Jeff Baker 9/5/2020
The “Basket” and Time-frame
**the examples and commentary given are for informational purposes only and as with any investment decisions you are encouraged to do your own due diligence and consult your licensed investment advisor**
As a Senior Analyst at Common Stock Warrants (CSW) and the primary data analyst, programmer, economic geologist, I have had the opportunity to run many Python simulations and placed our databases within the machine learning environment to find statistical abnormalities and patterns in warrants. This series of posts will focus on how the results of those investigations have led me to find a path to creating a rolling basket of securities that require far less capital to start trading with warrants. All of this is prefaced with an in-depth exposure to the trading methodology of Dudley Baker and CSW which seeks to secure thousands of percent in gains in longer term scenarios with warrants.
Return to the first part of this article series if any of the terminology or discussion in parts of this series needs clarification.
Without giving away the farm, I will allude to a system of calculations and processes that will not be fully discussed. The reason for this is partially proprietary and somewhat expansive as it relates to Python or Machine Learning algorithms, as it relates to this particular series of articles, the underlying methodology will be reserved for a different series on how to perform statistical analysis with your portfolio to increase the odds for success. These processes are being integrated at Common Stock Warrants after recent Graduate coursework at Penn State.
The trades in this series were conducted as an exercise, however, the implementation of our methodology as a tool would be ideal to provide the means to let subscribers develop a basket that they feel comfortable with. As of this time the tools are internal only, but we do see a time where these are implemented for subscriber use.
Now, you would think there was a magic ball that I was looking into and just spit out a list of 10 companies and voila… Well, that magic ball was called Python and the spitting out was more like statistics but let’s go with the former. I looked into my magic 8 ball, with only symbols and IDs to check against a variety of conditions. The list formed without any other coercion, and was ordered as follows.
- NFINW – Netfin Acquisition Corp
- TOTAW – Tottenham Acquisition I Limited
- SAQNW – Software Acquisition Group Inc
- KCAC.WS – Kensington Capital Acquisition
- CFFAW – CF Finance Acquisition Corp
- FPAC.WS – Far Point Acquisition Corporation
- SOAC.WS – Sustainable Opportunities Acquisition Corp.
- FTACW – Federal Street Acquisition Corp III
- NBACW – Newborn Acquisition Corp
- ALACW – Alberton Acquisition Corp
This list of warrants has a variety of industry specific classifications and deep dives into the companies would be prudent, however, most of this list had already undergone an extensive selection methodology with out-sized metrics on SPACs in particular, our index calculations, and potential for short term movements. The original list was actually 15 but has been truncated for the purpose of this article but does not omit the singular loser, but rather multiple that had 15-20 percent gains.
Now how long was the target time-frame? 7 days from the purchase to max length of time to exit or re-evaluate. In reference to the max length of time, this is somewhat arbitrary as it was a guide more than a rule. The max length signified the exit point barring a rational reason to stay. It does not exclude the possibility of an exit when favorable scenarios exist or present themselves. More than one example in that list had exit points that were attractive before the end of 7 days and would have been affected. The goal is to not have to day trade but to be capable of exiting when its time to take gains.
What is a SPAC? Special Purpose Acquisition Companies are used to provide an entry to the public market or rather the capital in that environment for private entities. They are generally formed via an IPO and seek to perform a merger or acquisition. News driven events of mergers can trigger parabolic changes in valuation.
Since our list is entirely comprised of SPAC entities with warrants, we are looking for their announcement of an event that will cause the explosive gain in a particular Warrant. This was not a guaranteed participant with this particular exercise; however, we were fortunate to have a great list of warrants that had really good days. Details on entry and exit prices will follow in the subsequent article of this series discussing the execution of the trades.
The basket now comprises a potential 300 dollars of each of the 10 warrants for a total cost of 3000.00 USD. Most of the participants in this list had not announced a merger, and all fit our price criteria. Odds of success were increased as a basket while also minimized as the gain would be shared across the basket, but so would a loss. This was not a “company story” based list of companies as would generally be part of a selection but rather a statistical methodology in case that was not clear.
OK so we now have our list with all the details, and target prices provided by Python and the previous close. It will be interesting to see each of their price ranges over the 7-day span and estimate a rational exit point if it was prior to the 7 days.
*As an investor, I have implemented this methodology in my own portfolio of warrants if they are a SPAC.
What’s the catch Jeff?
It would be pretty great if you decided to SUBSCRIBE to our database so that you can begin finding warrants that fit your investment needs. More hours have been spent curating and updating the data than any other service available and we seek to give the largest collection of these securities for helping you make sound decisions based on leveraging your cash into bigger returns. That is, after all, the beauty of the warrant as an investment vehicle… Leverage.