Scenario expectations, historical dispersion and a two-fund blend, all worked from supplied data, make up the GF540 Unit 2 risk and return computation on this page, each formula before its number. Searches like "gf 540 unit 2 assignment example", "gf540 unit 2 sample" and "gf540 unit 2 example" land here.
What a finished GF540 Unit 2 risk and return computation looks like
Three parts, each ending in a boxed result. Part one takes four economic states weighted 0.20, 0.30, 0.30 and 0.20, with a composite equity fund returning -14, 4, 12 and 26 percent and a composite bond fund returning 5, 6, 2 and 3 percent. Expected returns come to 7.20 and 4.00 percent, standard deviations to 13.06 and 1.67 percent, and a covariance of -0.00128 gives a correlation of -0.59. Part two uses five annual returns for a composite stock and a broad index, reporting an arithmetic mean of 5.80 percent against a geometric mean of 5.24, a sample standard deviation of 12.19 percent, a correlation of 0.82 and a beta of 1.21. Part three blends the two funds 60/40 and finds risk of 7.46 percent, below the 8.51 a weighted average would suggest.
How a GF540 Unit 2 example is structured
Each part opens with the data table exactly as supplied, so the reader can see nothing was altered, and then moves through the formulas in the order they depend on each other. Expected return comes before deviation from it, variance before its square root, covariance before correlation. Every formula is written once in symbols, then once with the numbers substituted, then as a result rounded to two decimal places in percent. Part two states which variance it uses, dividing by n minus one because five observations are a sample, and reports the population figure beside it for comparison. A short interpretation paragraph closes each part: what the correlation implies for combining the funds, why the geometric mean is lower, what a beta above one means for this stock. A final table gathers every result in one place.
Probabilities checked to one
The four state weights are summed before use, and the table notes that the scenarios are supplied assumptions rather than original forecasts.
Deviation squared, then weighted
Variance for the equity fund is built row by row, each squared deviation multiplied by its probability, reaching 0.017056 before the square root is taken.
Sample against population
Five years of history divided by n minus one give 12.19 percent; the population version, 10.91, sits beside it so the choice is visible.
Two means, two meanings
The arithmetic average of 5.80 percent describes a typical year, while the geometric 5.24 describes compound growth, and the paper says which question each answers.
Diversification measured, not asserted
The 60/40 blend's 7.46 percent risk is set against a naive weighted average of 8.51, and the negative covariance is named as the cause of the difference.
Where marks go in GF540 Unit 2
Most lost credit in a risk and return set comes from an early slip that every later figure inherits. A covariance computed without subtracting the means, or with unweighted deviations in the scenario table, corrupts the correlation and then the portfolio risk. Treating five historical returns as a population understates dispersion without saying so. Averaging standard deviations to get portfolio risk ignores covariance entirely and erases the result the unit exists to show. Graders also look for interpretation: a correlation reported without a sentence on what it means for combining assets is half an answer. Percent and decimal forms mixed inside one formula produce answers off by a factor of a hundred, and a set that shows only final numbers leaves nothing for partial credit when one of them is wrong.
Get a GF540 Unit 2 example written to your instructions
Send the data tables from your GF540 Unit 2 assignment along with the prompt and rubric, and mention whether your instructor wants spreadsheet output or hand-worked formulas. Every figure is derived from those numbers in dependency order, with interpretation after each part. The first custom sample is free, and it typically comes back inside 24-48h.
GF540 Unit 2 questions, answered
Should I divide by n or n minus one?
For historical returns treated as a sample of what the asset could produce, n minus one is the usual choice, and most finance texts use it. For probability-weighted scenarios there is no division at all, since the weights already sum to one. The sample states its choice in each part and reports the alternative beside it, so a grader who prefers the other convention can see both.
Why is the geometric mean lower than the arithmetic mean?
Because volatility drags compound growth below the simple average. A loss followed by an equal percentage gain leaves an investor behind, and the geometric mean captures that while the arithmetic mean does not. The gap widens as returns become more dispersed. Both appear in the sample, with a note that the arithmetic figure suits expected single-period return while the geometric suits growth over several years.
Does my set need a minimum variance portfolio?
When the prompt asks, and many do. The sample includes it as a short extension: with these two funds, the weight that minimizes risk puts about 7.8 percent in equities and produces a standard deviation near 1.26 percent. Showing where that weight comes from, rather than just stating it, is what separates a derivation from a spreadsheet printout in the eyes of most graders.