• 제목/요약/키워드: Variance Decomposition

검색결과 143건 처리시간 0.022초

Cointegrated Relations between Foreign Ownership and Business Conditions in the Level of Korean Capital Market

  • Kim, Ju-Wan
    • 재무관리연구
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    • 제26권1호
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    • pp.127-163
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    • 2009
  • This paper examines the results of survey that the foreign ownership is cointegrated with capital market conditions in Korea using Vector Error Correction Model (VECM) and how the mechanism of innovations and dynamics among the foreign ownership and capital market proxies in the VECM was described. Specifically, we find that the foreign ownership and capital market proxies follow I (1) process and there are cointegrated relations between the foreign ownership and capital market proxies. Adopting the impulse response function and variance decomposition in the VECM, we suggest, in turn, the default risk premia, liquidity of market and the rate of interest in long term business cycle take on a special function on the KSE and KOSDAQ. Finally, we also offer evidences of which there are differences of the mechanism of dynamics and innovations between on the KSE and on the KOSDAQ.

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아시아 주식수익률의 동조화에 대한 연구 (East Asian five stock market linkages)

  • 정헌용
    • 경영과정보연구
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    • 제27권
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    • pp.131-147
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    • 2008
  • The study examines common component existing in five Asian countries from 1991 to 2007. To do this, the daily stock market indices of Korea, Malaysia, Thailand, Indonesia, and the Philippines were used. Using a Vector Autoregressive Model this paper analyzes causal relations and dynamic interactions between five Asian stock markets. The findings in this study indicate that level of five Asian stock markets' stock return linkages are low. First, from the statistics for pair-wise Granger causality tests, I find Granger-causal relationship between Korea and Indonesia and between Malaysia and and Indonesia. Second, from the results of response function and the statistics of variance decomposition, I find that week shocks to Korean stock market return on Malaysia, Indonesia, Thailand, and the Philippines stock market returns. The results indicate increased Asian stock market linkages but the level is very low. This implies that the benefits of diversification within the five Asian stock markets are still existed.

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Research on the Environmental Effects and Green Development Path of South Korean Foreign Trade

  • Le, Cao
    • Journal of Korea Trade
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    • 제24권7호
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    • pp.93-106
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    • 2020
  • Purpose - This paper aims to examine the environmental effects of South Korean foreign trade, and the changing relationship between industrial "three wastes" emissions and foreign trade. Design/methodology - Based on time series data of South Korean foreign trade and industrial "three wastes" from 2009 to 2019, a VAR model was used to analyze the long-term internal links and dynamic changes between foreign trade and environmental pollution. Findings - Variance decomposition analysis shows that for the three types of pollutants, self-impact contributes the most to the variance decomposition. It follows that South Korean foreign trade has a certain negative impact on the environment, and this impact has a certain sustainability. Originality/value - This paper contributes to the study on the relationship between foreign trade and environmental pollution. It theoretically proposes a coordinated development path for foreign trade development and green development based on the environmental impact of foreign trade, to provide a reference for the development of collaborative promotion.

Analyzing nuclear reactor simulation data and uncertainty with the group method of data handling

  • Radaideh, Majdi I.;Kozlowski, Tomasz
    • Nuclear Engineering and Technology
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    • 제52권2호
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    • pp.287-295
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    • 2020
  • Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

An Orthogonal Representation of Estimable Functions

  • Yi, Seong-Baek
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.837-842
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    • 2008
  • Students taking linear model courses have difficulty in determining which parametric functions are estimable when the design matrix of a linear model is rank deficient. In this note a special form of estimable functions is presented with a linear combination of some orthogonal estimable functions. Here, the orthogonality means the least squares estimators of the estimable functions are uncorrelated and have the same variance. The number of the orthogonal estimable functions composing the special form is equal to the rank of the design matrix. The orthogonal estimable functions can be easily obtained through the singular value decomposition of the design matrix.

국채선도금리(Forward rate)의 효율성(Efficiency)에 관한 연구 (A Study on the Efficiency of KTB Forward Markets)

  • 문규현;홍정효
    • 재무관리연구
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    • 제22권2호
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    • pp.189-212
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    • 2005
  • 본 연구는 새로운 정보에 대하여 국채선도금리시장(forward market)과 국채 현물시장(spot market) 중 어느 시장이 더 효율적으로 반응하는지에 관한 분석을 실시하였다. 2002년 3월부터 2005년 1월말까지 3개월, 6개월, 9개월 및 1년물 국채선도금리(forward rate)와 각 시계열들의 현물 금리의 수익률 및 변동성자료를 사용하여 그랜져인과관계분석, 충격반응함수 및 분산분해 분석을 실시하였으며 주요 분석결과는 다음과 같다. 먼저 수익률 및 변동성을 이용한 그랜져인과관계분석(Granger causality test)결과에 의하면 국채 선도금리시장이 국채현물시장보다 새로운 정보에 대하여 더 효율적으로 반응하는 것으로 나타났다. 충격 반응함수(impulse response analysis)에서도 국채선도금리시장의 국채현물시장에 대한 영향력이 국채현물시장의 국채선도금리시장에 대한 영향력보다 더 강하고 지속적인 것으로 나타났다. 분산분해분석(variance decomposition analysis)에서는 전체적으로 3개월 및 6개월 등기간이 짧은 국채선도금리 수익률 및 변동성이 기간이 긴 국채선도금리보다 국채현물시장에 대한 영향력이 상대적으로 더 큰 것으로 나타났다. 이러한 분석결과로부터 새로운 정보에 대하여 국채현물시장보다는 국채선도금리시장이 더 효율적으로 반응하고 있음을 추론해 볼 수 있으며 이는 기존 국내외 주식현물시장과 선물시장들 간의 영향력을 분석한 결과 선물시장의 현물시장에 대한 영향력이 더 강한다는 결과들과 일맥상통하는 것으로 나타났다.

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Nonnegative variance component estimation for mixed-effects models

  • Choi, Jaesung
    • Communications for Statistical Applications and Methods
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    • 제27권5호
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    • pp.523-533
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    • 2020
  • This paper suggests three available methods for finding nonnegative estimates of variance components of the random effects in mixed models. The three proposed methods based on the concepts of projections are called projection method I, II, and III. Each method derives sums of squares uniquely based on its own method of projections. All the sums of squares in quadratic forms are calculated as the squared lengths of projections of an observation vector; therefore, there is discussion on the decomposition of the observation vector into the sum of orthogonal projections for establishing a projection model. The projection model in matrix form is constructed by ascertaining the orthogonal projections defined on vector subspaces. Nonnegative estimates are then obtained by the projection model where all the coefficient matrices of the effects in the model are orthogonal to each other. Each method provides its own system of linear equations in a different way for the estimation of variance components; however, the estimates are given as the same regardless of the methods, whichever is used. Hartley's synthesis is used as a method for finding the coefficients of variance components.

곱분해 기법 기반의 통계 모멘트를 이용한 효율적인 강건 최적설계 (Efficient Robust Design Optimization Using Statistical Moments Based on Multiplicative Decomposition Method)

  • 조수길;이민욱;이태희
    • 대한기계학회논문집A
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    • 제36권10호
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    • pp.1109-1114
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    • 2012
  • 제품 생산 시 발생하는 제작 공차, 항복강도와 탄성계수 등 재료 물성치의 불확실성, 온도와 습도 같이 시스템에 작용하는 환경인자 등은 시스템의 성능에 영향을 미친다. 강건 최적설계는 이러한 인자들이 시스템에 미치는 영향을 최소화하면서 성능을 개선하는 설계기법으로 최근 많은 연구가 이루어지고 있다. 하지만 기존의 강건 최적설계 기법은 여러 인자들의 분포를 고려해야 하기 때문에 막대한 계산비용이 드는 문제가 있다. 본 논문에서는 이러한 문제점을 개선하기 위하여 곱분해 기법을 이용한 강건 최적설계를 제안한다. 제안된 기법을 이용하여 설계영역을 크리깅 메타모델로 근사하고 곱분해 기법을 적용하여 평균과 분산을 효율적이고 정확하게 계산하여 강건 최적설계를 수행한다. 제안된 방법을 수학예제와 공학예제에 적용하여 유용성을 검증한다.

주택가격 상승 충격의 저출산 심화 기여도 연구 (An Empirical Study on the Contribution of Housing Price to Low Fertility)

  • 박진백
    • 문화기술의 융합
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    • 제7권4호
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    • pp.607-612
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    • 2021
  • 본 연구는 주택가격 상승 충격이 저출산에 미치는 영향과 각 변수들의 합계출산율 변동 기여도를 추정하였다. 본 연구는 기존 연구들이 시도하지 않았던 샤플리 분해와 패널 VAR의 예측오차분산분해를 통해 과거 출산율 하락 경험치에 대한 각 변수들의 기여도와 각 변수의 향후 기여도를 추정하여 차별성이 있다. 본 연구의 주요 분석결과는 다음과 같다. 우리나라 합계출산율의 하락은 최근 합계출산율 하락 흐름에 강한 영향을 받았으며, 이 영향력은 향후 미래에도 지속될 것으로 전망되었다. 주거비의 경우는 과거 주택 매매가격은 전세가격에 비해 상대적으로 합계출산율변동에 미친 기여도가 작았으나, 향후 미래에는 장기적으로 그 영향력이 커질 것으로 전망되었다. 주택 매매가격, 전세가격 이외 사교육비 역시 합계출산율 하락에 주요 원인으로 작동하였음을 실증하였고, 높은 사교육비 부담이 장기적으로도 합계출산율을 낮출 것으로 전망되었다.

신경망을 이용한 시계열의 분해분석 (Decomposition Analysis of Time Series Using Neural Networks)

  • 지원철
    • 대한산업공학회지
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    • 제25권1호
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    • pp.111-124
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    • 1999
  • This evapaper is toluate the forecasting performance of three neural network(NN) approaches against ARIMA model using the famous time series analysis competition data. The first NN approach is to analyze the second Makridakis (M2) Competition Data using Multilayer Perceptron (MLP) that has been the most popular NN model in time series analysis. Since it is recently known that MLP suffers from bias/variance dilemma, two approaches are suggested in this study. The second approach adopts Cascade Correlation Network (CCN) that was suggested by Fahlman & Lebiere as an alternative to MLP. In the third approach, a time series is separated into two series using Noise Filtering Network (NFN) that utilizes autoassociative memory function of neural network. The forecasts in the decomposition analysis are the sum of two prediction values obtained from modeling each decomposed series, respectively. Among the three NN approaches, Decomposition Analysis shows the best forecasting performance on the M2 Competition Data, and is expected to be a promising tool in analyzing socio-economic time series data because it reduces the effect of noise or outliers that is an impediment to modeling the time series generating process.

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