• 제목/요약/키워드: X-12 ARIMA

검색결과 16건 처리시간 0.018초

ARIMA 모형을 이용한 보이스피싱 발생 추이 예측 (Forecasting the Occurrence of Voice Phishing using the ARIMA Model)

  • 추정호;주용휘;엄정호
    • 융합보안논문지
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    • 제22권3호
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    • pp.79-86
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    • 2022
  • 보이스피싱은 가짜 금융기관, 검찰청, 경찰청 등을 사칭하여 개인의 인증번호와 신용카드 정보를 알아내거나 예금을 인출하게 하여 탈취하는 사이버 범죄이다. 최근에는 교묘하고도 은밀한 방법으로 보이스피싱이 이루어지고 있다. '18~'21년 발생한 보이스피싱의 추세를 분석하면, 보이스피싱이 발생되는 시기에 예금 인출이 급격하게 증가하여 시계열 분석에 모호함을 주는 계절성이 존재함을 발견하였다. 이에 본 연구에서는 보이스피싱 발생 추이의 정확한 예측을 위해서 계절성을 X-12 계절성 조정 방법론으로 조정하고, ARIMA 모형을 이용하여 2022년 보이스피싱 발생을 예측하였다.

Trading Day Effect on the Seasonal Adjustment for Korean Industrial Activities Trend Using X-12-ARIMA

  • Park, Worlan;Kang, Hee Jeung
    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.513-523
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    • 2000
  • The X-12-ARIMA program was utilized on the analysis of the time series trend on 76 Korean industrial activities data in order to ensure that the trading day effect adjustment as well as the seasonal effect adjustment is needed to extract the fundamental trend-cycle factors from various economic time series data. The trading day effect is strongly correlated with the activity of production and shipping but not with the activity of inventory. Furthermore, the industrial activities were classified with respect to the sensitivity on the tranding day effect.

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ARIMA model에 의한 서울시 일부지역 $SO_2$ 오염도의 월변화에 대한 시계열분석 (A Time Series Analysis for the Monthly Variation of $SO_2$ in the Certain Areas)

  • 김광진;이상훈;정용
    • 한국대기환경학회지
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    • 제4권2호
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    • pp.72-81
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    • 1988
  • The typical ARIMA model which was developed by Box and Jenkins, was applied to the monthly $SO_2$ data collected at Seoungsoo and Oryudong in metropolitan area over five years, 1982 to 1986. To find out the changing pattern of $SO_2$ concentration, autocorrelation and partial autocorrelation analysis were undertaken. The three steps of time series model building were followed and the residual series was found to be a random white noise. The results of this study is summarized as follows. 1) The monthly $SO_2$ series was found to be a non-stationary series which which has a periodicity of 12 months. After eliminating the periodicity by differencing, the monthly $SO_2$ series became a stationary series. 2) The ARIMA seasonal model of the $SO_2$ was determined to be ARIMA $(1, 0, 0)(0, 1, 0,)_{12}$ model. 3) The model equations based on the prediction were: for Seoungsoodong: $Y_t = 0.5214Y_{t-1} + Y_{t-12} - 0.5214Y_{t-13} + a_t$ for Oryudong: $Y_t = 0.8549Y_{t-1} + Y_{t-12} - 0.8549Y_{t-13} + a_t$ 4) The validity of the model identified was checked by compairing the measured $SO_2$ values and one-month-ahead predicted values. The result of correlation and regression analysis is as follows. Seoungsoodong: $Y = 0.8710X + 0.0062 r = 0.8768$ Oryudong : $Y = 0.8758X + 0.0073 r = 0.9512$

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철도수요의 시계열 분해 방법에 대한 연구 (A Study on the Seasonal Decomposition of the Railway Passenger Demand)

  • 오석문;김동희
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2001년도 추계학술대회 논문집
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    • pp.111-116
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    • 2001
  • This paper introduces how to adopt the X-12-ARIMA to decompose the railway passenger demand of the Korea National Railroad Especially, selecting on proper filters is focused. The trend filter is identical to the low pass filter in the signal Processing field, and so the seasonal filter is to band pass filter too. Some considerations, selecting a filter, are provided from the view-point of the spectrum analysis. The technique introduced in this paper will be adopted to the project that is to develope the forecasting system of Korea railway passenger demand which is a part of the high speed rail information system.

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Nexus between Indian Economic Growth and Financial Development: A Non-Linear ARDL Approach

  • KUMAR, Kundan;PARAMANIK, Rajendra Narayan
    • The Journal of Asian Finance, Economics and Business
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    • 제7권6호
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    • pp.109-116
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    • 2020
  • The study examines the nexus between financial development and economic growth in India during Q1: 1996 to Q3: 2018. This study employs time-series data of real GDP and ratio of broad money to GDP as a proxy for economic and financial development, respectively. The data are obtained from RBI database on the Indian economy. All variables are seasonally adjusted using X12-arima technique and expressed in natural logarithm form. Non-linear Autoregressive Distributed Lag (NARDL) bound test has been used to check for cointegrating relationship of these two variables. Empirical findings suggest that, unlike in the short run, in the long run financial development does impact economic growth positively. Further, a symmetric effect of positive and negative components of financial development is found for the Indian economy, whereas the effect of control variable like exchange rate and trade openness is in consonance with common economic intuition. Exchange rate is in consonance with intuitive economic logic that a fall in exchange rate makes exports cheaper and increases the quantity of export, which improves the balance of payment and leads to a rise in aggregate demand, hence improves economic growth. This paper contributes to the existing literature on India by breaking down financial indicator into positive and negative components to examine the finance-growth relationship.

한국의 구직급여 수급률 결정요인 분석 (Unemployment Insurance Take-up Rates in Korea)

  • 이대창
    • 노동경제논집
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    • 제39권1호
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    • pp.1-31
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    • 2016
  • 고용노동부 "고용보험DB" 의 상실자 종합통계와 실업급여 지급통계를 이용하여 구직급여 수급자격자의 수급과 재취업에 따른 수급자격 상실을 경합적 위험(competing risks)모형으로 분석하였다. 아울러 구직급여 수급률과 경기지수 간의 교차상관관계 분석을 하였다. 분석결과 구직급여 수급률이 실업률과 정(+)의 상관관계를 보이고, 6개월가량 실업률과 경기동행지수를 선행한다. 아울러 수급률이 연령, 학력, 급여지급기간, 소득대체율과 정(+)의 상관관계를 보이고 있다.

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