The purpose of the study was to assess the sustainability of dual credit programs from 2013-2016 across U.S. public community and junior colleges and the effect of 2 funding variables associated with these course offerings. The literature postulated that dual credit programs have continued to grow in demand since their origin with no indication of decreasing in the near future. The researcher chose 2 funding mechanisms to associate with dual credit enrollment: governance structure of the state and the state funding model as it pertains to dual credit enrollment. Tuition revenue totals were extracted from the Integrated Postsecondary Education Data System for each fall semester from 2013-2016. This data set included 48 states in the U.S. The only non-reporting states were Alaska, Delaware, and The District of Columbia. This study uses a quantitative approach to determine if state governance structure and state funding model had an impact on tuition revenue. The statistics computed included an Independent Samples T-test. In summary, the analysis did support the research hypothesis in that there was statistically significant differences based on the governance structure of the state for the years of 2013 and 2014, but not years 2015 and 2016. The analysis did not support the research hypothesis in that there were no statistically significant differences based on the state funding model in tuition revenue derived from enrollment. Limitations in the current study that may have influenced the outcome of the analysis and recommendations for further studies are discussed.

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本篇論文將Kariya, Ushiyama, and Pliska三位學者在2003所發表之三因子不動產證券化評價模型加入信用風險(credit risk)的考量. / In this paper, we extend Kariya, Ushiyama, and Pliska’s three factor mortgage-backed securities pricing model with credit risk. In our model, two reasons that cause prepayment behaviors are the refinancing factor and the equity factor. Our pricing model is a discrete-time model, and the credit risk is priced due to the concept of reduced form model. We also use Monte Carlo simulation to test our theoretical value and make some comparisons between changing parameters.

債券信用風險的規避,一直以來是學者有興趣研究的課題,本篇研究以HJM模型去衡量信用風險, 透過市場資料的輸入,去衡量違約程度,並對信用風險相關之衍生性金融商品作出適當的評價,以求規避信用風險. / Abstract In this study, we combine credit valuation approaches developed by Jarrow＆Turnbull (1995)、Duffie＆Singleton (1999)、Schonbucher (2000) to execute a default pricing methodology under H.J.M default intensity structure. We can use market data such as defaultable yield rate and its volatility to measure credit risk, however, because of the close form in our model, the comparative static analysis for parameters can be done. At last, after introducing the survivor probability measure, we can extend to price default related derivatives.

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