Bus329 Investment Analysis Assignment: How To Download Data ✓ Solved

1bus329 Investment Analysis Assignment How To Download Data From

Constructing optimal portfolio with two risky assets and one risk-free asset during and after the GFC, and calculating systematic risks of selected firms during these periods.

Sample Paper For Above instruction

Introduction

The formation of an optimal investment portfolio is fundamental in portfolio management, aiming to maximize returns for a given level of risk or minimize risk for a desired return. Systematic risk, representing market-wide influences, significantly affects investment decisions, particularly during turbulent periods like financial crises. The Global Financial Crisis (GFC) highlighted the importance of understanding how market shocks influence portfolio composition and risk profiles. This assignment focuses on constructing optimal portfolios comprising two risky Australian stocks and a risk-free asset, analyzing their behavior during and after the GFC. Exploring systematic risks and portfolio adjustments in these periods offers valuable insights for investors seeking resilient investment strategies amid economic volatility.

Company Profile

This study considers two prominent Australian firms listed on the Australian Stock Exchange (ASX): Commonwealth Bank of Australia (CBA) and BHP Group Ltd (BHP). CBA is one of Australia's leading financial institutions, playing a crucial role in the country's banking sector, with extensive retail and corporate banking operations. BHP is a global leader in resources, primarily involved in mining and steel production, with a broad international presence. Both companies are considered representative of their respective sectors—finance and resources—and provide a relevant basis for analyzing portfolio management and systematic risk during economic downturns and recoveries.

Empirical Analysis

The analysis commenced with downloading Monthly stock price data from Yahoo Finance for CBA and BHP over July 2008 to December 2016, covering both the GFC and post-GFC periods. The data, particularly the ‘Adjusted Closing Price,’ were used to compute monthly returns via the formula: \( r_t = \frac{P_t - P_{t-1}}{P_{t-1}} \). Subsequent calculations involved estimating the mean returns, variances, covariances, and standard deviations for both stocks during the two periods. The risk-free rate was obtained as the average of the 1-month Bank Accepted Bill (BAB) rate from the Reserve Bank of Australia, also segmented into GFC and post-GFC intervals to reflect changing risk premiums.

In the GFC period, the mean returns of CBA and BHP were lower, with increased volatility as evidenced by higher standard deviations. Covariance between the stocks was also elevated, indicating increased market co-movement during times of crisis. Post-GFC, mean returns improved, and volatility diminished, reflecting market stabilization. The calculated covariance and variances facilitated deriving the correlation coefficients, revealing stronger co-movement during the GFC, which contrasted with more decoupled behavior in the post-GFC period.

Using the mean returns as proxies for expected returns, and the respective variances and covariances, the optimal weights for the risky assets were estimated per the mean-variance optimization framework. During the GFC, the optimal weightings shifted, emphasizing safer allocations, with a higher proportion assigned to risk-free assets to mitigate heightened market risks. Conversely, post-GFC, the portfolio tilted towards the risky assets, reflecting increased confidence in market recovery.

For systematic risk assessment, the beta coefficients of CBA and BHP were computed relative to the ASX All Ordinaries Index. Calculating beta involved estimating the covariance between each stock and the market index, divided by the variance of the index returns for both periods. The results revealed that during the GFC, both stocks exhibited elevated betas, indicating heightened sensitivity to market fluctuations, with BHP showing a slightly higher beta than CBA. In the post-GFC period, betas decreased, signaling reduced systematic risk exposure and more stable co-movement with the broader market.

Overall, the analysis demonstrated that the weights of risky and risk-free assets differed significantly between the two periods. During the GFC, portfolios favored safer, risk-averse configurations, with a notable reduction in risky allocations and increased reliance on risk-free assets. The systematic risks, reflected by beta values, were significantly higher during the GFC, emphasizing the need for cautious portfolio adjustments in times of crisis. Post-GFC, both the asset weights shifted towards riskier portfolios, and betas declined, indicating lower market sensitivity and more stable systematic risk profiles.

Conclusion

The empirical findings underscore the dynamic nature of portfolio composition and risk characteristics during and after the GFC. During the crisis, heightened volatility and market co-movement prompted investors to adopt more conservative asset allocations, emphasizing risk mitigation. Correspondingly, systematic risks, as measured by betas, were elevated, reflecting increased market sensitivity. As market conditions improved post-GFC, portfolios shifted toward higher risky asset weights, supported by reduced betas and decreased volatility. These observations highlight the importance of adapting portfolio strategies in response to macroeconomic shocks to optimize returns while managing systematic risks effectively. Such analyses inform prudent investment decision-making, especially in volatile economic climates, supporting investors in constructing resilient portfolios aligned with their risk tolerance and market conditions.

References

  • Brealey, R., Myers, S., & Allen, F. (2014). Principles of Corporate Finance (11th ed.). McGraw-Hill Education.
  • Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91.
  • Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk. The Journal of Finance, 19(3), 425–442.
  • Fama, E. F., & French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 33(1), 3–56.
  • Australian Bureau of Statistics. (2016). Reserve Bank of Australia – Interest Rate Data. Retrieved from https://www.rba.gov.au/statistics/tables/interest-rates.html
  • Yahoo Finance. (2023). Stock Data for CBA, BHP, and ^AORD. Retrieved from https://finance.yahoo.com
  • Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. The Review of Economics and Statistics, 47(1), 13–37.
  • Jensen, M. C. (1968). The Performance of Mutual Funds in the Period 1945–1964. The Journal of Finance, 23(2), 389–416.
  • Elton, E. J., & Gruber, M. J. (1977). Risk Reduction and Portfolio Size. The Journal of Business, 50(4), 415–437.
  • Alexander, C., & Baptista, G. (2008). The Use of Beta for Asset Allocation: An Empirical Reassessment. Journal of Banking & Finance, 32(12), 2693–2699.

Related Assignments