• Title/Summary/Keyword: 비대칭성 변동성

Search Result 114, Processing Time 0.02 seconds

Financial Structure, Ownership, and Corporate Control (기업의 소유구조 및 지배력과 재무구조)

  • Rhieu, Sang-Yup;Cheong, Ki-Moon
    • Korean Business Review
    • /
    • v.11
    • /
    • pp.195-216
    • /
    • 1998
  • Ownership of an asset can be identified with the right to exercise "residual control" where the contract is silent about decision rights, or with the right to receive any "residual returns" that remain after contractual. obligations are fulfilled. Although the concept of "ownership" seems reasonably clear in many of the cases, the concepts of residual control and the residual returns that define ownership are actually quite elusive. For large corporations, there is really no single individual who owns both the residual returns and the residual control. Despite the limited qualifications, ownership is clearly. the most common and effective meas to motivate people to create, maintain, and improve the value of assets. In this paper, we try to clarify the relationships among financial structure, ownership, and corporate control with the concept of ownership defined as the residual control and the residual returns, Financial securities are not just claims to part of a firm's net income. They give the security holder certain rights. A careful matching of rights of control and returns can create incentives that increase total value of the firms. In the corporate firms, managers, lenders, and shareholders have different interests. And the financial structure affects how different those interests are and what decisions management will make. Managers are, in general, better informed than investors about the firm's prospects. The financial decisions by managers may affect investors' beliefs and, therefore, the price of shares and the value of the firm.

  • PDF

Risk Spillover between Shipping Company's Stock Price and Marine Freight Index (해운선사 주가와 해상운임지수 사이의 위험 전이효과)

  • Choi Ki-Hong
    • Journal of Korea Port Economic Association
    • /
    • v.39 no.1
    • /
    • pp.115-129
    • /
    • 2023
  • This study analyzed the risk spillover of BDI on shipping company stock prices through the Copula-CoVaR method based on daily data from January 4, 2010, to October 31, 2022. The main empirical analysis results and policy implications are as follows. First, copula results showed that there was a weak dependence between BDI and shipping company stock prices, and PAN, KOR, and YEN were selected as the most fitting model for dynamic Student-t copula, HMM was selected as the rotated Gumbel copula, and KSS was selected as the best model. Second, in the results of CoVaR, it was confirmed that the upside (downside) CoVaR was significantly different from the upside (downside) VaR in all shipping companies. This means that BDI has a significant risk spillover on shipping companies. In addition, as for the risk spillover, the downside risk is generally lower than the upside risk, so the downside and upside risk spillover were found to be asymmetrical. Therefore, policymakers should strengthen external risk supervision and establish differentiated policies suitable for domestic conditions to prevent systematic risks from BDI shocks. And investors should reflect external risks from BDI fluctuations in their investment decisions and construct optimal investment portfolios to avoid risks. On the other hand, investors propose that the investment portfolio should be adjusted in consideration of the asymmetric characteristics of up and down risks when making investment decisions.

Determinants of Capital Structure in KOSDAQ Firms (코스닥 기업의 자본구조 결정요인: 동태적 자본구조 모형을 중심으로)

  • Son, Seung-Tae;Lee, Yoon-Goo
    • The Korean Journal of Financial Management
    • /
    • v.24 no.1
    • /
    • pp.109-147
    • /
    • 2007
  • According to the perspective of capital structure theory, we analyzed the dynamism of the capital structure determinants by using panel data of 244 KOSDAQ firms based on two-step GMM system methodology suggested by Blundell Bond(1998). This dynamic methodology had not been used to analyse capital structure determinants in Korea. In the dynamic model of capital structure, profit had negative effect on the book leverage and market leverage, which meant supporting pecking order theory. Growth opportunity (MBR) affected negatively to the market leverage. For the determinants of leverage, earnings volatility had significantly positive effect on KOSDAQ 50 firms. KOSDAQ and KOSDAQ 50 firms had the target leverage. The adjustment speed in KOSDAQ firms was 0.4958 on the book leverage, it was faster than in KOSDAQ 50 firm's 0.2863 on the book leverage and the adjustment speeds for the market leverage were 0.7651 for KOSDAQ firms and 0.5643 for KOSDAQ 50 firms. There was difference in adjustment cost between KOSDAQ firms and KOSDAQ 50 firms.

  • PDF

Research on the Application Methods of Big Data within SME Financing: Big data from Trading-area (소상공인의 자금공급 확대를 위한 빅데이터 활용 방안연구)

  • Lee, Ju Hee;Dong, Hak Lim
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
    • /
    • v.13 no.3
    • /
    • pp.125-140
    • /
    • 2018
  • According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.