• 한국경영과학회지
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• 제42권3호
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• pp.13-24
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• 2017

This paper aims to implement "structural changes detection procedure" in pairs trading algorithm and to show that the proposed approach outperforms the extant pair trading algorithm. Structural changes in pairs trading are defined in terms of changes in cointegrating factors and broken cointegration relationship. These changes are designed to test extant structural changes and unit root test methodologies. The simulation finds that expanding the changes in structure, increasing the mean reverting process of spread, and extending the consecutive days of broken cointegration will increase the performances of the proposed algorithm. Empirical study results are also consistent those of the simulation studies. The proposed algorithm outperforms the extant algorithm relative to risk and return given that the cumulative profit/loss has a significant upward-slope with minimal variance.

• 수산해양교육연구
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• 제27권6호
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• pp.1610-1618
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• 2015

This study is aimed to estimate price interactions between wild caught fish and farmed fish on the Korean seafood market, using multivariate cointegration analysis. Major commercially important four wild caught fish (chub mackerel, hairtail, yellow croaker and spanish mackerel) and two farmed fish(oliver flounder and black rockfish) are selected as analytical target fish species. Between 2000 and 2013, monthly production and price data are used in this study. The results of cointegration test showed that there would be a long-term equilibrium relationship among 4 wild caught fish and 2 farmed fish. However, the results of exclusion test indicated that farmed fish might not contribute significantly to the long-run relationship, suggesting that farmed fish might be only a weak substitute for wild caught fish, but no significant interaction could be found.

• 수산해양기술연구
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• 제50권4호
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• pp.502-510
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• 2014

This study aimed to analyze the relationship between catch amount and market price of sandfish for improvement of fishing revenues and effective fisheries management. By estimating the sandfish price function by fishery, the study tried to investigate changes of prices by catch amount as well as changes of fishing revenues by catch amount and price. Results showed that time series data on catch and price were estimated to be non-stationary from unit root tests, but long-term equilibrium relations between catch amount and price were found from a cointegration analysis. Results of regression analyses indicated that the catch amount would have negative impacts on prices of sandfish in both coastal gillnet and danish seine fisheries.

• East Asian Economic Review
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• 제19권1호
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• pp.39-70
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• 2015

This paper examines the effects of foreign direct investment (FDI) on South Asian economies' output growth, utilizing recent panel cointegration testing and estimation techniques. Annual panel data on eight SAARC (South Asian Association for Regional Cooperation) member countries' macroeconomic variables over the period 1960- 2013 are employed in empirical analysis. Using various heterogeneous panel cointegration and panel causality tests, a bi-directional relationship between FDI and growth is found. We find evidence for both FDI-led growth and growth-induced FDI hypotheses for the South Asian economies over the sample period. Individual member countries exhibit heterogeneity in terms of the direction or existence of causality subject to their idiosyncratic economic conditions. Among various regressors, FDI, financial development, human capital, and government consumption show the most significant positive effects on output growth. As determinants of FDI, GDP, financial development, human capital, and government consumption are found significant in the region. The bi-directional causality between FDI and growth is found robust to the inclusion of other control variables and using different estimation techniques.

• The Journal of Asian Finance, Economics and Business
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• 제3권2호
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• pp.5-11
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• 2016

This study investigates the impact of Malaysia's capital market and other key determinants on Economic Growth from the period of 1988 to 2012. The key determinants studied are foreign direct investment and real interest rate. This study also examines the long run and short run relationship between the economic growth and capital market, foreign direct investment, and real interest rate by using bound testing cointegration of Autoregressive Distributed Lag (ARDL) and Error Correction Model (ECM) version of ARDL model. The empirical results of the study suggest that there is long- run cointegration among the capital market, foreign direct investment, real Interest rate and economic growth. The result also suggests that capital market and real interest rate have positive impact on economic growth in the short run and long run. Foreign direct investment does not show positive impact on economic growth in the short run but it does in the long run.

• 펄프종이기술
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• 제43권3호
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• pp.128-136
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• 2011

In order to investigate the relationship between the prices of wood chips and pulps, regression analysis and cointegration test were conducted. Test results indicated that pulp producers adjusted pulp price in response to the change in wood-chip price and there were a long-run relationship between these prices. This implied that by raising the selling price of pulp, pulp producers avoid profit loss incurred by the increase in the wood-chip price. The existence of cointegration between wood chips and pulp prices implied that pulp producers were competing when they set the selling price of pulp.

• 정보처리학회논문지B
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• 제14B권7호
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• pp.531-540
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• 2007

본 논문에서는 주가예측의 정확도를 향상시키기 위하여 공적분 검정(Cointegration Tests)과 인공 신경망(Artificial Neural Networks)을 사용한 2단계 하이브리드 예측 모델을 제시한다. 기존의 연구에서는 예측을 시도하고자 하는 종목의 일자별 개별 레코드를 인공 신경망과 같은 방법으로 학습함으로써 주식 데이터가 가지는 시계열적 특성을 충분히 반영하지 못하였는데, 새로 제안한 모형에서는 주식자료의 과거시차들의 값들도 인공 신경망의 속성(feature)으로 사용하여 기존 연구의 한계를 보완하였다. 또한, 예측대상종목의 정보들 외에도 장기적으로 높은 시계열 유사성을 보유한 종목들을 선발한 후 속성으로 사용하여 모형의 예측성능을 향상 시켰다. 구체적으로 1단계는 Johansen의 공적분 검정을 통하여 예측대상종목과 장기적 관계(long-term relationship)에 있는 종목을 추출하고, 2단계는 이 선발된 종목들과 예측대상종목의 시계열 정보 특성을 속성으로 구축한 인공 신경망으로 학습하여 관심 종목을 예측한다. 제안된 모델의 성능을 확인하기 위하여 KOSPI 지수의 방향성을 예측하는 시스템을 구현하였으며, 시가총액 상위 종목군을 대상으로 지수와의 공적분 검정을 하였다. 성능을 살펴보기 위하여 본 연구에서는 시계열 정보가 속성으로 반영된 단순 인공 신경망 모델, 공적분 검정을 통과한 종목들의 시계열 속성이 포함된 모델, 그리고 그 모델과 속성의 개수를 동일하게 하기 위하여 임의로 종목을 선택하여 이들의 시계열 속성이 포함된 모델을 구축하였다. 실험 결과 공적분 검정을 통과한 종목군의 속성이 결합된 모델은 단순 인공 신경망만으로 학습된 기존 모델에 비하여 평균적으로는 11.29% (최대 29.98%) 정확도가 향상되었고, 임의로 선택된 종목군의 속성이 결합된 모델에 비해서는 평균적으로는 10.59% (최대 25.78%) 가 향상된 예측 정확도를 보여주었다.

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.719-726
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• 2008

In this paper we consider a joint test for seasonal cointegrating(CI) ranks that enables us to simultaneously model cointegrated structures across seasonal unit roots in seasonal cointegration. A CI rank test for a single seasonal unit root is constructed and extended to a joint test for multiple seasonal unit roots. Their asymptotic distributions and selected critical values for the joint test are obtained. Through a small Monte Carlo simulation study, we evaluate performances of the tests.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.797-805
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• 2005

Multivariate unit root tests for the VAR(p) model have been commonly used in time series analysis. Several unit root tests were developed and recently Shin(2004) suggested a cointegration test based on weighted symmetric estimator. In this paper, we suggest a multivariate unit root test statistic based on the weighted symmetric estimator. Using a small simulation study, we compare the powers of the new test statistic with the statistics suggested in Shin(2004) and Fuller(1996).

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.501-522
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• 2007

We propose an estimation procedure that can be used for detecting structural changes in the seasonal cointegrated vector autoregressive model. The asymptotic properties of the estimates and the test statistics for the parameter change are provided. A simulation example is presented to illustrate this method and its concept.