• Title/Summary/Keyword: VECM

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국채선물을 이용한 채권포트폴리오의 VECM과 VAR모형에 의한 헤지

  • Han, Seong-Yun;Im, Byeong-Jin;Won, Jong-Hyeon
    • The Korean Journal of Financial Studies
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    • v.8 no.1
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    • pp.231-252
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    • 2002
  • 2000년 7월부터 채권시가평가의 실행으로 채권운용자들도 채권포트폴리오의 위험을 채권선물을 이용하여 통제하거나 감소시키기 위해 헤지를 하여야 한다. 이때 헤지비율을 추정하는 방법으로는 전통적 회귀분석모형, 백터오차수정모형(Vector Error Correction Model : VECM)과 VAR모형(Vector AutoRegressive Model)이 있다. 전통적인 회귀분석모형에 의하여 추정된 헤지비율은 시계열자료의 불안정성(nonstationary) 등으로 인하여 잘못 추정될 가능성이 있어 면밀한 검토와 분석 후 사용하여야 한다. 시계열자료의 불안정성으로 말미암아 야기되는 문제점들을 개선할 수 있는 모형으로서 VECM과 VAR모형이 널리 이용되고 있다. 따라서 본 연구는 VECM과 VAR모형을 사용하여 추정된 헤지비율과 전통적 회귀분석모형을 사용하여 추정한 헤지비율을 비교하여 어떤 모형으로 추정한 헤지비율이 더 정확한지를 평가하는데 목적을 두고 있다. 즉, 본 연구는 KTB 현 선물의 헤징에 대한 연구로 2000년 1월 4일부터 2001년 7월 27일까지 385일간의 KTB 현 선물 자료와 불룸버그 국채지수를 대상으로 VECM 및 VAR모형과 전통적 회귀분석모형에 의한 헤지비율을 추정하고 각 모형의 설명력과 예측력을 비교하고자 한다. 이 연구의 실증분석 결과, KTB 현물가격과 KTB 선물가격간, 블룸버그 국채지수와 KTB 선물가격간에는 공적분 관계가 존재하며, VECM 및 VAR와 전통적 회귀분석모형을 이용하여 추정한 최적헤지비율의 크기는 대동소이(大同小異)하며, 전통적 회귀분석방법을 이용하는 것이 VECM과 VAR모형을 이용할 때 보다 설명력과 예측력이 우월한 것으로 나타났다.

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Analysis and Forecasting of Daily Bulk Shipping Freight Rates Using Error Correction Models (오차교정모형을 활용한 일간 벌크선 해상운임 분석과 예측)

  • Ko, Byoung-Wook
    • Journal of Korea Port Economic Association
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    • v.39 no.2
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    • pp.129-141
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    • 2023
  • This study analyzes the dynamic characteristics of daily freight rates of dry bulk and tanker shipping markets and their forecasting accuracy by using the error correction models. In order to calculate the error terms from the co-integrated time series, this study uses the common stochastic trend model (CSTM model) and vector error correction model (VECM model). First, the error correction model using the error term from the CSTM model yields more appropriate results of adjustment speed coefficient than one using the error term from the VECM model. Furthermore, according to the adjusted determination coefficients (adjR2), the error correction model of CSTM-model error term shows more model fitness than that of VECM-model error term. Second, according to the criteria of mean absolute error (MAE) and mean absolute scaled error (MASE) which measure the forecasting accuracy, the results show that the error correction model with CSTM-model error term produces more accurate forecasts than that of VECM-model error term in the 12 cases among the total 15 cases. This study proposes the analysis and forecast tasks 1) using both of the CSTM-model and VECM-model error terms at the same time and 2) incorporating additional data of commodity and energy markets, and 3) differentiating the adjustment speed coefficients based the sign of the error term as the future research topics.

The Behavior of the Term Structure of Interest Rates with the Markov Regime Switching Models (마코프 국면전환을 고려한 이자율 기간구조 연구)

  • Rhee, Yu-Na;Park, Se-Young;Jang, Bong-Gyu;Choi, Jong-Oh
    • Journal of Korean Institute of Industrial Engineers
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    • v.36 no.3
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    • pp.203-211
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    • 2010
  • This study examines a cointegrated vector autoregressive (VAR) model where parameters are subject to switch across the regimes in the term structure of interest rates. To employ the regime switching framework, the Markov-switching vector error correction model (MS-VECM) is allowed to the regime shifts in the vector of intercept terms, the variance-covariance terms, the error correction terms, and the autoregressive coefficient parts. The corresponding approaches are illustrated using the term structure of interest rates in the US Treasury bonds over the period of 1958 to 2009. Throughout the modeling procedure, we find that the MS-VECM can form a statistically adequate representation of the term structure of interest rate in the US Treasury bonds. Moreover, the regime switching effects are analyzed in connection with the historical government monetary policy and with the recent global financial crisis. Finally, the results from the comparisons both in information criteria and in forecasting exercises with and without the regime switching lead us to conclude that the models in the presence of regime dependence are superior to the linear VECM model.

Stock Market and Economic Forces : Evidence from Korea (우리나라 증권시장과 거시경제변수 - VECM을 중심으로 -)

  • Jung, Sung-Chang
    • The Korean Journal of Financial Management
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    • v.17 no.1
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    • pp.137-159
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    • 2000
  • 재무경제학에서 많은 연구들이 주식가격과 거시경제활동과의 이론적 모형을 설정하고 이를 점증하고자 하였다. 이 분야에서 지금까지 주로 ARMAX 모형이나 VAR 모형들이 사용되어 왔으나, 이러한 방법들은 주식가격과 거시경제변수들간의 장기적인 균형관계를 파악할 수 없다는 한계점을 안고 있다. 따라서, 본 연구의 목적은 이러한 한계점을 극복할 수 있는 VECM을 이용하여 우리나라 증권시장과 거시경제변수들간의 장기적인 균형관계를 규명하고자 함에 있다. 검증결과, 모든 변수들의 시계열이 불안정적인 것으로 확인된 관계로, 다변량시계열의 공적분 관계를 검증하는 Johansen 검증을 VECM 모형의 구조 안에서 실시하였다. 종합주가지수와 거시경제변수들간에는 장기적 안정관계를 나타내는 공적분관계가 있는 것으로 나타났으며, 종합주가지수와 거시경제변수들간의 관계는 대부분 이론적인 관계에서 예상하는 부호와 동일한 부호를 갖으며 통계적으로도 유의하였다. 그리고, VECM의 설명력이 종래에 주로 사용하였던 VAR 모형의 설명력보다 더 우월하게 나타났다.

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Korean Stock Price Index and Macroeconomic Forces (우리나라 증권시장과 거시경제변수 : ANN와 VECM의 설명력 비교)

  • Jung, Sung-Chang;Lee, Timothy H.
    • The Korean Journal of Financial Management
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    • v.19 no.2
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    • pp.211-231
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    • 2002
  • 본 연구의 목적은 VECM(Vector Error Correction Model)과 인공지능모형(Artificial Neural Networks)을 이용하여 우리나라 증권시장과 거시경제 변수들과의 장기적 관계에 대한 설명력을 비교해보고자 함에 있다. VECM이 APT(Arbitrage Pricing Theory)에 기초를 둔 선형동학모형이라고 한다면, 인공지능모형은 비모수적 비선형모형이라는 점에서, 두 방법론의 분석결과를 직접 비판하는 것은 의미있는 연구라고 할 수 있다. 인공지능모형을 주로 활용하는 선행연구들에 의하면, 증권시장은 시장의 특이패턴들로 인해 계량경제학적 접근인 선형 모형보다는 인공지능모형을 통해 증권시장의 움직임을 설명하고 예측하는 것이 더 바람직할 수도 있다는 것이다. 따라서, 본 연구에서는 VECM분석에서 자료의 안정성을 검증하고, 공적분 백터를 발견한 이후, 장기적 균형관계의 실증적 분석을 하였다. 그리고, 인공지능모형에서는 delta rule과 Sigmoid 함수를 이용한 GRNN(General Regression Neural Net)과 Back-Propagation등의 방법들을 활용하였다. 이러한 분석결과, Back-Propagation 모형이 다른 모든 모형들보다도 더 우수한 설명력을 보여주고 있었다. 이러한 결과들은 인공지능모형이 동태적인 선형 모형보다도 더 우수한 설명력을 제공할 수 있는 가능성을 보여주고 있었다.

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

  • Kim, Ju-Wan
    • The Korean Journal of Financial Management
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    • v.26 no.1
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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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A Causality Test on Hairtail Prices among Import and Domestic Markets Using a Vector Error Correction Model(VECM) (오차수정모형을 이용한 갈치 시장가격 간의 인과관계 분석)

  • Kim, Kyu-Min;Kim, Do-Hoon
    • Ocean and Polar Research
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    • v.40 no.1
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    • pp.49-58
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    • 2018
  • This study aimed to analyze the causality of hairtail prices among import and domestic distribution channels using a Vector Error Correction Model(VECM). The results are as follows. First, since the ADF unit-root test suggests that each of the price variables, apart from retail price, has a unit root, the price variables should be 1st-differenced to secure the stability of the prices. Next, through the Johansen co-integration test, it was discovered that there are long-term relationships among the price variables. On the basis of the co-integration test, VECM analysis shows that the producer price has a long-run balance with the import and wholesale prices. In particular, when the prices deviate from the balance, the producer price dynamically adjusts to return to the long-term relationship among prices. It also indicates that the producer price has an impact on the import, wholesale, and retail prices in the short-term, and the import price has an influence on the producer and wholesale prices. In addition, the impulse response analysis demonstrates that the impulse of import and producer prices has a lasting impact on each of the prices.

Long Memory and Cointegration in Crude Oil Market Dynamics (국제원유시장의 동적 움직임에 내재하는 장기기억 특성과 공적분 관계 연구)

  • Kang, Sang Hoon;Yoon, Seong-Min
    • Environmental and Resource Economics Review
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    • v.19 no.3
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    • pp.485-508
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    • 2010
  • This paper examines the long memory property and investigates cointegration in the dynamics of crude oil markets. For these purposes, we apply the joint ARMA-FIAPARCH model with structural break and the vector error correction model (VECM) to three daily crude oil prices: Brent, Dubai and West Texas Intermediate (WTI). In all crude oil markets, the property of long memory exists in their volatility, and the ARMA-FIAPARCH model adequately captures this long memory property. In addition, the results of the cointegration test and VECM estimation indicate a bi-directional relationship between returns and the conditional variance of crude oil prices. This finding implies that the dynamics of returns affect volatility, and vice versa. These findings can be utilized for improving the understanding of the dynamics of crude oil prices and forecasting market risk for buyers and sellers in crude oil markets.

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A Study on the Effects of the Macroeconomic Variables on the Economic Growth by VECM Model (VECM모형을 활용한 거시경제변수가 성장에 미치는 영향분석)

  • Cho, Woo-Sung
    • International Commerce and Information Review
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    • v.14 no.4
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    • pp.27-47
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    • 2012
  • The study aims to analyze how the variables for Korea, such as the exports, imports, FDI(Inward) and FDI(Outward), influence the economic growth and how they affect each other. For the purpose of empirical analysis, this paper used the quarterly time series data from 1980 to 2010, dividing the period before and after 1997(IMF). The variables used in this study were log-transformation from the original variables. This study empirically tests the relationship among variables by using VECM with considering the time-series properties of each variable. The results found from the study are as followings. Causality analysis using VECM proved that no causality between GDP and exports existed, whereas causality between GDP and FDI(Inward) existed, in which GDP affected FDI(Inward) since IMF. However, it was found that other periods and FDI(Inward) did not affect GDF and had no causality among them.

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A Study on the Causal Relationship Between Shipping Freight Rates (해운 운임 간 인과관계에 관한 연구)

  • Jeon, JunWoo
    • Journal of Convergence for Information Technology
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    • v.9 no.12
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    • pp.47-53
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    • 2019
  • The purpose of the study was to utilize VECM(Vector Error Correction Model) and detect causal relationships among shipping freight rates. Shipping freight rates used in this study were BDI(Baltic Dry Index), HRCI(Howe Robinson Containership Index), WS(World Scale rate) and SCFI(Shanghai Containerized Freight Index). Using weekly data published since August 2nd, 2013 to September 6th, 2019, it was discovered that BDI and WS were heavily influenced by past week's BDI and WS respectively. VECM also found that one percent increase in WS resulted in 0.022% increase in following week's HRCI data. One percent increase in HRCI affects SCFI by 0.77% on the following week. This study believes that finding may help each shipping market of shipping freight rates estimates, thereby encouraging decision markers to exercise discretion and establish best interest decision.