FAANG – Review of 2019 Performance

** Intended for New Graduates **

(Click on the image to enlarge)

Wendy, a new college graduate with a major in Economics, is interviewing for the Market Analyst position.

Question # 1
Interviewer: Do you know what the acronym 'FAANG' stands for?

Wendy: Yes, it refers to five major stocks: Facebook, Amazon, Apple, Netflix and Google. In fact, I follow all of them very closely.

Question # 2
Interviewer: Okay, now take a look at the FAANG table and give us your interpretation of its overall performance.

Wendy: Obviously, Apple has hugely outperformed the other four components. While Facebook and Google produced fairly good returns, they were nonetheless below the S&P 500's 2019 return of 30%. Unfortunately, Amazon's return was sub-par while Netflix disappointed its investors. 

Question # 3
Interviewer: Why do you think we've added the Coefficient of Variation (COV)?

Wendy: COV is a very common metric used to demonstrate the volatility of asset classes and components. Amazon was the least volatile component while Apple was the most volatile in the FAANG complex.  

Question # 4
Interviewer: By simply glossing over the data series, would you have known that Apple was the most volatile in the complex?

Wendy: Yes, by simply looking at the data series I could have found it out. It has a much wider spread in the series than the rest, resulting in the highest COV and the volatility.


Question # 5
Interviewer: Was that the right use of the COV metric?

Wendy: It's perfectly fine in an interview setting. If I were compiling a report for a client, I would go back to the daily closing data, at least the weekly closing.

Question # 6
Interviewer: Okay, now switch to the Apple vs. Facebook chart and compare and contrast their performances. 

Wendy: They moved more or less in tandem during the first half of the year. Since then they produced significantly different performances. While Apple continued on a linear  growth path, Facebook moved sideways, remaining mostly range bound.

Question # 7
Interviewer: In terms of the market behavior, do you notice any similarity or dissimilarity between Amazon and Google?

Wendy: Yes, very dissimilar behavior. During the first half of the year, Amazon produced a nice run-up, while Google continued to decline. They however reversed courses in the second half.

Question # 8
Interviewer: Now let's move on to the Amazon chart. What is the point of overlaying the 2-month moving average trendline?

Wendy: To introduce a level of smoothing. It smooths out the noises that are inherent in month-over-month data series. For instance, the moving average trendline here is proving that the April and May data points are somewhat aberrations.   

Questions # 9
Interviewer: How would you graph all five components into one graph?

Wendy: By showing the month-over-month +/- growth rates, so they are apples-to-apples. 

-Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Link to the Book

Can FAANG Stocks Predict Dow Jones Industrial Average (DJIA)?

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John, a new college graduate with co-concentrations (Econ and Math) is interviewing for Equity Analyst with a major Hedge Fund. 

Interviewer: Thanks for interviewing with us, John. On that corner laptop you'll find a spreadsheet containing one year of daily closing prices - between 7/1/2018 and 6/30/2019 - pertaining to the Dow Jones Industrial Average (DJIA) and FAANG (Facebook, Amazon, Apple, Netflix and Google) stocks. Please analyze the data and give us your conclusions as to:

a) The FAANG stock that is most predictive of the DJIA so, from time to time, we could recommend it to our clients in place of the Dow ETF.

b) The FAANG stock that best represents as a hedge to the DJIA so it could be recommended as the DJIA becomes over-valued.

c) Finally, the FAANG stock that is highly predictive of the DJIA but has low multi-collinearity within the mix.

Once you are ready, just press 201 on this dial and I'll be back to talk to you.

___________________________________________________

As the interviewer returns, John presents his conclusions:

1. John -- The above correlation matrix clearly demonstrates that Amazon (AMZN) is the FAANG stock that is most predictive of the DJIA. The regression output, with DJIA as the dependent variable in the equation, further confirms it via its smallest standard error.

Interviewer -- But Netflix (NFLX) has better t-stat and lower p-value? Doesn't it contradict your conclusion?

John -- No. The correlation coefficient, which is the primary metric here, makes Amazon a far better (DJIA) predictive choice than Netflix.

2. John -- Of the FAANG components, Facebook (FB) is best hedge as it has the lowest correlation with DJIA. The regression out also confirms it via its negative coefficient.

Interviewer -- Would it be okay to recommend Facebook as a DJIA hedge to our clients?

John -- If the choice is limited to the FAANG complex only, yes. But there are other ETFs with much lower correlations with DJIA. I'd rather research and recommend one from the outside universe.     

3. John -- Apple (AAPL) is the FAANG stock that is highly predictive of the DJIA, but has lower multi-collinearity with the other components. The graph shows how Apple diverges from Facebook (which is the inside hedge component) with very low r-squared.

Interviewer -- Would you play the FAANG complex? If so, how?

John -- Each component has its own contributory properties so the complex as a whole makes a good investment vehicle. I would play it via a liquid FAANG ETF and as the DJIA becomes over-valued I would introduce an ETF with good hedging property.

   

Disclaimer - The author is not advocating the stocks/indices listed here. Consult your Registered Rep, RIA or Financial Planner for an appropriate asset allocation model and the suitability of stocks, indices and other holdings for your portfolio.


Good Luck!

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Link to the Book

How to Solve Complex Data Problems in a Job Interview (20 Live Simulations with actual Market Data)