A finished FIN-350 Topic 6 risk and return measurement example, computing expected return, standard deviation and coefficient of variation for two stocks and a portfolio of both. Searches like "fin 350 topic 6 assignment example", "fin350 topic 6 sample" and "fin-350 topic 6 example" land here.
What a finished FIN-350 Topic 6 risk and return measurement looks like
The finished example sets out three illustrative scenarios, boom, normal and recession, with probabilities of 25, 50 and 25 percent. Stock A returns 30, 12 and minus 10 percent across them, for an expected return of 11 percent and a standard deviation of about 14.2 percent. Stock B returns 4, 10 and 16 percent, moving against the economy, for an expected return of 10 percent and a standard deviation of about 4.2 percent. The coefficient of variation, about 1.29 for A and 0.42 for B, expresses risk per unit of return. A portfolio split evenly between them returns 17, 11 and 3 percent, an expected 10.5 percent with a standard deviation of about 5.0 percent, far below the 9.2 percent average of the two.
How a FIN-350 Topic 6 example is structured
The example computes one measure at a time and then combines them. It opens with the scenario table, each state of the economy listed with its probability and the return of each stock. The expected return section multiplies and sums, showing each product. The dispersion section computes deviations from the expected value, squares and weights them, and takes the square root, with the working visible for both stocks. A comparison passage introduces the coefficient of variation and explains why it suits stocks with different expected returns. The portfolio section computes the combined return in each scenario and repeats the measures, then sets the result beside a simple average of the two standard deviations. The closing section states which holding a risk-averse investor would choose and why the portfolio beats either stock held alone.
Scenarios with probabilities stated
Three states of the economy and their likelihoods open the example, since every later measure is a weighted calculation across those same rows.
Dispersion computed, not described
Deviations are squared, weighted and rooted in full view, turning a stock's volatility into a figure that can be compared and used.
Risk per unit of return
The coefficient of variation divides dispersion by expected return, which ranks two stocks fairly when their expected returns are not the same.
Two stocks moving opposite ways
Stock B rises when A falls, so the combined holding's variability drops well below the average of the two standalone figures.
A choice drawn from the measures
The closing section says which holding a cautious investor would prefer and ties that preference to the computed figures, not to impressions of either company.
Where marks go in FIN-350 Topic 6
Describing a stock as volatile or safe without a computed measure loses the most, because the topic asks for risk expressed as a number that can enter a comparison. Standard deviation computed without weighting each squared deviation by its probability treats unlikely scenarios as common and overstates dispersion. Averaging the two stocks' standard deviations to get the portfolio's ignores how they move together, which is the whole reason the portfolio is less risky. Ranking stocks by standard deviation alone when their expected returns differ can reverse the sensible choice. Arithmetic errors in the probabilities, such as weights that do not sum to one, invalidate every figure after them. A set of measures with no recommendation stays a calculation exercise, and the topic asks for more than that.
Get a FIN-350 Topic 6 example written to your instructions
Send the FIN-350 Topic 6 problems and the rubric shared in your classroom, with the scenario data your section supplied. We write a custom example to those problems, with expected return and standard deviation worked in view, risk per unit of return compared, a portfolio measured against its parts and a choice stated, in 24 to 48 hours. The first one is free.
FIN-350 Topic 6 questions, answered
Why is the portfolio less risky than the average of its stocks?
Because the two stocks do not move together. When A falls in a recession, B rises, so losses in one are partly offset by gains in the other. Averaging their standard deviations assumes they rise and fall in step, which they do not. The less two holdings move together, the more combining them reduces variability without giving up much expected return.
When should the coefficient of variation be used?
When comparing investments whose expected returns differ. A stock with a higher standard deviation may still offer more return per unit of risk, and standard deviation alone cannot show that. Dividing dispersion by expected return puts both on the same footing. It works poorly when expected returns are near zero or negative, where the ratio becomes unstable and hard to read.
Does this topic cover beta?
Often, as the next step. Standard deviation measures a stock's total variability, while beta measures only the part that moves with the market, which diversification cannot remove. Many sections introduce beta once the portfolio calculation has shown that some risk disappears when holdings are combined. The custom example follows whichever measures the assignment specifies.