• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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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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• v.22 no.2
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.727-736
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• 2009

Many of the researchers have tried to enhance the satisfaction of both users and owners of social infrastructures by applying the asset management methodology. This study is to develop more efficient asset management framework for bridge management. Based on various literature review, an asset management procedure for bridge management was suggested, and appropriate practices at each step were given. The suggested procedures include the determination of operation and maintenance strategy, level of service, performance measure, valuation of assets, and decision-makings. In addition, this study suggests an applicable decision-making process for the resource distribution based on the management strategy.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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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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• v.15 no.4
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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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• v.19 no.4
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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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• v.5 no.3
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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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• v.7 no.9
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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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• v.5 no.4
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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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• v.7 no.8
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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.