• Title/Summary/Keyword: returns

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What Drives the Stock Market Comovements between Korea and China, Japan and the U.S.?

  • Lee, Jinsoo;Yu, Bok-Keun
    • KDI Journal of Economic Policy
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    • 제40권1호
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    • pp.45-66
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    • 2018
  • This paper measures the extent of comovements in stock returns between Korea and three major countries (China, Japan and the U.S.) using industry-level data for Korea from 2003 to 2016 in the spirit of the international capital asset pricing model. It also examines what drives the comovements between Korea and the three countries. We find that the comovements of Korean stock returns with those of the U.S. and Japan became smaller after the global financial crisis. In contrast, the comovement in stock returns between Korea and China became larger after the crisis. After an additional analysis, we conclude that trade linkage is the main driver of the comovements between Korea and the three countries.

주식분할의 장기성과 측정 모델에 대한 연구 (A Study about Measurement Model of Long Term Performance in Stock Split)

  • 신연수
    • 정보학연구
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    • 제9권3호
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    • pp.77-89
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    • 2006
  • The event study analyzes returns around event date at a time. Event study provides estimation periods and cumulative returns. Stock split announcements are generally associated with positive abnormal returns. It is important to investigate the responses of stocks to new information contained in the announcements of stock splits. So It is important to study the long term performance in the case of Stock Split. This Study forced to two approach method in evaluating the performance, the event time portfolio approach and calendar time portfolio approach. The event time portfolio approach exists the CAR model, BHAR model and WR model. And the calendar time portfolio approach has the 3 factor model, 4 factor model, CTAR model, and RATS model.

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신경망을 이용한 산업주가수익율의 예측 (Industry Stock Returns Prediction Using Neural Networks)

  • 권영삼;한인구
    • Asia pacific journal of information systems
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    • 제9권3호
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    • pp.93-110
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    • 1999
  • The previous studies regarding the stock returns have advocated that industry effects exist over entire industry. As the industry categories are more rigid, the demand for predicting the industry sectors is rapidly increasing. The advances in Artificial Intelligence and Neural Networks suggest the feasibility of a valuable computational model for stock returns prediction. We propose a sector-factor model for predicting the return on industry stock index using neural networks. As a substitute for the traditional models, neural network model may be more accurate and effective alternative when the dynamics between the underlying industry features are not well known or when the industry specific asset pricing equation cannot be solved analytically. To assess the potential value of neural network model, we simulate the resulting network and show that the proposed model can be used successfully for banks and general construction industry. For comparison, we estimate models using traditional statistical method of multiple regression. To illustrate the practical relevance of neural network model, we apply it to the predictions of two industry stock indexes from 1980 to 1995.

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The Impact of Global Financial Crisis 2008 on Amman Stock Exchange

  • Ajlouni, Moh'd Mahmoud;Mehyaoui, Wafaa;Hmedat, Waleed
    • 유통과학연구
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    • 제10권7호
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    • pp.13-22
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    • 2012
  • The effect of the September 2008 global financial crisis weighed heavily on stock markets around the world. The purpose of this study is to empirically investigate the impact of the crisis on Amman Stock Exchange. Event study methodology has been adopted on a period of 24 months, from January 2008 to December 2009. Monthly average abnormal returns across a sample of 52 industrial and services companies have been tested separately. The results reveal that Amman Stock Exchange experienced significant negative abnormal returns in the fourth quarter of the year 2008. However, there were no significant abnormal returns observed thereafter. This means that Amman Stock Exchange managed to overcome its adverse consequences. Since the event study tests for market efficiency, as well, the results show that Amman Stock Exchange reaction is consistent with the semi-strong form of the efficient market hypothesis.

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An Empirical Investigation on the Interactions of Foreign Investments, Stock Returns and Foreign Exchange Rates

  • Kim, Yoon-Tae;Lee, Kyu-Seok;Shin, Dong-Ho
    • Communications for Statistical Applications and Methods
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    • 제9권1호
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    • pp.141-154
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    • 2002
  • Foreign investors'shares and their influences on the Korean stock market have never been larger and greater before since the market was completely open to foreign investors in 1992 Quantitatively and qualitatively as well, as a result, changes in the patterns of foreign investments have caused enormous effects on the interactions of major macroeconomic indices of the Korean economy. This paper is intended to investigate the causal relations of the four variables, foreigners'buy-sell ratios, stock returns, ₩/$ exchange rates and $\yen$/$ exchange rates, over the two time periods of the pre-IMF (1996.1.1-1997.8.15) and the post-IMF (1997.8.16-2000.6.15) based on the daily data of the variables. Granger Causality Test, Forecast Error Variance Decomposition(FEVD) using VAR model and Impulse Response Function were implemented for the empirical analysis.

Stationary Bootstrap Prediction Intervals for GARCH(p,q)

  • Hwang, Eunju;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • 제20권1호
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    • pp.41-52
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    • 2013
  • The stationary bootstrap of Politis and Romano (1994) is adopted to develop prediction intervals of returns and volatilities in a generalized autoregressive heteroskedastic (GARCH)(p, q) model. The stationary bootstrap method is applied to generate bootstrap observations of squared returns and residuals, through an ARMA representation of the GARCH model. The stationary bootstrap estimators of unknown parameters are defined and used to calculate the stationary bootstrap samples of volatilities. Estimates of future values of returns and volatilities in the GARCH process and the bootstrap prediction intervals are constructed based on the stationary bootstrap; in addition, asymptotic validities are also shown.

Efficiency and Returns to Scale in the Bangladesh Banking Sector: Empirical Evidence from the Slack-Based DEA Method

  • Sufian, Fadzlan;Kamarudin, Fakarudin
    • 아태비즈니스연구
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    • 제5권1호
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    • pp.1-11
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    • 2014
  • The study provides new empirical evidence on the level of profit efficiency and returns to scale of the Bangladesh banking sector. We employ the Slack-Based Data Envelopment Analysis (SBM-DEA) method to assess the level of profit efficiency of individual banks over the years 2004 to 2011. The empirical findings indicate that the Bangladesh banking sector has exhibited the highest and lowest level of profit efficiency during years 2004 and 2011 respectively. We find that only eight banks have been profit efficient throughout the period under study. The empirical findings seem to suggest that most of the Bangladesh banks have been experiencing economies of scale due to being at less than the optimum size, or diseconomies of scale due to being at more than the optimum size. Thus, decreasing or increasing the scale of production could result in cost savings or efficiencies.

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Mutual Fund 수익률의 비정상 함수형 시그널을 위한 다해상도 클러스터 계층구조 (Multi-scale Cluster Hierarchy for Non-stationary Functional Signals of Mutual Fund Returns)

  • 김대룡;정욱
    • 경영과학
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    • 제24권2호
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    • pp.57-72
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    • 2007
  • Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

SVM 커널함수의 파라미터 값에 따른 능동소나 표적신호의 식별 성능 분석 (Analysis of target classification performances of active sonar returns depending on parameter values of SVM kernel functions)

  • 박정현;황찬식;배건성
    • 한국정보통신학회논문지
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    • 제17권5호
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    • pp.1083-1088
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    • 2013
  • 수중 천해 환경에서 능동소나의 반향 신호로 기뢰를 탐지 및 식별하는 일은 복잡한 해양 환경의 영향으로 어려운 문제이다. SVM은 패턴인식 문제에서 최적의 해를 제공하는 이진 분류기이다. 본 논문에서는 SVM을 이용하여 능동소나의 반향 데이터로 기뢰와 같은 금속 물체와 바위를 식별하는 실험을 수행하면서, SVM에 사용되는 커널함수의 파라미터 값의 변화에 따른 식별 성능을 분석하고 제시하였다.

R&D 및 불완전경쟁과 경제성장 (R&D Activities, Imperfect Competition and Economic Growth)

  • 김병우
    • 기술혁신학회지
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    • 제10권1호
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    • pp.47-72
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    • 2007
  • 아이디어는 소멸하지 않으며 지식생산과정에 수확체감의 법칙이 작용하지도 않는다. 그럼에도 불구하고, 사적측면만을 고려하는 단순한 내생적 성장모형에서는 지속적 경제성장이 달성되지 않게 된다. 그러나, 지식자본의 비전유성을 고려하여 이를 공적자본으로 간주하게 되면 지속적 경제성장은 달성될 수 있게 된다. 우리 경제에 대한 실증분석 결과가 지식의 공적자본으로서의 성격을 강하게 뒷받침함을 확인할 수 있다. 즉, 제품혁신 생산함수에 대한 모든 함수형태에서 지식자본이 사적재화라는 귀무가설을 모두 기각할 수 있다. 이상의 결과로부터 우리 경제는 제품혁신을 통해 지속적 경제성장을 달성할 수 있다는 시사점을 얻을 수 있다.

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