Intro & Background After CHEK filed a report showing that Sabby Management filed to sell shares, it sparked some chatter online – none of which seemed to be consistent. So, we booted up Bloomberg and collected a list of all other times a company put out a similar report with the hedge funds’ name in it. Then we created a simple model that assesses what the underlying stock’s price did after the report was filed. We were interested in finding how high the stock gets using different time periods observed after the filing date, how long it takes it to get to its high, and then what happens afterwards. The outcome of our research shows that, while our calculations may lack some advanced math/academic prowess, stocks that file these particular reports experience enormous gains not long after the filings are released. We aren’t sure why, but they do. *Not financial advice* Model Mechanics Date of study: 05-27-2020 Search terms to screen filings on Bloomberg: “Sabby Management” + “Selling Shareholders” (CF function) We use this as a proxy to represent a point in time that Sabby Management shows up in a company’s equity offering filing. Number of results: 97 (from 07-27-2018 to 05-20-2020), number of unique companies: 30 97 reports across 30 unique companies (all being small-cap, most being biotech). Input = X = period length [days]. Chosen X value, for example: 100 We evaluate returns in the 100-day period following the filing (approx. 3 months) Column 1: Ticker Column 2: VWAP at date of filing [$] Column 3: Market Cap at date of filing [$] Column 4: Start Date = Date of filing [YYYYMMDD] All (most) of the 97 filings in the data set have a different starting date and ending date. Column 5: End Date = Lesser of a) Date of filing + X or b) current date [YYYYMMDD] I.e. if the filing was 2019-02-08, ending date = 2019-02-08 + 100 = 2019-05-19 (100 day period) However if the filing was 2020-04-21, ending date = 2020-05-27 (37 day period) When eliminating data points with <100 day periods, average returns exhibit insignificant changes. We kept them. Column 6: Intraday high of period [$] We are interested in finding how high the stock gets between filing date & end of the period (in this case, 100 days). Column 7: Return from Column 4 [%] (High of period – VWAP at filing date ) / VWAP at filing date, aka what is the HIGHEST return this stock generated Column 8: Days taken to reach intraday high of period [days] Column 9: Close of period [$] We are also interested in seeing what price the stock closed at by the end of the observed period. I.e. the stock’s price at day 100, rather than the stock’s price at its highest moment after the filing. Column 10: Return from Column 4 [%] (End of period – VWAP at filing date ) / End at filing date Column 11: Column 9 return from Column 4 [%] (End of period – High of period) / High of period I.e. how much the stock’s price came down since it’s high. Results Avg. Days Taken Period Length Avg. Return by Avg. Return at to Achieve High of % Fall from High (Days after Filing) End of Period High of Period Period of Period 10 -2.72% 16.16% 7.55 -15.37% 20 -2.81% 30.24% 14.09 -22.15% 30 -0.94% 43.33% 20.59 -26.25% 40 4.12% 52.14% 26.71 -28.17% 50 7.05% 58.23% 33.37 -29.84% 60 8.31% 72.34% 39.19 -34.28% 70 12.15% 84.74% 45.24 -36.68% 80 11.11% 86.61% 50.72 -37.80% 90 10.55% 87.75% 56.27 -38.83% 100 8.23% 92.62% 61.57 -41.56% 110 5.30% 94.13% 66.47 -43.16% 120 3.63% 94.85% 71.94 -44.46% 130 4.49% 95.30% 76.70 -44.75% 140 3.87% 97.55% 81.72 -45.83% 150 3.88% 98.78% 86.26 -45.90% 160 1.62% 100.37% 90.86 -46.72% 170 0.87% 100.56% 95.48 -46.94% 180 2.44% 100.76% 99.82 -46.46% 190 -0.09% 101.17% 104.56 -47.41% 200 -1.76% 101.62% 108.65 -48.48% The results above are straightforward: on average, when a filing is published including a) the term “Sabby Management” and b) “Selling Shareholders”, the underlying security’s price is expected to rise ~93% before closing the 100 day period up 8%. A visual representation can be found below using X values from 10 to 200: Further Analysis We are aware that there are 97 filings in the universe and only 30 unique companies (indicating an average of 3 filings per company). We created two separate spreadsheets, and still have them handy, limiting each individual company at 3 filings per name and 1 filing per name respectively, however the data did not exhibit significant changes. For example, using a 100-day period from filing data, the 3-filing limit produced an average intraday high return of 70% while the 1-filing limit returned 86% (vs. the raw data’s return of 93%). Our point is, there is a strong trend here: after the term “Sabby Management” shows up in a company’s equity offering filing, the stock experiences unusually high returns soon afterwards. Our goal following these findings was to learn if there was any relevance of the company’s market capitalization. For example, did companies with smaller market caps exhibit higher returns than those with larger market caps? To find this, we took a blank cell in excel (the “output” cell). Call this variable Q Formula 1: =AVERAGEIF(Market Cap at Filing Date,>Q, returns) Let’s say Q is “20”, which would mean $20 million market cap. This formula basically says: take an average of intraday high returns during a 100 day period IF the stock has a marketcap greater than $20mm Formula 2: =AVERAGEIF(Market Cap at Filing Date,<Q, returns) Same thing but switch out “greater” with “less”. Formula 3: = Formula 2 less Formula 1 The returns of companies with marketcap LESS than Q minus the returns of companies with marketcap GREATER than Q. We call this “smallercap outperformance”. We’ll get back to this later. Formula 4: = Same thing as Formula 1 except it just counts the number of stocks above Q marketcap. Formula 5: = ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ below ^^^^^^^^^^^ Formula 6: = Difference between formula 4 and 5. We want formula 6 at 0 to truly and fairly evaluate smallercap outperformance in the dataset. When formula 6 is 0, it means that the number of stocks above marketcap Q is equal to the number of stocks below marketcap Q. If the data were to be skewed either way, it may be biased. *Run solver to make Formula 6 equal to 0 by changing cell Q* Q = ~17. So out of 97 filings through 2 years, Sabby Management’s name showed up in 48 instances when the equity’s marketcap was above $17mm and 49 instances when the equity’s marketcap was below $17mm (as equal as we could get with a full number). So, which half performed better? MCAP>Q 57.49% MCAP<Q 127.24% Smallercap OP 69.75% *When Q is 17 The answer: Smallercaps by far. What does any of this mean and why is it good for CHEK? Sabby reported that they will be selling shares in $CHEK on 2020-05-20. It has been only 8 days since then and the stock has done nothing – which is normal, obviously (how can we expect such intense action so soon?) But remember, theoretically (calculated with our best efforts using empirical data), the stock should double in the next 100 days. And per our research that’s conservative. CHEK’s marketcap closed at around $16.8 million which JUST squeezes into the smallercap qualification. Bullish scenario would be 130% in the next few months based off nothing but Bloomberg API and simple calculations.