• Journal of the Korean Data and Information Science Society
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• 제20권6호
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• pp.1213-1223
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• 2009

In this paper, we develop noninformative priors for two parameter Pareto distribution. Specially, we derive Jereys' prior, probability matching prior and reference prior for the parameter of interest. In our case, the probability matching prior is only a first order matching prior and there does not exist a second order matching prior. Some simulation reveals that the matching prior performs better to achieve the coverage probability. A real example is also considered.

• Journal of the Korean Data and Information Science Society
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• 제22권2호
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• pp.361-369
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• 2011

In this paper, we develop the reference and the matching priors for the reliability function of two-parameter exponential distribution. We derive the reference priors and the matching prior, and prove the propriety of joint posterior distribution under the general prior including the reference priors and the matching prior. Through the sim-ulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

• 대한토목학회논문집
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• 제29권6D호
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• pp.727-736
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• 2009

사회기반시설물을 관리주체의 자산으로 인식하여 관리자뿐만 아니라 사용자 측면에서의 만족도에 대한 고려를 바탕으로 효율적으로 관리하고자하는 노력이 진행 중이다. 사회기반시설물의 자산관리체계 지원을 위하여 교량 자산관리 방안을 수립하였다. 교량 자산관리와 관련된 국내외 현황분석을 수행하고 교량 자산관리 절차를 제안하였다. 제안된 절차의 주요 기능을 정의하고 각 기능에 대한 정식화를 수행하였다. 교량의 서비스수준을 설정하고 정략적 평가를 위한 성능척도를 정의하였으며, LOS를 정식화하고 교량별 중요도에 따른 가중치를 고려하여 보다 실제적인 LOS의 평가가 가능하도록 하였다. 교량의 자산관리를 위한 장기 전략수립과 단기 계획수립 방법을 제안하고, 효율성지수를 도입하여 우선순위 산정을 위한 지표로 제시하였다. 또한 예산의 수립과 배정 문제를 순위최적화 문제로 정식화하여 자산관리 정책과 목표에 따라 다양한 의사결정을 지원할 수 있는 체계를 구축하였다.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.757-764
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• 2010

In this paper, we develop the reference priors for the common location parameter in the half-normal distributions with unequal scale paramters. We derive the reference priors as noninformative prior and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.825-835
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• 2004

In this paper, we investigate the estimation of the value at risk(VaR) when stock prices are subjected to price limits. The mixture of probability mass functions and beta density functions is proposed to derive the distribution of asset returns. The analyses of real data show that the proposed distribution is appropriate to explain the VaR when the price limits exist in the data.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1409-1418
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• 2008

In this paper, we develop the reference priors for the common location parameter in two parameter exponential distributions. We derive the reference priors and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.

• The Journal of Asian Finance, Economics and Business
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• 제5권3호
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• pp.19-29
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• 2018

This research examined the alternatives of Jensen's alpha (α) estimation models in the Capital Asset Pricing Model, discussed by Treynor (1961), Sharpe (1964), and Lintner (1965), using the robust maximum likelihood type m-estimator (MM estimator) and Bayes estimator with conjugate prior. According to finance literature and practices, alpha has often been estimated using ordinary least square (OLS) regression method and monthly return data set. A sample of 50 securities is randomly selected from the list of the S&P 500 index. Their daily and monthly returns were collected over a period of the last five years. This research showed that the robust MM estimator performed well better than the OLS and Bayes estimators in terms of efficiency. The Bayes estimator did not perform better than the OLS estimator as expected. Interestingly, we also found that daily return data set would give more accurate alpha estimation than monthly return data set in all three MM, OLS, and Bayes estimators. We also proposed an alternative market efficiency test with the hypothesis testing Ho: α = 0 and was able to prove the S&P 500 index is efficient, but not perfect. More important, those findings above are checked with and validated by Jackknife resampling results.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.329-340
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• 2020

This study investigates the effect of capital structure on the financial performance of pharmaceutical enterprises which are listing on Vietnam's stock market. The study builds the regression using ROE as dependent variable and four independent variables, including self-financing, financial leverage, long-term asset and debt to assets ratios. In addition, we use other variables as controlling ones, such as firm size, fixed asset rate and growth. We collect data for the period from 2015 to 2019 of all 30 pharmaceutical enterprises which are currently listing on Vietnam's stock market. The least square regression (OLS) is used to test the effect of capital structure to the firms' financial performance. The analysis results show that the financial leverage ratio (LR), long-term asset ratio (LAR) and debt-to-assets ratio (DR) have positive relationship with firm performance, meanwhile the self-financing (E/C) affects negatively to the return on equity (ROE). Upon the findings we suggest that the Vietnamese government should focus on stabilizing macro environment to create favorable environment for enterprises. And the pharmaceutical enterprises should build more reasonable capital structure with higher debt proportion than equity, diversifying loan mobilization channels such as issuing long-term bonds. Additionally, the firms should expand the scale appropriately to maintain development and ability to pay debts.

• The Journal of Asian Finance, Economics and Business
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• 제5권4호
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• pp.187-199
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• 2018

This study examined the effects of startup firm's knowledge assets on the effectiveness of their sales strategies, efficiency of sales activities, and management performance, after categorizing these assets into customer knowledge assets and technology knowledge assets. Furthermore, the moderating effects of promotion focus by CEOs and sales managers of startup firms were analyzed. For the analysis, dyadic questionnaire surveys were conducted targeting the CEOs and sales managers of startup firms established at the Gyeongnam Technopark and the KAIST Technology Business Incubation Center in Korea. Hypotheses were verified through structural equation modeling, and moderating effects were identified through ANOVA. CEO's customer knowledge asset strengthened their effectiveness of sales strategies, and sales manager's technology knowledge asset strengthened the efficiency of their sales activities. Also, CEO's effectiveness of sales strategies and sales manager's efficiency of sales activities have been found to enhance startup firm's management performance. Meanwhile, the moderating effect of promotion focus strengthened CEO's effectiveness of sales strategies through CEO's customer knowledge asset and interaction as CEO's promotion focus level increased, but promotion focus of sales managers did not have any significant interaction effect. This study provides implications by offering empirical evidence on startup firms with regard to knowledge assets.

• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.