflecting the predicted common risk factors in the model. Stocks in the portfolio are satisfied with the independence to each other because the common factors are fixed by the predicted value. Therefore, we can easily determine the investment in each stock to minimize the variance of the portfolio. In addition, the portfolio VaR is decomposed into the sum of the individual VaR. So we can effectively implement the constitution of the portfolio to meet the target maximum losses.

Regional frequency analysis using spatial data extension method : I. An empirical investigation of regional flood frequency analysis (공간확장자료를 이용한 지역빈도분석 : I. 지역홍수빈도분석의 실증적 검토)

  • Kim, Nam Won;Lee, Jeong Eun;Lee, Jeongwoo;Jung, Yong
    • Journal of Korea Water Resources Association
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    • v.49 no.5
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    • pp.439-450
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    • 2016
  • For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.