가스, 전력 산업의 자기자본 beta 추정의 적정성 분석

DC Field Value Language
dc.contributor.advisor최기련-
dc.contributor.author김용수-
dc.date.accessioned2018-10-16T02:15:15Z-
dc.date.available2018-10-16T02:15:15Z-
dc.date.issued2007-02-
dc.identifier.other1896-
dc.identifier.urihttps://dspace.ajou.ac.kr/handle/2018.oak/2055-
dc.description학위논문(석사)--아주대학교 일반대학원 :에너지학과,2007.2-
dc.description.abstractThe efficiency in resources allocation is generally achieved through competitive market. When there exist natural monopolies in the sectors of gas and electricity due to their own characteristics, however, the Government tends to play on some regulations for economic efficiency. The gas and electricity industries are regulated through energy pricing policies, which has not only a great deal of impacts on the business' profitability, but on the entire national economy. Therefore, predictable pricing structure and costing mechanism are highly significant. So far, the existing regulation onto the industries put by the regulatory authority has been by means of the ROR (rate of return)-determining method by applying the "fixed deposit interest rate" or "the 2% premium plus fixed deposit interest rate". As competition introduced through the restructuring in the sectors of gas and electricity gradually tends to increase market risks and the individual business' stocks listed on the capital markets are assessed by the ordinary investors, the Government faces the need for introducing the CAPM (Capital Asset Pricing Model), to determine the ROR for the sectors of gas and electricity. CAPM, an estimation method for capital cost, depends on demand & supply in the capital market and on beta, a relative risk of relevant asset. That is to say, the ROE determination is made by the market, not by the regulatory authority or the utility businesses of the sectors. As CAPM means a transition to market-based evaluation from the existing artificial regulation, it essentially entails problems, such as asymmetric risk due to the regulation, adjustment of difference between the private and social discount rates, and its own unrealistic assumptions. As in CAPM the level of the entire market risk is expressed as beta, the determination of ROE for the sectors of gas and electricity, after all, might be an estimation of beta, the most essential and important variable. This study tests the stability within 95% confidence interval by estimating the equity beta with daily stock prices of the individual companies of the sectors during the period 2001-2005. It also studies the foreign countries' examples and other industries for the optimal level of equity beta. The study concludes as follows: First, stability tests of the recursive beta values estimated in the sectors of gas and electricity during the entire period (2001~2005) shows only the electricity industry is stable within 95% confidence interval while the gas industry on the most confidence nterval is too unstable to rely. Therefore, the direct use of market beta for the gas sector without adjustment may lead to a wrong analysis of the expected ROR due to the beta estimation with the unstable data. Second, the beta estimate of the gas and electricity industries for the 5 periods holds 0.588 in average, which reaches the 63.4% level of 0.927, the total market industries. Especially, the beta (0.399) for gas takes 43% level that is so far from the market average, and estimated to low compared with the same industries of the foreign countries. Therefore, it may not be seen that the normal market-based evaluation has been accomplished. Third, in terms of the shares for systematic/unsystematic risks of the total risks, the average estimate for the total market industries gives 52.4%/47.6% while electricity 29.4%/70.6% and gas 12.9%/87.1% which may be too excessive. Therefore, the ROR regulation could constrain the systematic risk, with the unsystematic risk relatively expanded. Lastly, the ROR according to market-beta-based CAPM estimates 40% and 31% lower respectively, when compared with DCF(Discounted Cash Flow)/ROE(Rate of Equity) method. Therefore, These lower values may result in the minimum ROR estimated. The demonstration analysis of this study comes up with the result that the equity betas for gas and electricity have a lot of estimation errors and regulatory unsystematic risks. As unsystematic risks, as in the assumption of CAPM, can not be dissolved with diversified investment, upward beta method or adjusted leverage beta method applied to the optimal debt/equity ratio has been taken by other countries' regulatory authorities that use CAPM approaches. Summing up, for the domestic gas and electricity industries that just starts to introduce CAPM approach, it may be the most reliable beta estimation method to determine ROR by applying the industry characteristics weight to the beta values estimated from the capital market, just like Blume beta and leverage beta, and with other industries and the related foreign cases taken into full consideration.-
dc.description.tableofcontents제1장 서론 = 1 제1절 연구의 목적 및 배경 = 1 제2절 선행연구 검토 및 논문의 구성 = 3 1. 선행연구 및 문헌검토 = 3 2. 논문의 구성 = 4 제2장 투자수익률의 결정과 자기자본수익률추정방식 = 6 제1절 투자수익률의 결정시 고려사항 = 6 1. 사회적 할인율과 사적 할인율의 차이 = 6 2. 가스,전력 규제산업의 특성 = 7 3. 요금규제 = 8 4. 수익률 규제의 비대칭위험(Asymmetric risks) = 13 제2절 자기자본수익률추정방식 = 14 1. 자본자산가격결정모형(CAPM) = 15 2. 할인현금흐름모형(DCF) = 15 3. 외국 산업의 자기자본수익률적용사례 = 16 제3장 CAPM 이론과 beta 추정모형 = 20 제1절 CAPM 이론 = 20 1. CAPM 이론 = 20 2. CAPM beta 추정의 어려움 = 23 제2절 beta 추정모형 = 25 1. 증권시장선과 beta = 25 2. 단일지수모형 beta = 27 3. 조정(Adjusted) beta = 28 제3절 시장 위험크기와 beta의 안정성 검정 = 29 1. 시장 위험크기 = 29 2. beta 의 안정성 검정 = 31 제4장 가스, 전력 산업의 beta추정 실증분석 = 33 제1절 가스, 전력 산업의 beta 추정 및 안정성 검정 = 33 1. 가스,전 력산업 기업별 베타 및 안정성 검정 = 33 2. 각 업종별 beta 추정 및 비교분석 = 35 3. 외국 가스, 전력기업 베타 비교 = 39 제2절 가스, 전력 산업의 시장위험크기 및 조정베타 = 40 1. 기업별 시장위험크기 측정 = 40 2. 수익률 비교(CAPM/DCF/ROE) = 45 3. 조정베타(Adjusted beta) = 47 제5장 결론 = 53 참고문헌 = 56 Abstract = 58 부록 61-
dc.language.isokor-
dc.publisherThe Graduate School, Ajou University-
dc.rights아주대학교 논문은 저작권에 의해 보호받습니다.-
dc.title가스, 전력 산업의 자기자본 beta 추정의 적정성 분석-
dc.title.alternativeKim, Young-Soo-
dc.typeThesis-
dc.contributor.affiliation아주대학교 일반대학원-
dc.contributor.alternativeNameKim, Young-Soo-
dc.contributor.department일반대학원 에너지학과-
dc.date.awarded2007. 2-
dc.description.degreeMaster-
dc.identifier.localId565773-
dc.identifier.urlhttp://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000001896-
dc.subject.keywordCAPM(Capital Asset Pricing Model)-
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Graduate School of Ajou University > Department of Energy Systems > 3. Theses(Master)
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