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Big Mover™ catalyst readouts for Feb 2021
Validation of Big Mover™ catalyst predictions
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Big Mover™ catalyst readouts are those that appear likely to move the stock price at least 20% if they read out strongly positive or negative. On January 11, 2021 we analyzed 39 companies in our BPIQ catalyst database for the likelihood that they were going to announce a catalyst readout between Jan 11, 2021 and mid-February that would move the stock price, at least 20% (Big Mover™ event). We performed this analysis based on the type of catalyst readout and by using stock options data, without performing deep fundamental analysis of the company or catalyst event. Of the 39 events analyzed, a group of 7 stocks were identified as Big Mover™ catalyst events within this time period. As of February 8, 2021, 5 of 7 of these Big Mover™ companies had read out their scheduled major catalyst event, and all of these readouts moved the relevant stock price by over 20%.
For this analysis, we performed both a technical and a fundamental approach to attempt to identify Big Mover™ events: For our fundamentals approach (“Readout Type” column in Table 1), we analyzed companies mainly that had some catalyst listed in our BPIQ™ catalyst database, which now includes catalyst info for over 1,000 clinical stage assets of biopharma companies with a market cap of between $100 million and $2 billion. For our technical approach (“Options Strategy” columns in Table 1) on January 11, 2021, we analyzed stock option data with a February 19th expiration date using several different volatility measures. The companies and their catalysts that were included in the analysis, and the results for all these companies, are shown in Table 2.
Those catalysts that are most likely large magnitude (at least 20%) mover events solely based on their type of catalyst event (e.g. Phase 2 and Phase 3 data readouts), not based on deeper analysis, are highlighted green. Those catalysts that are possibly significant magnitude type mover events solely based on their type of catalyst event (e.g. Phase 1 readout, PDUFA date), not based on deeper analysis, are highlighted in blue. For technical analysis using stock options data, we used 2 different values (A and B) for 2 different approaches (1 and 2) to predict the magnitude of stock move. Very High, High, Borderline High (Med/High), Med, Low, and Very Low indicated the magnitude of stock price move on or before February 19, 2021 predicted by the option analysis. As indicated above, based on this analysis, those companies in Table 1 that were most likely to exhibit a large magnitude price move (at least 20%) between January 12 and February 19, 2021 were categorized as Big Mover™ catalyst events are listed in Table 2.
Results of our Big-Mover™ catalyst event analysis are shown in Table 1, at the end of this article.
Those catalysts scheduled to occur on or before February 19, 2021 that are most likely to be mover events (e.g. topline readouts), were identified and highlighted in blue (mover events) or green for those events most likely to be the largest magnitude mover events (See Catalyst Event column in Table 1). The magnitude of the effect of a strongly positive or negative readout on stock price was then predicted using Stock options data with a February 19, 2021 expiration date (See Strategy columns in Table 1). On visual inspection of Table 1, a general correlation between predicted large magnitude movers is observed between the technicals/options analysis and the readout type (fundamentals analysis).
As indicated above, the most impactful readouts on stock price are typically topline readouts, especially phase 2 or phase 3 topline readouts, or PDUFA decisions, for a major clinical asset of the underlying company. However, not all data readouts, even phase 2 or phase 3 readouts move a stock price significantly, even if they are strongly positive or negative. For example, a clinical drug candidate might have a small revenue potential compared to other assets in a company’s pipeline. Or a positive result for a trial might be highly likely and already priced into a stock. Thus, we used the stock options data to help predict which of the catalyst readouts that are the type of catalyst readout that could move the stock significantly, are likely to be Big-Mover™ catalyst events.
Seven of the 39 catalyst events analyzed were identified as likely Big Mover™ catalyst events on or before Feb 19, 2021 based on this analysis (Table 2). Thus, Table 2 companies are those that are most likely to have the largest stock price move between Jan 11, 2021 and February 19, 2021 from the 39 companies we analyzed, most of which had some event to report-out before Feb 19, 2021.
Table 3, shows the performance of these predicted Big-Mover™ stocks as of February 8, 2021, and identifies any major readouts for these companies that occurred since our Big-Mover™ analysis on January 11, 2021. Even as of Feb 8, 2021, before 2 of the 7 potential Big-Mover™ read outs occurred, 5 of 7 of the Big-Mover™ stocks had a peak or minimum stock price between Jan 11 and Feb 8, 2021 that deviated by at least 20% from their Jan 11, 2021 closing price even when subtracting out the 16% gain of XBI a well-known small/mid cap ETF, during this time period. As far as the day after a readout, the stock price of all the predicted Big-Mover™ stocks whose important catalyst event read out as of Feb 8, 2021, moved by at least 20% by the next trading day close after a major readout. Thus, the Big-Mover™ Catalyst analysis based on readout date/type and options data appeared to effectively identify those catalyst events that would have a major impact on stock price if strongly positive or negative.
Notably in the analysis of Table 1, for some catalyst-type events that are less-certain to be Big Mover events, the options data provided a strong prediction. For example, AUPH had a PDUFA date before Feb 19, 2021. PUDFA readouts can be big-mover events, but it is a very case-by-case analysis. The options analysis correctly predicted that the AUPH catalyst would be a Mega-Mover event.
It is noteworthy that several readouts were identified correctly as Big Mover™ events or not by our stock options analysis, even though this was not clear from the readout type or our fundamental analysis. For example, DBVT only had a trial initiation in our BPIQ database for the relevant time frame. However, all our options calculations identified DBVT as having a Big Mover™ catalyst event in the relevant timeframe. In fact, each of our stock options calculations yielded a “Very High” magnitude stock move in this timeframe. Sure enough, on January 14, 2021 DBVT announced that their interactions with the FDA after receiving a CRL (i.e. rejection) for their peanut allergy patch NDA, yielded a potential path forward to approval with improved patch adhesion and manufacturing/quality control and a 6 month trial, which drove the stock price up from $3.74 to $5.66.
Furthermore, we were not certain whether the NKTR phase 1/2 data update of its bempeg asset that the company announced will happen by the end of this quarter, would be a Big Mover™ event, or even whether it will indeed read out by February 19, 2021 (See our bull/bear writeup HERE). From this Big Mover™ catalyst readout options analysis, it appeared that the market did NOT believe the readout would occur before Feb 19, 2021 and/or did not believe that it would be a Big Mover™ event. We did not realize at that time, that earlier that day at the JP Morgan conference, NKTR announced that they would not read out efficacy data from that trial until year-end 2021. Thus, the Big Mover™ options analysis helps to level the playing field between retail investors and institutional investors, who have much more access to senior management and much more time to stay on top of all company events/announcements.
As another example, a trial update appeared possible for ENLV on or before Feb 19, 2021 to our BPIQ analyst who initially analyzed the trial, although they were not certain of timing. The options data indicated that a significant price move was likely by Feb 19, 2022. Pm Feb 3, 2021 ENLV read out positive top-line data in COVID trial and the stock increased by 7% that day, but then over 100% over the next 2 or 3 days. Thus, once again, stock options data helped to give us further clarity from our initial insights that a major readout was going to occur.
Finally, the magnitude of stock move appeared to be predicted, at least in an approximate manner, by our Big Mover™ analysis. FIGURE 1 depicts the magnitude of maximum and minimum moves between Jan 11, 2021 and Feb 8, 2021 based on the classification of stock as Big-Mover™ through low or very low mover by this analysis. As can be seen from FIG. 1, Big-Mover™ stocks had the largest range of the magnitude of stock price change during the target date range, and low and very low had the smallest.
The data provided herein supports that our Big Mover™ analysis predicts large mover events quite well. This may not be surprising since stock options volatility data should be aligned with fundamental considerations by an experienced biopharma stock analyst. Nevertheless, it is valuable to have this predictive tool. For example, Big Mover™ catalyst analysis should help fundamental investors to quickly identify companies with upcoming big move readouts that may be worthy of their deeper experienced analysis. Furthermore, Big Mover™ catalyst readout information should be useful to help small-mid cap biopharma fundamentals investors gain more confidence about whether a particular event, if strongly positive or negative, would indeed affect a stock price significantly.
It should be noted that there are a number of limitations of our Big Mover™ analysis. For example, this analysis does not predict a positive or negative readout, just those that are likely to move the stock significantly up or down if clearly positive or negative. Furthermore, even for predicted Big Mover™ catalysts, the move on the actual trading close after the readout might not be up over 20% for numerous reasons. First, a readout may be a mixed positive readout, not clearly positive or negative. Furthermore, sometimes biopharma stocks run up into/before a readout. Thus, a positive readout on the day of the move might not have as much upward.
At BPIQ, we plan to use Big Mover™ analysis in future time periods to identify Big Mover™ catalyst events and to make such events available to subscribers on BPIQ.com. This information should be helpful to those who want to trade around biopharma Big Mover™ events. For example, such information will be helpful to options traders to devise options trading strategies that are based on large magnitude stock catalyst events. For example, options strategies that could be profitable on a large magnitude stock price move, regardless of whether it is up or down, are well aligned with Big Mover™ catalyst events.
We continue to study different options parameters to hone in our analysis to better predict with precision, for any given catalyst event, the extent of a possible move that the market is predicting. As part of this, we plan to continue to monitor the ability of various options volatility calculations to predict future stock moves around catalyst events. Investors need to be cautious about these methods. For example, options volume is low for many micro and small-cap biopharma stocks, which likely causes less precision in the options measurements. This may create some false negatives or positives (i.e. outliers) in the options data. Furthermore, for some low-volume micro and small-cap biopharma companies, there is no stock options market, and the calculations cannot be performed.
In conclusion, our Big Mover™ catalyst analysis proved effective at predicting high magnitude readouts. This information, which we plan to provide on BPIQ.com on a going-forward basis, should be valuable to biopharma investors.
Table 1. Jan/Feb 2021 (i.e. Mid-Q1 ‘21) Catalysts analyzed for larger stock moves.
Readout Type column is likely move based on the catalyst type - dark green if very likely big-mover catalyst event type, green if likely big-mover, blue is possible mover type of readout.
Strategy shows results for various options volatility analysis strategies; For Strategy - red is very low stock price move predicted by the stock options data; dark orange is low or med/low move predicted; blue is med/high or borderline high move predicted; white is medium move predicted; light green is High move predicted; and dark green is very High stock price move predicted by the options data.