Much to the delight of Hemispherx BioPharma individual and institutional investors, a reader and follower of StocksHaven Investments has evaluated the Price Per Share potential should Ampligen see FDA approval within the coming weeks.
The following article has been submitted by an investor named, Ace Spader
The much anticipated FDA decision on the Hemispherx Biopharma, Inc. drug Ampligen has held a large audience of traders glued to their computers while tirelessly posting rants and raves in various trading forums across the web. Some of the most popular topics have included wild conspiracy theories surrounding the dilutions by the company and the delays by the FDA. Others have postulated about all of the potential uses of Ampligen in the future with a particular emphasis on the pandemic flu.
Of all the topics seen and discussed recently, there is one that continues to resurface multiple times each day leading up to the FDA decision:
“How high will the HEB price per share go once Ampligen gets approved?”
This topic differs from the others in that we can come up with a result that is backed by facts, logic, and conservative estimates rather than just pure speculation. Out of my own curiosity I decided to tackle this problem. I believe my results will prove to be right on the money. My analysis calculates an estimated pps for HEB in the weeks following FDA potential approval of Ampligen to treat CFS patients in the US. We cannot predict what other events will occur to cause the pps to go higher or lower in that time frame, so I will just focus on the impact of this individual event.
- ((Total Customer Base * Annual Revenue Per Customer * Possible Market Penetration * Net Profit Margin) / Cost of Equity) / Number of Outstanding Shares = Expected PPS
I performed some extensive research to come up with fair estimates based on real world information for each of the variables in the equation. I then scaled the variables to come up with a conservative estimate. This is not an exact science, and some of the values could be quite different from what I have decided to use. However, by making an effort to err on the conservative side I can reduce the effect of errors that might be introduced by potentially inflated numbers found in my research.
The numbers found in my research:
- The generally accepted number of people suffering from CFS in the US is 4,000,000.
- Of those 4,000,000 about 20% are the cases that would be considered for treatment using Ampligen.
- In a recent survey of doctors over 50% said they would likely change their prescribed treatment for CFS once Ampligen was approved. I chose to use a more conservative estimate of 35%.
- The annual cost of Ampligen treatments is $14,400. I chose to use a much lower number $4,800 which is 33% of the known cost to account for potential economies of scale and to err on the conservative side.
- The number of outstanding shares at the time of my analysis was 110,670,341. This was taken from the most recent SEC filing.
- At the time of my analysis the average Beta for HEB was 0.87.
- The risk free rate is 0.0013. I used the 3 month T-bill rate found on Bloomberg.
- The market’s historical excess return rate is 0.067.
- I calculated the Cost of Equity using the CAPM formula: (Beta * Market’s Historical Excess Return Rate) + Risk Free Rate = Cost of Equity. I then doubled the result to once again err on the conservative side. The resulting calculated Cost of Equity was 0.12.
- C: Total Customer Base = 4,000,000
- R: Annual Revenue Per Customer = 4,800
- P: Potential Market Penetration = (20% * 35%) = 0.07
- N: Net Profit Margin = 0.15
- E: Cost of Equity = 0.12
- S: Number of Shares = 110,670,341
- ((C * R * P * N) / E) / S
- ((4,000,000 * 4,800 * 0.07 * 0.15) / 0.12) / 110,670,341 = $15.18
- A conservative estimate for the PPS of HEB shortly after news that Ampligen has been approved by the FDA is $15.
The Sanity Check:
One could argue that there is simply too much room for error for this result to be meaningful. After All I did make choices to scale some of the numbers found in my research in order to come up with a more conservative estimate. And, the raw numbers found in my research might also be flawed. For these reasons I decided to perform an additional analysis to come up with a range to account for estimation errors.
I applied the same formula to VNDA and TTNP using data from before the FDA approval of the drug Fanapt in order to gauge how accurate my estimate might be. The common business realities between Vanda Pharmaceuticals (VNDA) and Titan Pharmaceuticals (TTNP) allow me to apply the equation to both stocks using mostly the same values for key variables in the equation. This allows me to treat the common variables as constants thereby reducing variances caused by erroneous estimates. In simple terms by having less variables to adjust between the two calculations a more meaningful variance can be found. As it turns out there are only two variables that have different values between the VNDA calculation and the TTNP calculation, and one of those variables is the number of shares which has no room for error since it is a known number.
- C: Total Customer Base = 2,000,000
- R: Annual Revenue Per Customer = 7,900 (Market is 15.8 billion in US / 2 million customers = 7,900)
- P: Potential Market Penetration = 0.028 (Competing with 6 other drugs. Target customer base = 14%. [0.14 * 0.2 = 0.028])
- N: Net Profit Margin = 0.15
- E: Cost of Equity = 0.24 (Beta for both VNDA and TTNP was roughly double the Beta of HEB before the approval of Fanapt.)
- S: Number of Shares = 26,650,000
Predicted PPS = ((2,000,000 * 7,900 * 0.028 * 0.15) / 0.24) / 26,650,000 = 10.38
Known post approval peak PPS = 14.79
Difference between peak PPS and predicted PPS = 14.79 – 10.38 = 4.41
Deviation from predicted pps = 4.41 / 10.38 = 42%
- C: Total Customer Base = 2,000,000
- R: Annual Revenue Per Customer = 7,900
- P: Potential Market Penetration = 0.028
- N: Net Profit Margin = 0.08 (This number was disclosed.)
- E: Cost of Equity = 0.24
- S: Number of Shares = 58,290,000
Predicted PPS = ((2,000,000 * 7,900 * 0.028 * 0.08) / 0.24) / 58,290,000 = 2.53
Known post approval peak PPS = 1.70
Difference between peak PPS and predicted PPS = 2.53 -1.70 = 0.83
Deviation from predicted pps = 0.83 / 2.53 = 33%
The average percentage deviation from the predicted pps is (42+33)/2 = 37.5%. Using this information I can now apply a range of roughly plus or minus 40% to my HEB predicted pps of 15.
Lower limit = 15 * 0.6 = 9
Upper limit = 15 * 1.4 = 21
My analysis shows that the PPS for HEB will peak somewhere between $9 and $21 within the first few weeks given that the FDA approves Ampligen for treatment of CFS. It is important to understand that there are other potential uses for Ampligen on the horizon that could easily push the PPS beyond the conservative range that I have calculated. The most promising of these uses is the use of Ampligen as an adjuvant for influenza vaccines on a global scale.
I believe my analysis is very conservative, so I would not be surprised to see the PPS reach the upper limit of my range. And, if any other positive news comes out for HEB it could go beyond my calculated range later this year. I will be setting my sell limits very high, and I am long on HEB. I hope you all enjoyed reviewing this analysis, and hopefully you will find this method useful for other stocks in the future.
Ace Spader is a freelance web developer based in Chicago, IL. He has a BS in Computer Science from Northwestern University. He has no formal background in finance. Other interests include poker, singing, science and technology. He recently started a stocks related private Google group called Farseers. His future plans include developing useful online tools for organizing and sharing information on stocks
Disclosure: Long-Term Position
The formula used in this analysis was provided by Mohammed Miah, a graduate from University of Manchester and a B.A. in Economics with a focus on Finance.
By reading StocksHaven Investments you agree to the disclaimer, and thereby will not hold Michael Vlaicu accountable for any transactions or decisions you make. It is up to you to do your own due diligence.