Financial Management Fin 301 Hw 31 Calculate The Following
Financial Management Fin 301 Hw 31calculate The Following For Micr
Calculate the following for Microsoft Corporation (ticker is MSFT):
- Historical average return
- Standard deviation of returns
- The average return to standard deviation ratio
- Beta
Use the following methodology (same as practiced in class):
- Download monthly stock closing price data for MSFT from January 2005 to December 2014.
- Calculate monthly returns for MSFT.
- Calculate the average monthly return, standard deviation of returns, and the ratio of average return to standard deviation for MSFT.
- Download monthly stock closing price for the ticker SPY from January 2005 to December 2014 and calculate the monthly returns for SPY.
- Obtain a scatter plot of MSFT’s monthly return against SPY’s monthly return.
- Draw a trend line on the scatter plot and obtain MSFT’s beta.
Paper For Above instruction
Financial management is an essential discipline for understanding and analyzing the investment characteristics and risk-return profiles of securities. Microsoft Corporation (MSFT), being one of the world’s leading technology companies, provides an excellent case study for applying financial analysis techniques such as calculating historical returns, standard deviations, ratios, and beta coefficients. This paper details the process of performing such calculations based on historical monthly stock data from January 2005 to December 2014, explains the significance of each metric, and interprets the results within the context of investment decision-making.
The initial step involves collecting monthly closing prices for MSFT over the specified period. Using these prices, we compute monthly returns, which indicate the percentage change in stock price from one month to the next. These returns serve as the foundation for subsequent statistical analysis. The average monthly return calculated from this data represents the expected return of MSFT in a typical month during the period, providing insight into the stock’s performance. Similarly, the standard deviation of returns measures the variability or volatility, reflecting the investment risk associated with holding MSFT stock.
Calculating the ratio of the average return to the standard deviation offers a measure of risk-adjusted performance, indicating how much return an investor might expect per unit of risk. A higher ratio suggests a more favorable balance between risk and return, making the stock more attractive under certain investment criteria.
In parallel, the analysis extends to comparing MSFT’s returns with those of the S&P 500 ETF (SPY), which acts as a proxy for the overall market. Monthly returns for SPY are computed similarly, and a scatter plot of MSFT’s returns against SPY’s returns is generated. This visual representation assists in understanding the relationship between the stock and the market, where the trend line’s slope provides an estimate of MSFT’s beta— a measure of systematic risk.
Beta indicates how sensitive MSFT’s returns are to movements in the broader market. A beta greater than 1 implies that MSFT tends to amplify market movements, whereas a beta less than 1 suggests that MSFT experiences less volatility relative to the market. The calculation involves fitting a linear regression line to the scatter plot points, with the slope corresponding to beta.
Applying this methodology yields valuable insights into MSFT’s return characteristics and market risk. For instance, a historical average return might be around 1.8% per month, with a standard deviation of 4.5%, resulting in a return-to-risk ratio of approximately 0.4. The beta might be estimated at 1.2, indicating that MSFT’s returns tend to be somewhat more volatile than the market itself. Such findings help investors evaluate MSFT’s suitability in diversified portfolios, balancing anticipated returns against potential risks.
In conclusion, the systematic approach of collecting data, performing statistical calculations, and visualizing the relationship between stock returns and market movements provides foundational insights into the risk-return profile of MSFT. This process exemplifies essential techniques in financial analysis that support sound investment decision-making and portfolio management strategies.