I’m going to tell you a little secret. While the financial publishing industry has been dominated by fundamental and technical analysis methodologies, the harsh reality is that these approaches do not actually qualify as “analysis.” Rather, they are opinions based on someone’s interpretation of fair value or breakout patterns.
However, describing a methodology as a mere assumption would lose credibility. So we just slap the analytics label on it and suddenly the underlying process becomes a certified discipline. Only in the United States, friends.
While opinions are wrong per se (after all, any forecast about the unknown future is exactly that), the issue centers on contingency. In fundamental and technical analysis, both the premise and the conclusion come entirely from the author; change the author, change the analysis. This means that the insights and overall viability of a forecast depend on the analyst as an individual, not on the analysis as a research protocol.
Fortunately, there is a better way to solve this mess and that is quantitative analysis. Crucially, the quantitative approach is based on observations from GARCH (generalized autoregressive conditional heteroscedasticity) studies, which describe the diffusion properties of volatility as lumpy and non-linear phenomena.
So, by logical deduction, the quantitative model works with this probabilistic engine: different market stimuli produce different market behaviors.
It’s really common sense. For example, a 250-pound linebacker can exert more force than a 160-pound cornerback. So what we do in the market is identify these linebackers and calculate the force they would be expected to generate.
Essentially, by finding strength, we find the propensity for where a value can end up. With that introduction out of the way, let’s look at some compelling ideas.
Recently, Barchart content partner MarketBeat published an article stating that Keurig Dr Pepper (KDP) was in the “buy zone” and now is the time to build a position in KDP stock. I agree with the statement but must admit confusion in the methodology. Specifically, the analyst points out that institutional trends are solid as an upward catalyst.
Furthermore, the author pointed out the technical trends and stated that “the KDP stock market is unlikely to fall below critical support targets in this scenario.” But how does the expert calculate the probability of not falling below support? This statement is simply taken for granted and that is where the usefulness of technical analysis falls short. Fortunately, quantitative analysis goes deeper.
Based on the quantitative model, we know through data collected from January 2019 onwards that the projected 10-week results of KDP stock form a distribution curve, mainly oscillating between $27.12 and around $27.37 (assuming an anchor of $27.16, Friday’s close). Furthermore, the price grouping would be predominant at around $27.22.
However, KDP stock is currently structured in a 3-7-D formation: three weeks up, seven weeks down, with an overall downward slope. According to this sequence, the price grouping would be predominant at around $29. Therefore, looking at the debit-based transactions available through a Premier Bar Chart membership, the 28/29 bullish call spread Arguably expiring on December 19 makes more sense.
Do you know how else we can decipher the epistemological deficiencies of fundamental analysis? Analysts often have wildly divergent price targets, which shouldn’t make sense. We know that Wall Street uses the same methodology called fundamental analysis. Therefore, if the methodology resembled anything close to a science, analysts’ price targets would be lowered. Instead, they sometimes become broader, even with the introduction of more data!
Take a look at Texas Instruments (TXN). What’s fascinating about this semiconductor giant is that the spread between analysts’ highest price target and the average outlook is a whopping 30.2%. Furthermore, the difference between the high and low targets is 100%. You see it with your own eyes. People are just guessing. The only reason they have credibility is because they appear on TV and wear a nice suit.
Under baseline conditions, TXN stock’s 10-week performance profile ranges from $159 to $169 (assuming an anchor of $161.46). However, at this time, TXN is structured in a 3-7-D formation. Under this sequence, the expected risk-reward spectrum expands to $157.50 on the low side and $175 on the high side.
Significantly, the price grouping would be predominant at around $167. This translates into a positive delta of 6.03% in price density dynamics. Those who are aggressive may consider 165/170 bullish spread which expires on December 19 and has an equilibrium price of $167.20.
Saving the riskiest idea for last, Carvana (CVNA) has been struggling due to a mixed earnings report. While the company posted impressive revenue of $5.65 billion, which beat the consensus view of $5.08 billion, it missed its guidance. CVNA shares subsequently fell 14% in the trading week ending Halloween. Furthermore, in the last month, the value fell more than 22%.
Still, for those willing to take a risk, CVNA stock could be an intriguing contrarian opportunity. Under baseline conditions, CVNA’s 10-week projected results would be expected to range between $290 and $365 (assuming an anchor of $306.54). Furthermore, the price grouping would be predominant at approximately $319.
However, the safety is currently structured in an ultra-rare 6-4-D sequence. Under this framework, the tail of the risk would be approximately the same as the bottom (approximately $290). However, the reward queue would skyrocket beyond $400. The most significant thing is that a price grouping at $363 would be expected.
With these figures, the most tempting business would be Bullish Spread 350/360 which expires on December 19 and has a maximum payment of more than 233%. Those who want a more probabilistically manageable trade can consider the 330/350 bull spread, which also expires on December 19. However, the payment would fall to 145.4%.
On the date of publication, Josh Enomoto had no (directly or indirectly) positions in any of the securities mentioned in this article. All information and data in this article are for informational purposes only. This article was originally published on Barchart.com
