• 제목/요약/키워드: , Stock Investment

검색결과 517건 처리시간 0.03초

한국 주식시장에서 마코위츠 포트폴리오 선정 모형의 입력 변수의 정확도에 따른 투자 성과 연구 (Investment Performance of Markowitz's Portfolio Selection Model over the Accuracy of the Input Parameters in the Korean Stock Market)

  • 김홍선;정종빈;김성문
    • 한국경영과학회지
    • /
    • 제38권4호
    • /
    • pp.35-52
    • /
    • 2013
  • Markowitz's portfolio selection model is used to construct an optimal portfolio which has minimum variance, while satisfying a minimum required expected return. The model uses estimators based on analysis of historical data to estimate the returns, standard deviations, and correlation coefficients of individual stocks being considered for investment. However, due to the inaccuracies involved in estimations, the true optimality of a portfolio constructed using the model is questionable. To investigate the effect of estimation inaccuracy on actual portfolio performance, we study the changes in a portfolio's realized return and standard deviation as the accuracy of the estimations for each stock's return, standard deviation, and correlation coefficient is increased. Furthermore, we empirically analyze the portfolio's performance by comparing it with the performance of active mutual funds that are being traded in the Korean stock market and the KOSPI benchmark index, in terms of portfolio returns, standard deviations of returns, and Sharpe ratios. Our results suggest that, among the three input parameters, the accuracy of the estimated returns of individual stocks has the largest effect on performance, while the accuracy of the estimates of the standard deviation of each stock's returns and the correlation coefficient between different stocks have smaller effects. In addition, it is shown that even a small increase in the accuracy of the estimated return of individual stocks improves the portfolio's performance substantially, suggesting that Markowitz's model can be more effectively applied in real-life investments with just an incremental effort to increase estimation accuracy.

한국 장단기 금융시장, 주식 및 외환시장 연관성 (Analysis about relation of Long-term & Short-term Financial Market, Stock Market and Foreign Exchange Market of Korea)

  • 김종권
    • 산업경영시스템학회지
    • /
    • 제22권50호
    • /
    • pp.105-125
    • /
    • 1999
  • The results of analysis on foreign exchange market, stock and financial market after January of 1997 are that foreign exchange market will be affected by stock and financial market volatility about 1999. This means that stock and financial market are more stable than foreign exchange market. This also is supported by ‘financial market forecast of 1999 in Daewoo Economic Research Institute’. After won/dollar (end of period) will be increasing in 1,430 at second quarter of 1999, this is to downward 1,200 fourth quarter of 1999. This is somewhat based on government's higher exchange rate policy. But, after yield of corporate bond is to 11.0% at first quarter of 1999, this will be stable to 10.2% at fourth quarter. During the first quarter of 1999, yield of corporate bond is to somewhat increasing through sovereign debt and public bonds, technical adjustment of interest rate. After this, yield of corporate bond will be stable according to stability of price, magnification of money supply, restucturing of firms. So, stock market is favorably affected by stability of financial market. But, the pension and fund of USA, i.e., long-term portfolio investment fund, are injected through international firm's management. It is included by openness of audit, fair market about foreign investors. Finally, Moody's strong rating on the won-denominated bonds suggest that Korea's sovereign debt ratings could be restored to an investment grade in the near future. It sequentially includes inflow of foreign portfolio investment fund, fall of won/dollar foreign exchange rate (appreciation of won) and stability of yield of corporate bond.

  • PDF

주가지수 선물의 가격 비율에 기반한 차익거래 투자전략을 위한 페어트레이딩 규칙 개발 (Developing Pairs Trading Rules for Arbitrage Investment Strategy based on the Price Ratios of Stock Index Futures)

  • 김영민;김정수;이석준
    • 산업경영시스템학회지
    • /
    • 제37권4호
    • /
    • pp.202-211
    • /
    • 2014
  • Pairs trading is a type of arbitrage investment strategy that buys an underpriced security and simultaneously sells an overpriced security. Since the 1980s, investors have recognized pairs trading as a promising arbitrage strategy that pursues absolute returns rather than relative profits. Thus, individual and institutional traders, as well as hedge fund traders in the financial markets, have an interest in developing a pairs trading strategy. This study proposes pairs trading rules (PTRs) created from a price ratio between securities (i.e., stock index futures) using rough set analysis. The price ratio involves calculating the closing price of one security and dividing it by the closing price of another security and generating Buy or Sell signals according to whether the ratio is increasing or decreasing. In this empirical study, we generate PTRs through rough set analysis applied to various technical indicators derived from the price ratio between KOSPI 200 and S&P 500 index futures. The proposed trading rules for pairs trading indicate high profits in the futures market.

Asymmetric Effects of Global Liquidity Expansion on Foreign Portfolio Inflows, Exchange Rates, and Stock Prices

  • Rhee, Dong-Eun;Yang, Da Young
    • East Asian Economic Review
    • /
    • 제18권2호
    • /
    • pp.143-161
    • /
    • 2014
  • This paper examines the effects of global liquidity expansion on advanced and emerging economies by using panel VAR methodology. The results show that global liquidity expansion tends to boost economy by increasing GDP growth and stock prices. However, we find that the effects are asymmetric. The effects of global liquidity on GDP and stock prices are greater and more persistent in emerging economies than in liquidity recipient advanced economies. Moreover, global liquidity appreciates emerging economies' exchange rates more persistently than those of advanced economies. Lastly, while global liquidity expansion increases foreign portfolio investment inflows to Asian countries and liquidity recipient advanced economies, there is no evidence for Latin American countries.

주식유통시장의 층위이동과 장기기억과정 (Level Shifts and Long-term Memory in Stock Distribution Markets)

  • 정진택
    • 유통과학연구
    • /
    • 제14권1호
    • /
    • pp.93-102
    • /
    • 2016
  • Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.

외국인직접투자, 경제성장, 환경규제의 관계분석 : 규모효과와 기술효과를 중심으로 (The Linkage of Foreign Direct Investment, Economic Growth, and Environmental Regulations : Scale Effect and Technique Effect)

  • 김광욱;강상목
    • 자원ㆍ환경경제연구
    • /
    • 제18권3호
    • /
    • pp.523-544
    • /
    • 2009
  • 본 연구는 목적은 내생적 환경정책모형(endogenous environmental policy)에 기초하여 외국인직접투자(foreign direct investment), 경제성장, 환경규제의 상호관계를 실증적으로 분석하는 것이다. 외국인자본비율의 1% 증가는 0.044%(고정효과), 0.047%(확률효과)의 경제성장효과를 유발하였으며, 노동자 1인당 생산량의 1% 증가는 2.038%(고정효과), 1.890%(확률효과)의 환경규제강화를 유도하는 것으로 계측되었다. 그러나 생산 과정에 있어 강력한 환경규제가 기술혁신의 유인으로 작용한다는 포터의 가설(Porter's theory)을 지지할 만한 실증결과는 보여주지 못하였다. 또한 2개의 대기오염물질 (NOx, $CO_2$)을 기준으로 규모효과(0.0119, 0.0172)가 기술효과(-0.0048, -0.0007)보다 크게 추정되었다. 이는 국제사회의 꾸준한 노력에도 불구하고 더욱 적극적인 환경보호를 위해 각국의 공공지출액을 증액시킬 필요성이 있음을 의미한다.

  • PDF

천연가스산업 연구개발 투자 평가 연구 (An Empirical Study of Ramp;D Investment Assessment in Natural Gas Industry)

  • 박승민;오경준
    • 한국가스학회지
    • /
    • 제4권4호
    • /
    • pp.34-41
    • /
    • 2000
  • 본 연구에서는 기업의 연구개발 의사결정을 위한 정보 도출을 위한 연구방법론을 설정하고, 한국가스공사의 연구개발 부문을 대상으로 기술 그룹별 연구개발 니드, 기술 파급도, 기술스톡을 추정하여, 연구개발 투자의 적정성을 평가하고자 하였다 연구개발 투자 평가 결과, 한국가스공사의 연구개발 투자는 설비 보수 및 운영 부문에 집중되어 있으며, 비교적 기술 파급도가 높고 연구개발 니드 충족도가 큰 연구과제의 기술스톡 수준이 높은 것으로 분석되었다.

  • PDF

The relationship between audit quality and Investment efficiency

  • Dashtbayaz, Mahmoud Lari;Mohammadi, Shaban
    • 융합경영연구
    • /
    • 제4권2호
    • /
    • pp.20-32
    • /
    • 2016
  • The purpose of the present study is to investigate the audit quality and Investment efficiency of the listed companies on the Tehran Stock Exchange (TSE). The population includes 94 firms selected through systematic sampling. The data is collected from the audited financial statements of the firms provided by TSE's website from 2008 to 2015. In this study the variables, auditor industry specialization, auditor reputation, auditor tenure and auditor independence has been used to investigate audit quality. The results of multiple linear regression analysis show that there is a significant relationship audit quality and Investment efficiency.

기계학습을 활용한 상품자산 투자모델에 관한 연구 (A Study on Commodity Asset Investment Model Based on Machine Learning Technique)

  • 송진호;최흥식;김선웅
    • 지능정보연구
    • /
    • 제23권4호
    • /
    • pp.127-146
    • /
    • 2017
  • 상품자산(Commodity Asset)은 주식, 채권과 같은 전통자산의 포트폴리오의 안정성을 높이기 위한 대체투자자산으로 자산배분의 형태로 투자되고 있지만 주식이나 채권 자산에 비해 자산배분에 대한 모델이나 투자전략에 대한 연구가 부족한 실정이다. 최근 발전한 기계학습(Machine Learning) 연구는 증권시장의 투자부분에서 적극적으로 활용되고 있는데, 기존 투자모델의 한계점을 개선하는 좋은 성과를 나타내고 있다. 본 연구는 이러한 기계학습의 한 기법인 SVM(Support Vector Machine)을 이용하여 상품자산에 투자하는 모델을 제안하고자 한다. 기계학습을 활용한 상품자산에 관한 기존 연구는 주로 상품가격의 예측을 목적으로 수행되었고 상품을 투자자산으로 자산배분에 관한 연구는 찾기 힘들었다. SVM을 통한 예측대상은 투자 가능한 대표적인 4개의 상품지수(Commodity Index)인 골드만삭스 상품지수, 다우존스 UBS 상품지수, 톰슨로이터 CRB상품지수, 로저스 인터내셔날 상품지수와 대표적인 상품선물(Commodity Futures)로 구성된 포트폴리오 그리고 개별 상품선물이다. 개별상품은 에너지, 농산물, 금속 상품에서 대표적인 상품인 원유와 천연가스, 옥수수와 밀, 금과 은을 이용하였다. 상품자산은 전반적인 경제활동 영역에 영향을 받기 때문에 거시경제지표를 통하여 투자모델을 설정하였다. 주가지수, 무역지표, 고용지표, 경기선행지표 등 19가지의 경제지표를 이용하여 상품지수와 상품선물의 등락을 예측하여 투자성과를 예측하는 연구를 수행한 결과, 투자모델을 활용하여 상품선물을 리밸런싱(Rebalancing)하는 포트폴리오가 가장 우수한 성과를 나타냈다. 또한, 기존의 대표적인 상품지수에 투자하는 것 보다 상품선물로 구성된 포트폴리오에 투자하는 것이 우수한 성과를 얻었으며 상품선물 중에서도 에너지 섹터의 선물을 제외한 포트폴리오의 성과가 더 향상된 성과를 나타남을 증명하였다. 본 연구에서는 포트폴리오 성과 향상을 위해 기존에 널리 알려진 전통적 주식, 채권, 현금 포트폴리오에 상품자산을 배분하고자 할 때 투자대상은 상품지수에 투자하는 것이 아닌 개별 상품선물을 선정하여 자체적 상품선물 포트폴리오를 구성하고 그 방법으로는 기간마다 강세가 예측되는 개별 선물만을 골라서 포트폴리오를 재구성하는 것이 효과적인 투자모델이라는 것을 제안한다.

빅데이터를 활용한 인공지능 주식 예측 분석 (Stock prediction analysis through artificial intelligence using big data)

  • 최훈
    • 한국정보통신학회논문지
    • /
    • 제25권10호
    • /
    • pp.1435-1440
    • /
    • 2021
  • 저금리 시대의 도래로 인해 많은 투자자들이 주식 시장으로 몰리고 있다. 과거의 주식 시장은 사람들이 기업 분석 및 각자의 투자기법을 통해 노동 집약적으로 주식 투자가 이루어졌다면 최근 들어 인공지능 및 데이터를 활용하여 주식 투자가 널리 이용되고 있는 실정이다. 인공지능을 통해 주식 예측의 성공률은 현재 높지 않아 다양한 인공지능 모델을 통해 주식 예측률을 높이는 시도를 하고 있다. 본 연구에서는 다양한 인공지능 모델에 대해 살펴보고 각 모델들간의 장단점 및 예측률을 파악하고자 한다. 이를 위해, 본 연구에서는 주식예측 인공지능 프로그램으로 인공신경망(ANN), 심층 학습 또는 딥 러닝(DNN), k-최근접 이웃 알고리즘(k-NN), 합성곱 신경망(CNN), 순환 신경망(RNN), LSTM에 대해 살펴보고자 한다.