The financial publishing sector often carries narratives that lead us to believe that correct fundamental and technical analysis can generate significant profits. However, this notion can be misleading. Real advantages are often fragile and can vanish in an instant when they gain widespread attention.
Here’s the good news: the quantitative method I’m about to present is both unconventional and distinct. More importantly, it relies on empirical data rather than mere assumptions about future volatility.
Publicly traded securities tend to exhibit a state of mathematical homeostasis, reflecting an average trend over time. However, employing GARCH (generalized autoregressive conditional heteroscedasticity) reveals that volatility distributions occur not in a linear manner, but rather in clusters that depend significantly on prior volatility events.
This means that recent triggers have a much more pronounced effect on market behavior than older ones. It seems intuitive, right? But it underscores a vital aspect of quantitative analyses: various stimuli yield varying outcomes.
My argument is that by matching the probability distribution of the particular stimulus with the main data set, we can form a bimodal distribution. Then, if the target population shows unexpected results, we may find a profitable opportunity for our options trading strategy.
Using option pricing data can help you figure out the most lucrative strategy.
Amgen (AMGN)
The crux of quantitative analysis is studying pricing behavior. To monitor such behavior effectively, it’s crucial to standardize price language from scalar signals to discrete signals. We do this by compressing the price data into blocks of 10 units for both upward and downward weeks.
Take Amgen (AMGN) as an example. In this framework, AMGN has recorded a 3-7-D sequence over the past 10 weeks: three weeks up, seven weeks down, indicating an overall downward trend. The specific order isn’t what matters most; rather, it’s how we respond statistically to this pattern.
Historical data indicates that under 3-7-D conditions, AMGN stock is expected to fluctuate between $285 and $310, primarily clustering around $297, assuming an anchor price of $291.76. If Amgen were in homeostasis, we’d expect clustering just under $293.
Looking ahead, it seems AMGN stock could reach a median price close to $300 within the next four weeks, with an excess rate over the starting point of around 65.5% in the fourth week.
Given these numbers, the options trades that appear most promising are: 290/300 bull call spread, set to expire on November 21st.
Costco (COST)
While membership retailer Costco (COST) might not fire up excitement for options trading, its contrarian attributes are intriguing. Over the past 10 weeks, COST stock recorded a 4-6-D sequence: four weeks up, six weeks down, showcasing an overall downward trend. Surprisingly, this sequence is rare, making up only 6.8% of all identifiable patterns since January 2019.
Under 4-6-D conditions, COST stock is predicted to settle between $920 and roughly $1,000, with clustering around $975, assuming an anchor of $932.14. Typically, baselines indicate price clustering closer to $962, which suggests bullish traders can benefit from a 1.35% positive delta in price dynamics.
It may not sound groundbreaking, but strategies like vertical spreads can amplify even minor differences. Also, market makers seem to expect little in the way of a rebound from COST stock.
Let’s delve deeper based on this data: 950/960 bull call spread, with an expiration date of December 19th.
Spotify (SPOT)
Spotify (SPOT) initially generated a lot of buzz, but that interest has somewhat shifted. That said, the stock isn’t necessarily lagging—it’s increased by over 44% since the start of the year. Still, short-term momentum has been lacking, with SPOT experiencing a decline of more than 9% recently, and Barchart’s Technical Opinion Indicator rates it a 24% Sell.
Despite its challenges, Spotify might be an appealing contrarian pick. The past 10 weeks show SPOT stock printed 3-7-D sequences, a rare occurrence at only 6.25% of recognizable patterns. Interestingly, SPOT’s probability distribution has two peaks for clustering: around $650 and $710.
Under baseline conditions, clustering is mostly centered at $665, indicating increased safety for SPOT stocks under homeostasis. When subjected to 3-7-D conditions, both risk and reward become more pronounced, offering both opportunities and threats.
Nonetheless, the higher average price clustering could attract some speculators. If that’s you, consider the 700/720 bull spread, set to expire on December 19th.
