• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.2
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• pp.63-73
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• 2016

In these days startup became one of the most hot issue in business world. The problem is many startup couldn't overcome the valley of death. For this reason many startup want to funded by venture capital. However startup's business is trade secret itself, so they have to make strategic approach to venture capital. The purpose of study is to find the way to make strategic decision for startup. By analyzing the relation between startup's characteristic and venture capital's investment portfolio. Four famous venture capital(Sequoia capital, Lightspeed venture, Firstround and Khosla venture) and their seed invested startup Dropbox, Airbnb, Snapchat, Uber and Instacart was selected for this study. As a result, each venture capital has their own invest category characteristic and their seed funding belong to their category. Moreover, between seed funded startup and 36,4% of 244 past invented company shown vertical relationship, beside 0.5% of past 244 invested company shown horizontal relationship. This result shown the importance of the relation between startup's characteristic and venture capital's portfolio. Startup have to check the venture capital's portfolio for the strategic approach for funding and venture capital have to make mutual positive portfolio for decreasing the risk.

• Venture DIGEST
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• s.119
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• pp.8-11
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• 2008

창원에 위치한 일림나노텍(주)은 20년이 넘는 세월동안 소형정밀 기계 및 부품 사업 분야에서 입지를 굳혀왔다. 4반세기를 앞두고 차세대 정밀기계산업 분야에 새로운 도전장을 내민 박효찬 대표를 만나 그의 사업과 경영 이야기를 듣는다.

• Venture DIGEST
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• s.94
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• pp.8-11
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• 2006

보안장비 시장에서 매년 눈부신 성과를 갱신하고 있는 아이디스. 단 1초의 오차도 허용하지 않으며, 신뢰 없이는 존재조차 불가능하다는 까다로운 보안장비 업계를 평정함으로써 또 하나의 벤처신화를 만들어내고 있다. 365일 지구촌 곳곳에서 쉬지 않고 돌아가는 DVR은 아이디스의 끈기와 승부근성을 닮았다.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.137-152
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• 2014

In this paper, I suggest several techniques to estimate covariance matrix and compare the performance of the global minimum variance portfolio (GMVP) in terms of out of sample mean standard deviation and return. As a result, the return differences among the GMVPs are insignificant. The mean standard deviation of the GMVP using historical covariance is sensitive to the estimation window and the number of assets in the portfolio. Among the model covariance, the GMVP using constant systematic risk ratio model or using short sale restriction shows the best performance. The performance difference between the GMVPs using historical covariance and model covariance becomes insignificant as the historical covariance is estimated with longer estimation window. Lastly, the implied volatilities from ELW prices do not lead to superior performance to the historical variance.

• Korean Management Science Review
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• v.25 no.3
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• pp.59-72
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• 2008

This paper proposes an R&D opportunity scan framework for information and telecommunications company in aging society. The framework consists of trend analysis, market-oriented search, technology-oriented search, and R&D Portfolio development. We identify technology themes in the market-oriented search by developing market scenarios and analyzing a new business model framework. And then we search prospective technologies in the technology-oriented recess by technology scanning and patent analysis. By matching technology themes with prospective technologies, generate an R&D portfolio. Finally, we evaluate the risk of the proposed R&D portfolio.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.63-71
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• 2009

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk. The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic programming problem. Since it is now computationally practical to solve the model, a number of alternative models to overcome this complexity have been proposed. In this paper, among the alternatives, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we developed an algorithm to obtain an optimal portfolio from the MAD model. We showed mathematically that the algorithm can solve the problem to optimality. We tested it using the real data from the Korean Stock Market. The results coincide with our expectation that the method can solve a variety of problems in a reasonable computational time.

• International Area Studies Review
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• v.20 no.4
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• pp.121-145
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• 2016

The purpose of this study is to identify the strategy of alliance portfolio and to compare the firm's characteristics and internal capabilities of each strategy for the successful utilization of alliance. We conducted a cluster analysis and ANOVA on 477 samples, which have alliance experience among the manufacturers responding to the Business Survey by Statistical Office in both 2012 and 2013. As a result of the analysis, it was found that firms have alliance portfolio based on strategy such as exploration, exploitation, and ambidextrity. There are statistically significant differences in the number of patents, technology capability, marketing capability, and global capability among the alliance portfolio strategy type.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.122-129
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• 2009

Strategic planning is an essential function of senior management in any business firm. Planning involves the firm's behavior in an competitive market and adaptation of the company's resources towards the selected market strategy. This study presents a methodological procedure for strategic planning in global top-tier construction firms. This procedure consists of the following stages. First, analyzed growth of revenue in which weight of total construction firms' revenue shown in Global Top 225 Contractors(ENR). Second, analyzed specialty of construction products. The products are General Building, Power, Water Supply, Industrial/Petroleum Process, and Transportation. Third, analyzed business the portfolio plan. The business portfolio plan includes both local/overseas market and specification/diversification of construction products. It affects the subsequent choice of a benchmarking for development of each construction company. The choice of the benchmarking firm, among several available alternatives, should follow a careful analysis of the characteristics and benefits inherent in the implementation of each.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.135-145
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• 2020

This paper provides the practical application of a linear shrinkage framework on Vietnam stock market. The cumulative data points observed in this analysis are 468 weeks from January 2011 to December 2019. All the companies listed on Ho Chi Minh City Stock Exchange (HOSE), except the companies under two years period from Initial Public Offering (IPO), are considered. The cumulative number of stocks picked is therefore 350 companies. The VNINDEX, which is the Vietnam Stock Index, is used as a reference index for shrinking to a single-index model. The empirical results show that the shrinkage of covariance matrix for portfolio optimization gives the promising results for the investors on Vietnam stock market. The shrinkage method helps the investors to produce the optimal portfolio in the sense of having higher profit with lower levels of risk compared to the portfolio of the traditional SCM method. Moreover, the portfolio turnover of shrinkage method is always kept at low magnitudes, and this makes the shrinkage portfolios save much transaction costs and reduce the liquidity risks in the trading process. In addition, the ability of shrinkage method in making profit is once again confirmed by the Alpha coefficient that achieves a high positive value.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.44-51
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• 2016

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users' sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.