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Full-Text Articles in Business
The Capm, National Stock Market Betas, And Macroeconomic Covariates: A Global Analysis, Michael Curran, Adnan Velic
The Capm, National Stock Market Betas, And Macroeconomic Covariates: A Global Analysis, Michael Curran, Adnan Velic
Articles
Using global data on aggregate stock markets, this paper finds that the capital asset pricing model fares much better than suggested previously. At shorter time horizons, our results also show that the positive risk-reward relation can collapse during times of high volatility. Compared to other countries, we retrieve evidence of lower systematic risks across frontier equity portfolios. We find that countries characterized by higher levels of openness, exchange rate volatility, and larger economic size are exposed to higher systematic covariances with the world stock market. Conversely, we obtain an inverse link between international reserves and systematic risks in national equity.
Using Financial Investment Measures To Proactively Engage Students In The Introductory Business Statistics Course, Mark L. Berenson, Nicole Koppel, Richard Lord, Laura L. Chapdelaine
Using Financial Investment Measures To Proactively Engage Students In The Introductory Business Statistics Course, Mark L. Berenson, Nicole Koppel, Richard Lord, Laura L. Chapdelaine
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
Typically, the core-required undergraduate business statistics course covers a broad spectrum of topics with applications pertaining to all functional areas of business. The recently updated American Statistical Association's GAISE (Guidelines for Assessment and Instruction in Statistics Education) College Report once again stresses the pedagogical importance of topic and application relevancy in an increasingly data-centered world. To this end, only two introductory textbooks have incorporated some financial investment measures (Sharpe ratio and beta coefficient) in the teaching of numerical descriptive measures and simple linear regression analysis, respectively, while a few others include them as real-data application exercises at the end of …
Seeking The Profitability-Risk-Competitiveness Frontier Using A Genetic Algorithm, Ronnie Tan
Seeking The Profitability-Risk-Competitiveness Frontier Using A Genetic Algorithm, Ronnie Tan
Journal of Actuarial Practice (1993-2006)
Monte Carlo simulation is used to develop a flexible framework to measure the profitability, risk, and competitiveness of any insurance product. A genetic algorithm is then used to seek the optimum asset allocations that form the profitability-risk-competitiveness frontier and to examine the profitability, risk, and competitiveness trade-off's. We also show how to select the appropriate asset allocation and crediting strategy in order to position the product at the DeSired location on the profitability-risk-competitiveness spectrum.
A Further Inquiry Into The Market Value And Earnings' Yield Anaomalies, John W. Peavy, Iii, David A. Goodman
A Further Inquiry Into The Market Value And Earnings' Yield Anaomalies, John W. Peavy, Iii, David A. Goodman
Historical Working Papers
The apparent existence of two stock market anomalies, the earnings' yield (E/P ratio) and the market value (MV) effects, has stimulated considerable research. This study expands the E/P - MV literature by detecting the following: (1) both an E/P and a MV effect exist among a sample of industrial stocks over the 1970-1980 period; (2) using risk-adjusted returns, each of the E/P and MV effects persisted even after controlling the other; (3) an adjustment for a significant time bias in the returns data caused the MV anomaly to disappear after controlling for E/P ratios, but a significant E/P effect remained; …
The Price-Earnings Relative As An Indicator Of Investment Returns, John W. Peavy, Iii, David A. Goodman
The Price-Earnings Relative As An Indicator Of Investment Returns, John W. Peavy, Iii, David A. Goodman
Historical Working Papers
The use of the price-earnings relative indicator (PER) is examined to assess its utility in evaluating stock returns for similarly performing firms. The measure does seem to be a valid predictor of investment returns and eliminate bias between firms within the same industry.