The S&P 500 and the Power of Indexing

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Nerfbow · September 6, 2026

No matter how sophisticated the strategy or approach, the S&P 500 is the toughest opponent in investing. As we get close to winding up the first competition and reset the bots, it is worth noting the real winner of our competition, the S&P 500. Since we built the bots, the S&P 500 has returned 3.86% or approximately 4.1% if dividends are included. At launch, the S&P 500 was 7,431.46, and it closed Friday at 7,718.60. We didn’t build it, but it is really tough to beat. Here are the final standings if the S&P 500 is included:

Competitor	Season Return
S&P 500	+4.1%
The Steward	-1.8%
The Trigger	-12.10%
The Risk Taker	-27.55%
The Consensus	-85.51%

The Risk Taker boomed and busted over 12 weeks, while The Consensus just chased the momentum trading of the other bots, but was always a week behind.

The History of the S&P 500

The S&P 500 was released on March 4, 1957, when it was expanded to approximately 500 stocks like it is structured today. Prior to that, the lack of electronic calculation methods made it too difficult to compile the data for so many companies. Since that day, the compound annual return for the index is 10.71%. There are good years and bad years included in that number, but many more good years than bad.

Back in 1957, $1,000 adjusted for inflation would have been equivalent to about $84.15. If you had put $84.15 in the S&P 500 at that point, it would be worth $99,151 today. Over 69 years, the equivalent of $1,000 would be worth about $100,000 today even after inflation. The past isn’t the future, but let’s admire that.

The S&P 500 is Difficult for Anyone to Beat

There are a lot of active managers of mutual funds in the market and a lot of marketing hype, but buying a low-cost S&P 500 ETF or mutual fund has outperformed active management. In 2025, 79% of all actively managed large-cap mutual funds failed to beat the S&P 500. In 2024, 65% of active managers failed to beat the S&P 500. Stretch the horizon out to 15 years, and the numbers for active management gets even worse. Over 15 years, 89% of actively managed funds fell short.

Industry groups do dispute these numbers, arguing that the equal weighting of these actively managed funds includes some smaller, less successful funds that skew the results. Still, the majority of professionally managed funds don’t beat the S&P 500 index.

Why is the S&P 500 So Hard to Beat?

It is difficult to beat because it is the 500 best companies traded on the U.S. exchanges, and it is weighted towards the most successful companies with the highest market capitalizations. It automatically rebalances towards the most successful businesses. It also doesn’t cost a lot to index. There are no large asset management fees to offset research teams and marketing departments with the need for profits after expenses. There is not a lot of turnover, buys or sells. Low fees are the primary driver as actively managed funds with lower fees tend to outperform actively managed funds with higher fees. Those fees compound over time and cause a real drag on performance.

Using the S&P 500 on Your Investing Journey

I’m not anyone’s financial advisor, but I have always been a proponent of the index plus a few strategy. The S&P 500 serves as the base. If someone is interested in learning more about investing, they could always add a few companies to their portfolio while the S&P index does most of the work and has the highest allocation. It is a way to learn while not taking too much risk. Personally, I have become more concerned about the concentration risk of the AI trade in the S&P 500 as the top 10 companies have grown to comprise almost 40% of the S&P 500. Diversification remains a sound risk-management idea.

As we start a new competition with our bots, we will guide them toward them to a more patient approach. They tended toward more trading in their first attempt, always chasing market momentum. We will see if they can improve over the next quarter.

As always, this is not investing advice. We are all learning here!

Investing Time Horizons: Why The Trigger Learned the Wrong Lesson On Eli Lilly (LLY)

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Nerfbow · August 29, 2026

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!

Is Options Bot Cheating?

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Nerfbow · July 3, 2026

In three full weeks, our Options Bot has turned $10,000 of fantasy cash into $51,853, a 418.5% return. We are very suspicious.

I have never been a day trader. I am mostly a long-term investor, but I will play around with option strategies every once in a while. It is not a game, and it is difficult to be consistently correct. I know there are successful traders out there, but I also think it is exceedingly rare. I’ve always preferred to have time on my side. The expert investors will preach that it is best to buy good companies at fair prices and then just hold. The biggest mistakes are often selling good companies too soon.

Options Bot is taking the opposite approach and seems to be winning. I’m trying to learn from it. What is it doing? On Wednesday, the bot noted:

The market is broadly ripping — SPY +1.56%, QQQ +1.23%, VIX collapsing to 16.57 (-2.3 WoW) — a low-IV, high-momentum environment. Several existing positions are printing massive wins: RDDT +120%, APP +142.8%, both on monster underlying moves (+25% and +26.6% respectively).

I know the VIX is a measure of volatility. I had to look up IV – it means implied volatility. It is also a high-momentum environment. I had to look up what this meant. This combination is generally considered a highly favorable environment. Because the stock is moving with high momentum, the underlying asset's price appreciates. Because IV is low, the cost to enter a directional call option is affordable.

So, is Options Bot playing momentum at the exact time that it is most favorable to do so? We started digging into its trades. I even followed along on one Thursday (or tried).

Thursday, midday, Options Bot reported a position on Mastercard. It bought 15 calls with a $575 strike price and 7/31 expiration at $2.43. There was a huge rotation into quality companies occurring yesterday, and Options Bot was playing the momentum. I went and looked at this option. It had a bid of $0.20 and an ask of $4.65. The logic is ($4.65+$0.20)/2. Basically, splitting the bid/ask. This is the right logic, but there had been 0 trades on this option all day and somehow the bot was going to get a perfect split with 15 contracts? The exit was also very profitable for the bot, of course, as it just split the bid/ask that I could never achieve.

I tried to enter the trade, and the market makers immediately moved the price away from me (or their algorithms did). I was quickly seeing a bid ask of $3.00/$6.00 while the stock was mostly flat. We think this happens often. The math is sound, but it isn’t practical.

Is Options Bot cheating? Not exactly, but we need to make some changes to make this more realistic. We are looking at requiring a minimum daily volume before the bot can enter a position or building in a realistic slippage assumption instead of a perfect bid/ask split. As always, this post is not investment advice. We are learning. Please don’t follow the bot here. That dude is suspicious!

BuffettBot’s Curious Holdings

BuffettBot currently has four holdings: cash, Visa (V), Moody’s (MCO), and MercadoLibre (MELI). Most of these make sense, but one seems a little out of character.

The company that the actual Warren Buffett used to run until very recently, currently holds just under $400 billion in cash and treasury securities. That’s a record high, and a good indication that there is not a lot of fair prices available in either the public or private markets to deploy this absolute hoard of cash. Berkshire is one of the largest holders of U.S. treasury securities in the world. Berkshire’s entire public equity portfolio (Apple, Amex, Coke, etc. combined) is valued at about $288B — meaning the cash pile is actually larger than the entire disclosed stock portfolio. So, the BuffettBot tracks on cash. It can’t find a lot of value either.

The next largest holding of the BuffettBot is Visa. Berkshire Hathaway actually held a small percentage of Visa since 2011 until it was sold in the first quarter of 2026. The Buffettbot is tracking this pretty well. A quick summary of what the bot might be seeing:

• Margins: Gross margin ~98%, operating margin ~65–68%, net margin ~51.7% — about as close to a "toll booth" business model as exists

• Growth: High-single to low-double-digit revenue growth; consensus 5-yr revenue CAGR ~9.4%

• ROIC: ~40% (5-yr average), against an estimated cost of capital around 6% — an enormous spread

• Valuation: Trailing P/E has ranged ~24–30x over the past two quarters; forward ~23–24x

• Owner earnings yield: FCF conversion is exceptional (FCF roughly tracks net income), so the earnings yield is in the same ballpark as the P/E implies — roughly 3.5–4%

• Moat: Two-sided network effect — 130M+ merchant locations on one side, billions of cardholders on the other. Widely rated a "Wide" moat (Morningstar concurs).

It is worth noting that some analysts are starting to note some emerging risks to this business from stablecoins/instant payment processors. This could be a longer-term threat to the 2–3% transaction-fee model. I doubt many would consider Visa to be cheap right now. That puts it squarely in “great business, full price” territory, in my view.

The next largest holding of the Buffettbot is Moody’s (MCO). Berkshire Hathaway has held this stock for 26 years, so Buffettbot is again tracking the real deal on this entry. Similar to Visa, likely not cheap. Moody’s has a Near-duopoly with S&P Global in credit ratings, protected by regulatory licensing (NRSRO status) that makes new entries very difficult. The business is capital-light, and converts intellectual capital into high-margin recurring revenue. Some additional information:

• Margins: Gross margin ~74%, operating margin ~45% GAAP (~53% adjusted), net margin ~32%

• Growth: Q1 2026 revenue +8% YoY to $2.1B; FY2026 guidance calls high-single-digit revenue growth, adjusted diluted EPS of $16.40–$17.00

• ROIC: ~29.5%; ROE ~71% (leverage-boosted)

• Valuation: Trailing P/E ~33.6x, forward ~25–28x, PEG ~2.0x — not cheap by any traditional screen

• Owner earnings yield: TTM FCF ~$2.3–2.6B against an ~$82B market cap ≈ 2.8–3.1% — well below what a strict Buffett-Munger 20–30% margin-of-safety discipline would want

• Moat: Wide, durable, arguably widening (AI-driven demand for "decision-grade" data is a new growth leg on top of the ratings business)

The final holding is MercadoLibre (MELI). This one is an odd entry from the Buffettbot. It seems unlikely that the real Buffett would invest in such a business. That doesn’t mean it’s a bad business, just not the usual entry from the real Buffett. The BuffettBot is likely seeing the following: Two-sided network effect in Latin American e-commerce (more sellers → more buyers → more data → better platform), plus Mercado Pago, which has grown from "let underbanked users pay for stuff" into a real digital-finance business with ~20M credit users. First-party data advantage in ad-tech is also becoming a real margin lever.

• Margins: This is the catch — margins are compressing, not expanding. Q1 2026 operating margin fell to 6.9%, and adjusted free cash flow was actually negative $56M in the quarter

• Growth: Revenue +49% YoY in Q1 2026 to $8.8B; GMV +42%, credit portfolio +87% — very strong top-line, but growth is being bought with heavier investment

• Valuation: Trailing P/E ~46x against a "fair" modeled P/E closer to ~36x by some estimates; DCF-based views would argue it's undervalued by 30–45%, while multiple-based views see it as fully or richly priced — a real split in how analysts are reading it right now

• Owner earnings yield: Not meaningful to quote right now given the negative quarterly FCF print — this is explicitly a "we're sacrificing near-term owner earnings for market share and ecosystem depth" story, closer to growth investor logic than classic Buffett-Munger logic

• Moat: Improving on the data/network side; genuinely uncertain on the credit side (this is a lending book, and lending books can hide problems until they don't)

Before I conclude, I want to note that this isn’t investment advice. I’m just commenting on what our bot is doing and the likely reasoning. The cash hoard it is holding is totally in line with what Buffett/Berkshire are doing now. The company isn’t seeing a lot of value and neither is the bot. I find it really interesting how this bot is executing on this strategy!

Welcome to InvestorBot Live!

Welcome to InvestorBot Live! It all starts here. Three investing philosophies, four AI bots, one live competition. We are building this site to further our knowledge of equity markets and artificial intelligence.

This is the perfect collaboration project for my brother and me. I have 30 years of investing experience, having studied all the masters, and my brother has a lifelong interest in technology and deep interest in the growth of artificial intelligence. As we began sharing information, it became obvious that this project was worth sharing. We were fascinated with how the bots were applying the strategies we were giving them and we were both learning from what they were doing.

As we launch, we have four bots executing their strategies. The trading is not real, but it is based on current market conditions. The universe of equities are small to start. It is based on a screen of stocks that exhibit high returns on invested capital. Each bot has a fully documented strategy the scans this small universe of companies at the market open, mid-day, and just before the market close. The competition is tracked since inception and broken down week by week. You always get to see the each bot’s holdings and their summary for the week. Track this competition live!

We do not view this as a stock picking service. This is not investing advice. We view this as a process of learning. We love seeing how the bots are executing the strategies that we gave them. We also created a bot that attempts to synthesize the other three strategies. It is trying to do what we are trying to do, learn what works best. The best part is that the bots are programmed to learn and that we get to learn right along with them!

We will continue to add strategies and the bots will continue to improve. We will comment along the way to share what we are seeing. Soon we will open subscriptions for the deeper learning and decision process of the bots. Our universe of stocks will expand. The bots will improve. Pick a strategy, and follow along to see what strategy wins!