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Expense ratios and net alphas of large cap funds: Do expenses add value?
No full textGlobal equity markets witnessed a tumultuous time-period of decline followed by growth, starting from the early part of 2000 to the beginning of the current period. Investment in actively managed mutual funds also experienced a decent growth over the same period though there were times when investors especially retail investors sat on the sidelines and seemed reluctant to invest in equity funds. This study analyzes the performance of large cap equity funds between January 2000 and December 2013. The main objective is to assess the performance as reflected in the alpha of funds conditioned on expenses. We apply both OLS regression and ranked portfolio approaches to estimate the abnormal performance. Results of this study show that large cap funds underperform against benchmarks after incorporating expenses. Results also suggest that expenses are not the only reason behind their underperformance
Advisor compensation: Which clients know and how do they pay?
No full textUsing the 2015 National Financial Capability Study Investor Survey, this study uses agency theory to inform an exploration of characteristics associated with knowing how one’s financial advisor/broker is compensated. This study further examines how individuals who do know the compensation method choose between financial advisors with different compensation models. Proposed changes in the financial advising regulatory landscape, as well as the pending changes to the CFP Board Standards of Professional Conduct, brings greater emphasis on understanding consumers’ advisor compensation preferences. Primary results indicate that clients who place importance on fees, that are more knowledgeable about diversification, and that perform background checks are more likely to know compensation methods. A follow-up analysis reveals distinct differences between individuals that used each model, but also provide some mixed results, indicating that clients may not fully understand the compensation paid to their advisors. Discussion and implications related to these results are provided
The Community Counseling, Education, and Research Center (CCERC) Model: Addressing Community Mental Health Needs Through Engagement Scholarship
Get PDFProviding access to high-quality health services for all people is a national problem further compounded when the focus is mental health. Long-term primary prevention strategies and solutions, foundational to best practices in public health, are often considered at odds with short-term profit-driven private sector approaches within the capitalistic economy of the United States. Engagement scholarship, then, provides a uniquely viable, adaptable, responsive, customizable, and sustainable set of structures, mechanisms, and processes to address pressing societal needs. The CCERC model of engaged scholarship offers an example of community engagement, transformative and exceptional in addressing these societal and structural health care problems, with potential for customizable and contextual scalability. Specifically, world-class health care as a human right and an organizational value can be operationalized with engagement scholarship, which has the creativity and capacity to transform institutional values into purposeful and practical vehicles of community change
A Rubric Development Study for the Assessment of Modeling Skills
No full textThe purpose of this study was to introduce a rubric named “Rubric for the Assessment of Modeling Skills” for assessing cognitive modeling skills and explaining the rubric’s development process. The dimensions of the rubric are understanding the problem, simplifying, mathematizing, working mathematically, interpreting and validating. Twenty-three 6th grade and twenty 11th grade students took part in the study. During the ten weeks of the data collection process, we analyzed the participants’ solutions on the modeling tasks and constructed the levels of the dimensions. The rubric offers a detailed assessment and scoring for different solutions that may arise in any modeling task implementation