Investing Time Horizons: Why The Trigger Learned the Wrong Lesson On Eli Lilly (LLY)
Investors often lose out on positive returns by failing to understand the companies they are investing in and reacting to short-term price movements rather than long-term fundamentals. There are many ways to first identify potential investment ideas, but once the research begins, it is important to understand why the market values the business the way it does and what could cause that value to increase or decrease. Having a strong thesis should help investors maintain discipline when the price moves day to day or week to week.
A Strong Long-Term Thesis
Our investor bots are all learning, but sometimes they learn the wrong lessons. On Monday, one of our bots, The Trigger, had this to say:
LLY (20%) — GLP-1 Oral Catalyst + Sector Momentum: +6.11% this week while tech collapsed. Healthcare sector was the #1 performer this week (+4.53%). Orforglipron Phase 3 readout remains H2 2026. LLY at $1,255 — 1 share × $1,255 = $1,255 from $9,225 × 20% = $1,845 → 1 share. ⚠️ FRACTIONAL CHECK: $9,225 × 20% = $1,845 → $1,845 ÷ $1,255.40 = 1.47 → 1 share × $1,255.40 = $1,255 ✓
The stock selection and thesis on Eli Lilly is very strong and completely fits the strategy assigned to this bot. The company has proven winners with Mounjaro and Zepbound. These two drugs treat diabetes and obesity and went from zero a few years ago to $36.5 billion in revenue in 2025, driving revenue growth of 45% in a single year. The company saw what they had early in these drugs and in the early clinical success in the oral version, Foundayo, and invested heavily in production facilities to the tune of $18 billion. Q2 2026 saw 48% revenue growth year over year, and the company raised revenue guidance to $85-87 billion for the year.
Revenue for Foundayo is barely registering yet, but the company bet big on its success. Analysts aren’t sure what to model. There is also a race from other companies to close this gap, but the huge infrastructure advantage Lilly created could give them quite the head start. If the drug outperforms over the next several quarters, it could signal continued strong revenue growth ahead for the company over the next several years.
A Rough Week
Eli Lilly had a down week, so this is what the bot had to say:
Memory (Week 11): LLY cratered -5.80% — the GLP-1 catalyst thesis failed to hold amid healthcare sector-wide selling (-2.03%), and HALO dropped -3.03% compounding the damage; MCO's modest +0.70% was the only position that didn't hurt us. The 35% cash buffer cushioned the blow but the concentrated healthcare/pharma bet was wrong timing — need to reassess whether LLY catalyst remains intact or if the thesis has broken down before adding back exposure.
Same Story, Different Price
Despite the bot’s really nice analysis of the company and its potential, it is questioning its decision based on this week’s sector rotation in the market. Nothing about the story has changed, only the price has changed. In fact, the bot has already traded in and out of stock a month earlier and lost $50/share then, too.
Matching Time Horizon to Thesis
The bot is struggling with its time horizon. It’s easy to point out this lesson, but many investors struggle with this. Emotions get the better of us, or we don’t understand the company as well as we thought. A sharp drop can lead us to cut our losses to avoid further pain, or pocket a quick gain and miss out on long-term appreciation that can be really meaningful. In this case, we will see how the story plays out for Eli Lilly. The bot has keyed in on the catalyst, even if it is missing the time horizon.
Is Our Own Competition Making This Worse?
Our competition may be warping the bots’ perspective. They are all competing for weekly wins, but we gave two of them long-term strategies to execute. It makes for compelling content, and we get a lot of analysis out of the bots as they select stocks. Still, it would be a nice contrast to see the tortoise versus the hare play out. The Steward is a little more patient, but still changes occur there almost weekly.
What We Are Considering?
We are early in the first competition, but we may need to clarify our instructions so the bots aren’t trying to win week to week at all costs, often playing sector rotations and wondering why a thesis didn’t play out over the course of a week instead of playing out over quarters or even years. In the meantime, the bots continue to learn and so do we. Hopefully others can learn along the way as well!
