Friday, October 18, 2019

Statistical coursework Example | Topics and Well Written Essays - 1500 words - 1

Statistical - Coursework Example Beta is the gradient of the model line. Nonetheless, for ADM, BLT, AV, CPG and RIO Company, there was no significant beta to explain the market risk since t-statistic was less than the critical value. Generally, alpha, the constant, illustrated how much worse or better the company performed than CAPM predicted (negative alpha illustrated how much worse the fund performed and vice versa). The quality of our model was illustrated by our R2. While an R2 of 1.0 would imply that our model fit the weekly data perfectly (100%) and that the performance of the funds were explained by their risk exposure, as estimated by beta, this was not the case as evidenced in different R2, s in the Table 1. According to Reilly & Brown (2012), variation of stock returns is the concern of any shareholder. As such, most models are not interested in finding out the most convenient way of determining stock return but to see which macroeconomic factors determine the variation of stock return. CAPM is a simple model that is perceived on sound reasoning, some of the assumptions that look like the model are unrealistic. Rather than simply just broadening an existing theory, Albright, Winston & Zappe (2009) propos this concern by giving a completely different model: the Arbitrage Pricing Theory (APT). Being the opposite of CAPM, the current developed APT starts with the assumption that arbitrage opportunities should not be found in perfect financial markets. This thought is a little bit restricted than those needed to develop the CAPM. Bruns (2013) claims APT starts by assuming that there are n factors, which cause asset returns to significantly differ from their expected values. Secondly, it adopts systematic risk (beta). CAPM considers systematic. This has been assumed in other return models, like the dividend discount model (DDM). Systematic or market risk is a fundamental variable because it is one does not see it therefore cannot be

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