A steady waste hauler against a cyclical chip-equipment maker: the MT217 Unit 8 risk and return analysis compares expected return, dispersion and the return beta requires. Searches like "mt 217 unit 8 assignment example", "mt217 unit 8 sample" and "mt217 unit 8 example" land here.
What a finished MT217 Unit 8 risk and return analysis looks like
Roughly four pages, divided into three parts. Part one sets out three economic states, weak, normal and strong, with probabilities of 0.25, 0.50 and 0.25. The waste hauler returns 6, 9 and 11 percent across them, an expected 8.75 percent with a standard deviation of 1.79; the equipment maker returns minus 18, 14 and 38 percent, an expected 12.00 percent with a deviation of 19.90. Part two divides risk by return: coefficients of variation of 0.20 and 1.66. Part three applies the pricing model with a 4.2 percent risk-free rate and a 5.5 percent market premium. With betas of 0.65 and 1.70, the required returns are 7.78 and 13.55 percent, so the hauler plots above the security market line and the equipment maker below it.
How a MT217 Unit 8 example is structured
The analysis moves from standalone risk to market risk, and says why the second matters more. Part one builds a table with the three states as rows, computing each company's weighted return and then its squared deviations row by row, so the variance can be followed. Part two introduces the coefficient of variation as a way to compare risk per unit of return when expected returns differ. Part three changes the question: a diversified holder cares about beta rather than total dispersion, so the paper computes the return each beta requires and compares it with the expected figure from part one. A short section combines the two in a 70 to 30 portfolio with a beta of 0.965. The closing paragraph reads the security market line result without turning it into advice.
Three states, weighted
Weak, normal and strong economies at 0.25, 0.50 and 0.25 give expected returns of 8.75 and 12.00 percent, each row multiplied out.
Deviation row by row
Squared deviations from each mean are weighted and summed before the square root, producing 1.79 and 19.90 percent.
Risk per unit of return
Coefficients of variation of 0.20 and 1.66 show the equipment maker carrying about eight times the risk for each point of return.
What beta requires
At a 4.2 percent risk-free rate and a 5.5 percent premium, betas of 0.65 and 1.70 require 7.78 and 13.55 percent.
Above and below the line
The hauler's expected return exceeds its requirement by about one point, the equipment maker falls short by about one and a half, and the paper explains what that implies.
Where marks go in MT217 Unit 8
Risk and return papers lose the most when standard deviation is computed without the probability weights, treating three states as equally likely when they are not. Expected returns reported without any measure of risk answer half the prompt. Many sections deduct for comparing total risk across companies with different expected returns without the coefficient of variation or a comparable adjustment. Beta applied to the wrong premium, the market return itself instead of the market return minus the risk-free rate, inflates every required return. Papers that stop at the pricing model's output without comparing it with expected return miss the interpretation the unit is built toward. Treating an above-the-line result as an instruction to buy draws comment, since the unit asks what the model implies, not what anyone should do.
Get a MT217 Unit 8 example written to your instructions
Upload the Unit 8 problem data, including any probabilities, returns and betas your instructor supplied, plus the rubric and any rounding rule. Expected return and dispersion are computed row by row, risk per unit of return is compared, and the pricing model is applied and interpreted. An initial sample costs nothing; allow roughly 24-48h.
MT217 Unit 8 questions, answered
Why does beta matter more than standard deviation?
Because much of a single company's dispersion can be removed by holding it alongside others, and investors are not paid for risk they could diversify away. Beta measures the part that remains, the sensitivity to the market as a whole. The sample shows both, then uses beta for the required return, which is the reasoning the pricing model rests on.
What does plotting above the security market line mean?
It means the expected return, from the scenario analysis, exceeds what the pricing model requires for that level of beta. In textbook terms the asset looks underpriced relative to its risk. The sample reports the waste hauler's result that way and notes that the conclusion is only as good as the scenario probabilities and returns behind it.
Should the probabilities come from real data?
In most sections the problem supplies them, and the task is the calculation and interpretation. If the prompt asks you to estimate your own, state the basis, such as how often the economy has been weak in recent decades. The sample's figures are illustrative, and the paper says so, which keeps the analysis honest about its inputs.