Stock Portfolio Analysis Of FAANG Companies

Discussion

The goal of this paper is to examine a stock portfolio that includes “FAANG” firms including Facebook (FB), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOGL) (GOOG). The risk and return estimate is based on daily price data for the stocks over the previous three years, from January 1, 2019 to December 31, 2021. For the stocks, measures of dispersion and central tendency have been carefully examined the calculations for which have been performed on Microsoft Excel. The statistical measurements skewness and kurtosis are used to assess and explain the normality of the returns. Finally, statistical approaches are used to determine the importance of the link between stock returns, the S&P 500 returns, and treasury yield returns.

Daily stock price for the stocks mentioned above were downloaded using Yahoo finance for the period starting from 1^st Jan 2019 lasting till 31^st December 2021. The following table contains the descriptive statistics of all the five stocks included in the portfolio:

• Mean – Mean return can be regarded as the expected return of a stock or a portfolio on a monthly or weekly basis (Oki?i? 2015). The stock of Apple, with a 0.20 percent return, has the greatest mean return among the other four equities. The stock of Alphabet, with a return of 0.14 percent, has the second greatest average return. The stock of Amazon, which has had a mean return of 0.10 percent over the last three years, has been the worst performer in the portfolio.
• Median – The median is the value that divides a set of data evenly between high and low values (Camarillo et.al, 2018). Facebook’s median was about 0.001235, which was extremely near to the stock market’s mean return, indicating that stock returns are more or less regularly distributed. Netflix’s stock also has a median value that is near to the mean of the returns, indicating that the stock returns are normally distributed.
• Minimum and maximum – The spread of a data set, which in this example is the stock returns of individual stocks, is determined by taking the minimum and highest values of the data set (George and Mallery 2018). The stock of Netflix has the most spread stock returns, with a range of 0.273853 and a minimum of -0.118095 and a maximum of 0.155758. The lowest range of returns are provided by the stock of Amazon which also has the lowest standard deviation.

• Standard deviation – The standard deviation is a statistic that quantifies how near values are to the mean of all the data. It’s a crucial statistic for measuring the risks in a portfolio using the individual returns of the assets included (Laha, Arbaiya and Linb 2020). With a standard deviation of 0.023936 and a mean return of 0.11 percent, Netflix’s stock has the greatest standard deviation among all stocks. The stock with the lowest standard deviation was Amazon’s stock, which had an SD of 0.018493 and a mean return of 0.10 percent, which was the lowest of all. Apple, the stock with the greatest mean return, has the third highest SD value of 0.021536.
• 25^th percentile and 75^th percentile – The stock of Netflix has the lowest 25th percentile return, with a negative return of -1.0927 percent, while Alphabet (GOOG) has the greatest 25th percentile return, with a negative return of -0.6275 percent. The stock of Netflix, with a return of 1.3989 percent, has the greatest 75th percentile return, followed by the stock of Facebook, with a return of 1.3706 percent. The stock of Google, with a return of 1.0035 percent, provides the lowest 75th percentile return.

The Sharpe ratio is a risk-return statistic that is calculated using three metrics: risk-free rate of return, stock return, and stock standard deviation. The Sharpe ratio of each stock, which quantifies the return gained per unit of risk, is shown in the table below. The risk-free rate of return in this study is the treasury yield on a 5-year government bond:

With a Sharpe ratio of 0.062, Apple’s stock offers the best return per unit of risk, followed by Google’s stock with a Sharpe ratio of 0.035. The stock of Amazon, with a Sharpe ratio of 0.018, provides the lowest amount of return per unit of risk.

The normal distribution, also known as the Gaussian distribution, is a symmetric distribution around a data set’s mean value, suggesting that data is distributed equally on both sides of the mean value. On a graph, a normal distribution is represented as a bell curve (Kim 2015). Skewness, on the other hand, examines the tail of the distribution by distinguishing heavy tailed or light tailed features, whereas skewness analyses the symmetrical attributes of a data set (Cain, Zhang and Yuan 2017). With the aid of a set of criteria and parameters, we may quantify the normality of stock returns utilizing Skewness and kurtosis values of the stock. A data set which is normally distributed has a skewness of zero and a kurtosis of three (Mei 2017). The following table presents the skewness and kurtosis of all the five stocks included in the portfolio:

Measures of Central Tendency

According to the data presented in the table above, the skewness of returns of the stock of Amazon is -0.049003 which is slightly above the parameter of 0 and the kurtosis of the stock is 2.6177 which is slightly below the threshold level of three, indicating that the stock of Amazon has the most normally distributed returns compared to all the other stocks in the portfolio.

Four of the five equities in the portfolio have a negatively skewed return, with Netflix being the only one with a favorably skewed return. According to (Managed futures investment 2015), the stock of Netflix has a positive mean with a positive skewness, which is a favorable indicator since it has more positive returns. Netflix’s kurtosis is likewise high, implying that the stock will provide more favorable returns on the extremes.

Apple’s stock has the most negatively skewed returns, implying that it provides more negative returns than other stocks. Due to larger tails, the stock will occasionally suffer dramatic negative returns.

Alphabet’s stock has a greater kurtosis, indicating that it has performed similarly to Apple’s stock. The stock’s skewness is less negative than Apple’s, implying that negative returns are less often in this stock than in Apple’s.

The treasury bond yield was calculated using pricing data from five-year US government bonds. The five-year bond was chosen since the stock price data was obtained for three years. The following table represents the covariance of each stock with the S&P 500 returns and treasury bill yield:

The following table represents the correlation of each stock with treasury bill yield and S&P 500 index:

S&P 500 returns

Null Hypothesis – Stock returns are closely related to S&P 500 returns.

Alternative Hypothesis – Stock returns are not related to S&P 500 returns.

P-values:

P-values obtained from a regression analysis determines the likelihood that a statistical measure of an expected probability distribution, such as the mean or standard deviation, would be larger than or equal to actual data and P-values less than 0.05 is considered to be significant. Regression was carried between each of the stock returns along with the returns provided by the S&P 500 index. The p-values obtained from the regression analysis suggests that they are significant and the stocks are heavily influenced by the return of S&P 500. Hence, we fail to reject the null hypothesis which claims that the stock returns are influenced by the returns on the S&P 500 index.

Measures of Dispersion

Treasury yields

Null Hypothesis – Stock returns are closely related to treasury yields.

Alternate Hypothesis – Stock returns are not related to treasury yields.

P-values:

Except for the stock of Netflix, the p-values of all the other stocks in the portfolio are significant which implies support for the manager’s assumption regarding stock returns getting influenced by bond yields. Investors are influenced by risk free rate of return and they make their investment decisions based on it. Except for the stock of Netflix, it can be concluded that the remaining stocks are influenced by the treasury bond yields. Hence, we fail to reject the null hypothesis.

Conclusion

This paper looks at a stock portfolio that includes “FAANG” companies including Facebook (FB), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOGL) (GOOG). The risk and return estimates are based on daily stock price data for the past three years, from January 1, 2019 to December 31, 2021. The highest returns were provided by the stock of Apple with the least amount of return being provided by Amazon. The riskiest stock to invest was the stock of Netflix based on the SD value. To examine and explain the normalcy of the returns, the statistical metrics skewness and kurtosis are utilized. Based on the analysis, we found that the stock of Amazon was more or less distributed normally as it had its skewness close to 0 and a kurtosis value of close to 3. Finally, statistical methods are employed to assess the significance of the relationship between stock returns, S&P 500 returns, and treasury yield returns. It was established that the managers assessment of stock returns being influenced by market returns and treasury bill yield was accurate and we failed to reject the null hypothesis.

References

Cain, M.K., Zhang, Z. and Yuan, K.H., 2017. Univariate and multivariate skewness and kurtosis for measuring nonnormality: Prevalence, influence and estimation. Behavior research methods, 49(5), pp.1716-1735.

Camarillo, T., Mathur, V., Mitchell, T. and Ratra, B., 2018. Median statistics estimate of the distance to the galactic center. Publications of the Astronomical Society of the Pacific, 130(984), p.024101.

George, D. and Mallery, P., 2018. Descriptive statistics. In IBM SPSS Statistics 25 Step by Step (pp. 126-134). Routledge.

Kim, T.K., 2015. T test as a parametric statistic. Korean journal of anesthesiology, 68(6), p.540.

Laha, M.S.C., Arbaiya, N. and Linb, P.C., 2020. STOCK INDEX MODELLING USING ARIMA WITH STANDARD DEVIATION BASED TRIANGULAR FUZZY NUMBERS. Journal of Critical Reviews, 7(8).

Mei, D., Liu, J., Ma, F. and Chen, W., 2017. Forecasting stock market volatility: Do realized skewness and kurtosis help?. Physica A: Statistical Mechanics and its Applications, 481, pp.153-159.

Oki?i?, J., 2015. An empirical analysis of stock returns and volatility: the case of stock markets from Central and Eastern Europe. South East European Journal of Economics and Business, 9(1), pp.7-15.

What is Skewness? | aiSource (2015). Available at: https://www.managedfuturesinvesting.com/what-is-skewness/ (Accessed: 8 March 2022).

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