• Title/Summary/Keyword: 단순이동평균법

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ESD(Exponential Standard Deviation) Band centered at Exponential Moving Average (지수이동평균을 중심으로 하는 ESD밴드)

  • Lee, Jungyoun;Hwang, Sunmyung
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.115-125
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    • 2016
  • The Bollinger Band indicating the current price position in the recent price action range is obtained by adding/substracting the simple standard deviation (SSD) to/from the simple moving average (SMA). In this paper, we first compare the characteristics of the SMA and the exponential moving average (EMA) in the operator's point of view. A basic equation is obtained between the interval length N of the SMA operator and the weighting factor ${\rho}$ of the EMA operator, that makes the centers of the 1st order momentums of each operator impulse respoinse identical. For equivalent N and ${\rho}$, frequency response examples are obtained and compared by using the discrete time Fourier transform. Based on observation that the SMA operator reacts more excessively than the EMA operator, we propose a novel exponential standard deviation (ESD) band centered at the EMA and derive an auto recursive formula for the proposed ESD band. Practical examples for the ESD band show that it has a smoother bound on the price action range than the Bollinger Band. Comparisons are also made for the gap corrected chart to show the advantageous feature of the ESD band even in the case of gap occurrence. Trading techniques developed for the Bollinger Band can be straight forwardly applied to those for the ESD band.

Estimation of Forest Growing Stock by Combining Annual Forest Inventory Data (연년 산림자원조사 자료를 이용한 임목축적 추정)

  • Yim, Jong Su;Jung, Il Bin;Kim, Jong Chan;Kim, Sung Ho;Ryu, Joo Hyung;Shin, Man Yong
    • Journal of Korean Society of Forest Science
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    • v.101 no.2
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    • pp.213-219
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    • 2012
  • The $5^{th}$ national forest inventory (NFI5) has been reorganized to annual inventory system for providing multi-resources forest statistics at a point in time. The objective of this study is to evaluate statistical estimators for estimating forest growing stock in Chungcheongbuk-Do from annual inventory data. When comparing two estimators; simple random sampling (SRS) and double sampling for post-stratification (DSS), for estimating mean forest growing stock ($m^3/ha$) at each surveyed year, the estimate for DSS in which a population of interest is stratified into three sub-population (forest cover types) was more precise than that for SRS. To combine annual inventory field data, three estimators (Temporally Indifferent Method; TIM, Moving Average; MA, and Weighted Moving Average; WMA) were compared. Even though the estimated mean for TIM and WMA is identical, WMA-DSS is preferred to provide more smaller variance of estimated mean and to adjust for catastrophic events at a surveyed year (so-called "lag bias") by annual inventory data.

Real-time Confidence interval estimation for Improved accuracy of Ship-inside the anomaly detection (선박내부 이상감지의 정확도 향상을 위한 실시간 신뢰구간 추정)

  • Kim, Yeong-Ju;Heo, yu Kyung;Jeong, Majung-A
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.721-723
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    • 2014
  • 본 논문은 선박내부의 센서데이터 이상감지를 위해 실시간 신뢰구간을 설정하고 신뢰구간을 초과하거나 미만이 되면 경보를 통해 관리자에게 알려주는 모니터링을 위한 신뢰구간 추정이다. 여기서, 이상 감지 예측의 정확도 향상을 위해 단순지수평활법과 이동평균법의 평균제곱오차를 비교 평가 하였다. 실험결과, 이동평균법의 평균제곱오차가 단순지수평활법 보다 적게 나와 선박 내부 모니터링을 위한 신뢰구간은 이동평균법을 적용하였다.

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.

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.

A Study on the Travel Speed Estimation Using Bus Information (버스정보기반 통행속도 추정에 관한 연구)

  • Bin, Mi-Young;Moon, Ju-Back;Lim, Seung-Kook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.4
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    • pp.1-10
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    • 2013
  • This study was conducted to investigate that bus information was used as an information of travel speed. To determine the travel speed on the road, bus information and the information collected from the point detector and the interval detection installed were compared. If bus information has the function of traffic information detector, can provide the travel speed information to road users. To this end, the model of recognizing the traffic patterns is necessary. This study used simple moving-average method, simple exponential smoothing method, Double moving average method, Double exponential smoothing method, ARIMA(Autoregressive integrated moving average model) as the existing methods rather than new approach methods. This study suggested the possibility to replace bus information system into other information collection system.

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.

Irregularly-Sampled Time Series Correction Method for Anomaly Detection in Manufacturing Facility (생산 설비의 이상탐지를 위한 불규칙 샘플링 시계열 데이터 보정 기법)

  • Shin, Kang-hyeon;Jin, Kyo-hong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.85-88
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    • 2021
  • There are many irregularly-sampled time series in the manufacturing data which are collected from manufacturing facilities by short intervals. Those time series often have large variance. In this paper, we propose irregularly-sampled time series correction method based on simple moving average. This method corrects time intervals between neighboring values in time series regularly and reduces the variance of the values at the same time. We examine that this method improves performance of anomaly detection in manufacturing facility.

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An estimation method based on autocovariance in the simple linear regression model (단순 선형회귀 모형에서 자기공분산에 근거한 최적 추정 방법)

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.2
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    • pp.251-260
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    • 2009
  • In this study, we propose a new estimation method based on autocovariance for selecting optimal estimators of the regression coefficients in the simple linear regression model. Although this method does not seem to be intuitively attractive, these estimators are unbiased for the corresponding regression coefficients. When the exploratory variable takes the equally spaced values between 0 and 1, under mild conditions which are satisfied when errors follow an autoregressive moving average model, we show that these estimators have asymptotically the same distributions as the least squares estimators. Additionally, under the same conditions as before, we provide a self-contained proof that these estimators converge in probability to the corresponding regression coefficients.

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An implementation of performance assessment system based on academic achievement analysis for promotion of self-directed learning ability (자기주도적 학습능력 촉진을 위한 학업성취도 분석 기반의 수행평가 시스템 구현)

  • Kim, Hyun-Jeong;Choi, Jin-Seek
    • Journal of The Korean Association of Information Education
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    • v.13 no.3
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    • pp.313-323
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    • 2009
  • The objective of this paper is an implementation of analysing and predicting functions to promote self-directed learning for student's performance assessment system in programming subjects. By adapting Rubric model, the proposed functions inform a student of the assessment criteria and level to be carried out with respects to two-way specifications such as rational ability, problem solving ability and creativity. The proposed system also provides a graphical results of each ability instead of assessment result, for better understanding and analyzing himself/herself based on to the performance assessment and the result. Moreover, the proposed system contains a method to predict future achievement result with moving average technique. Therefore, an academic achievement can be precisely determined by himself/herself to estimate self-directed learning. The teacher can provide different level of educational resources such as supplement learning, problem explains and private instructor etc., in order to maximize efficiency of education.

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