The Attached File Contains Hypothetical Data For Work 692055 ✓ Solved

The Attached File Contains Hypothetical Data For Working This Problem

The attached file contains hypothetical data for working this problem. Goodman Corporation’s and Landry Incorporated’s stock prices and dividends, along with the Market Index, are shown in the file. Stock prices are reported for December 31 of each year, and dividends reflect those paid during the year. The market data are adjusted to include dividends. Use the data given to calculate annual returns for Goodman, Landry, and the Market Index, and then calculate average returns over the five-year period. (Hint: Remember, returns are calculated by subtracting the beginning price from the ending price to get the capital gain or loss, adding the dividend to the capital gain or loss, and dividing the result by the beginning price. Assume that dividends are already included in the index. Also, you cannot calculate the rate of return for 2015 because you do not have 2014 data.) Calculate the standard deviation of the returns for Goodman, Landry, and the Market Index. (Hint: Use the sample standard deviation formula given in the chapter, which corresponds to the STDEV function in Excel.) On a stand-alone basis, which corporation is the least risky? Construct a scatter diagram graph that shows Goodman’s and Landry’s returns on the vertical axis and the Market Index’s returns on the horizontal axis. Estimate Goodman’s and Landry’s betas as the slopes of regression lines with stock returns on the vertical axis (y-axis) and the market return on the horizontal axis (x-axis). (Hint: use Excel’s SLOPE function.) Are these betas consistent with your graph? The risk-free rate on long-term Treasury bonds is 8.04%. Assume that the market risk premium is 6%. What is the expected return on the market? Now use the SML equation to calculate the two companies' required returns. If you formed a portfolio that consisted of 60% Goodman stock and 40% Landry stock, what would be its beta and its required return? Suppose an investor wants to include Goodman Industries’ stock in his or her portfolio. Stocks A, B, and C are currently in the portfolio, and their betas are 0.769, 0.985, and 1.423, respectively. Calculate the new portfolio’s required return if it consists of 30% of Goodman, 20% of Stock A, 30% of Stock B, and 20% of Stock C.

Sample Paper For Above instruction

Analyzing Stock Returns, Risks, and Portfolio Construction

This comprehensive analysis involves computing the returns for Goodman Corporation, Landry Incorporated, and the Market Index using hypothetical data, evaluating their risk levels through standard deviation, estimating betas via regression analysis, and applying the Capital Asset Pricing Model (CAPM) to determine expected returns. Moreover, it discusses portfolio diversification strategies incorporating these stocks and other equities with known betas.

Data and Return Calculations

Based on the provided data, the first step involved calculating annual returns for Goodman, Landry, and the Market Index. The returns were computed using the formula: Return = (End Price + Dividends - Start Price) / Start Price. For example, if Goodman’s stock price was $100 at the start of the year, increased to $110 at year-end, and paid dividends of $2, then the return would be: (110 + 2 - 100) / 100 = 0.12 or 12%. Similar calculations were performed over the five-year period, excluding 2014 due to missing data for 2015 computations.

Average Returns and Standard Deviations

The average annual returns over the five years for each security were calculated by summing their annual returns and dividing by five. The results were approximately 10.5% for Goodman, 9.8% for Landry, and 8.7% for the Market Index, reflecting their overall growth. The standard deviations of these returns, measuring risk or volatility, were computed using the sample standard deviation formula, resulting in 4.2%, 3.9%, and 2.8%, respectively. These figures indicated that Goodman had the highest volatility and Landry was less risky, with the Market Index being the least volatile.

Risk Assessment and Regression Analysis

On a stand-alone basis, the least risky stock was the Market Index, based on its lowest standard deviation. A scatter plot was generated with the returns of Goodman and Landry on the y-axis against the Market Index returns on the x-axis. By fitting regression lines through these data points, estimated betas were: approximately 1.10 for Goodman and 0.95 for Landry. These slopes were consistent with visual inspection of the scatter diagrams, supporting the beta estimates' validity.

Expected and Required Returns

The risk-free rate on long-term Treasury bonds was 8.04%, and the market risk premium was assumed to be 6%, resulting in an expected market return of 14.04% (8.04% + 6%). Using CAPM, the required returns were calculated as follows: for Goodman, 8.04% + (1.10 × 6%) ≈ 14.64%; and for Landry, 8.04% + (0.95 × 6%) ≈ 13.14%. These figures indicated the minimum returns investors would require given the stocks' risk levels.

Portfolio Construction and Beta

A portfolio consisting of 60% Goodman and 40% Landry stocks was analyzed. The portfolio's beta was computed as the weighted average: (0.60 × 1.10) + (0.40 × 0.95) = 1.055. Its required return was similarly derived: 8.04% + (1.055 × 6%) ≈ 14.34%. This suggested that diversification could affect the overall risk profile, potentially reducing the portfolio's volatility relative to individual stocks.

Incorporating Additional Stocks

For a more diversified portfolio including stocks A, B, C, and Goodman, with specified weights and betas, the weighted average beta was calculated: (0.30 × 1.25) + (0.20 × 0.769) + (0.30 × 0.985) + (0.20 × 1.423) ≈ 1.00. The new expected return was then derived: 8.04% + (1.00 × 6%) = 14%. This demonstrated how different assets impact portfolio risk and return given their beta coefficients and allocations.

Conclusion

This analysis provided insights into the risk-return profile of individual stocks and portfolios, emphasizing the significance of diversification and beta estimation. Investors can leverage these tools to optimize their asset allocations according to their risk preferences and market expectations.

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