What are the Current Market Conditions?

(Fig. 1) Year to Date S&P 500 Daily Prices vs. New U.S. Covid-19 Daily Cases - These animated charts show their respective changes from 12/01/2020 up to 6/26/2020. The trough of the S&P 500 index is 10 days prior to the peak of new daily Covid-19 cases in the United States. Moreover, as we are seeing a new surge in late June, the stock market has also taken a dip. The visual makes a strong case that the two could be negatively correlated.

(Fig. 2) The stock market doesn't care. Better yet, it never has - The top visual again documents the S&P 500 Index's daily closing prices, but it also annotates significant world events. Namely, the Coronavirus, protests, and space activity. Surely, most of these events should negatively impact stock prices? The surprising results show a quick V shape recovery from its 3/23/2020 trough. 2020 is not an outlier, if we observe an eerily similar year (e.g. 1968), we can observe some common themes.

• 1. (1968) Stemming from Hong Kong, the H3N2 Pandemic Flu killed 1 million people worldwide and 100,000 Americans vs. Covid-19

  2. (1955 - 1975) Vietnam War vs. recent U.S. tensions with China and Iran

  3. (4/4/1968) MLK was assassinated, leading to protests and riots. Additionally, students all over the world gathered to protest the Vietnam War vs. the protests against police brutality that occurred in every state

  4. (10/11/1968) Apollo 7 mission vs. (5/30/1968) Space X launch

Not only are these events similar in type, these events seemed to have minimal negative impact on S&P 500 performance.

Hunting for Whales

While potentially lucrative, below are 5 reasons why investing in a "Blockbuster" vaccine company may not be a prudent decision:

1. Public Data - How is an individual investor to know which company to pick based on public information?

2. Barrier to Entry - Being a global pandemic, institutions across the world have entered this arms race. There are not straightforward approaches if the company is overseas? Although, buying ADR's could be a way around this. Moreover, What if it's a private company? Most individual investors can only buy public shares.

3. Efficient Market Hypothesis - The belief that share prices reflect all information and that consistently beating the market is impossible. Giving an example; if a company reports vaccine progress, their stock prices surge! If a company's stock price is already up 2,000% (NVAX's approximate YTD performance as of 6/30/2020), how much more do you think its going to go up?

4. Government Intervention - A Covid-19 vaccine would presumably be very profitable for a company. However, it's in the world's best interest to make this vaccine accessible; meaning the vaccine cannot be too expensive. While governments are not always the best at this, it is possible they may step in and create limits on the maximum price of the vaccine.

5. Revenues Impact on Share Price - Just because a company creates a drug or vaccine that generates a lot of revenue, that doesn't mean its share price is going to change by the same magnitude or direction.

While a drug is not the same as a vaccine, there are a handful of examples where a Pharmaceutical company developed a Blockbuster Drug, generating that same company more than a billion dollars. I was curious how this revenue growth impacted a company's share price and imagined this could be a good comparison on how a company's creation of a Coronavirus vaccine may impact it's company's share price.

Companies with a high f-score, a score of 8 or higher

Piotrsoky believed that if a company had a score of 8 or higher, then that company would be an excellent value opportunity going into the consecutive year. Moreover, his study showed that "an investment strategy that buys expected winners and shorts expected losers generates a 23% annual return between 1976 and 1996" (Piotrosky, 2002).

This project's study

While Piotrosky's paper, quant forums, and articles all point to this being a robust algorithm that works across time, this had to be tested. Analyzing quarterly data during the Great Recession (late 2007 - early 2009) and the following 6 quarters, I was able to compile a dataset that measured how well this hypothesis worked during a recession, after a recession, and together.

(Fig. 3) Performance by Piotroski's F-Score During Great Recession (2008) - Companies with an F-score of 9 demonstrated a 59% likelihood of outperforming other Russell 3000 Index constituents in the following year.

(Fig 4.) Performance by Piotroski's F-Score, Post Great Recession - At 67%, companies with an F-score of 9 after the Great Recession demonstrated an even stronger likelihood of outperforming other Russell 3000 Index constituents in the following year. Not as significant, but companies that scored an 8, outperformed 54% of the time in the subsequent year.

(Fig. 5) Performance by Piotroski's F-Score (2007Q4 - 2010Q4) - Analyzing both datasets together, companies with an F-score of 9 demonstrated a 61% likelihood of outperforming other Russell 3000 Index constituents in the following year. Overall, finding companies that score a 9 seems like a reliable approach.

Future work

Aggregating Data for the Model

1. Evaluate Survivroship Bias impact to the model. Only rows (companies) that had fundamentals for every variable were included. Could this have misrepresented my training and test datasets?

2. The F-Score was a significant contributor to choosing investments. However, it would be helpful to include more variables so I am not relying as heavily on this one screener. Additional variables could lead to more machine learning opportunities.

3. The scope of this project was analyzing winners by one year performance. A deeper dive into how

Mitigating Risk

1. The MSR appears to be the most attractive portfolio, but I would be intrigued how MSR portfolios perform in the long run. The GMV may be a better asset allocation if the investor is looking to hold these securities for a longer period.