Do Newsletter Picks Beat a Simple Index Fund? We Ran the Numbers

The data

We measured 120 teased picks from the teaser date. The median one-year return was below the index, while a few big winners lifted the average.

What it means

Teasers can surface interesting ideas, but buying every pick is unlikely to beat a low-cost index fund after fees and subscription costs.

What this sample can and cannot establish

The article describes a sample of 120 teased stocks and says the median one-year return fell below the index. A few large winners lifted the average. Those statements are not interchangeable: the median describes the middle observation, while the average incorporates the size of every gain and loss. An average above the median can reveal a skewed distribution without showing that a typical subscriber earned the average.

The source data in this project are illustrative, and the complete 120-pick ledger is not supplied here. Consequently, this article should not be read as an independently reproducible audit of actual publishers. We can explain a defensible evaluation method and discuss the displayed examples, but we cannot calculate missing observations or certify the headline sample from the visible records alone.

The distinction matters because a persuasive summary can hide selection decisions. Were all recommendations included, or only stocks that received widely distributed promotions? Were repeated campaigns counted as new picks? Were failed companies retained? Before accepting a scorecard, ask for a dated list of the observations and a clear statement of the inclusion rules. Without those, an attractive average is difficult to interpret.

A consistent 30, 90, and 365-day method

Use the first documented teaser date as the signal date. The existing scoring convention uses that day's closing price. Preserve that convention for comparability, but explain that readers might not have been able to buy at that close if the message arrived later. A separate next-session execution test can show whether that timing assumption materially changes the conclusions.

Measure returns after 30, 90, and 365 calendar days. If a target date falls on a market holiday or weekend, apply one disclosed rule, such as using the next trading session. Do not move the endpoint selectively to capture a favorable quote. Keep picks without sufficient follow-up out of that horizon's average and report the number of eligible observations for each window.

Compare each stock with the S&P 500 over exactly the same start and end dates. Use total returns, including reinvested distributions, for both where reliable data permit. Comparing a stock's dividend-inclusive return with a price-only index is inconsistent. Report excess return as the stock return minus the benchmark return in percentage points. A 12% stock gain against a 15% benchmark gain is negative three percentage points of excess return.

Pick-by-pick reading of the displayed examples

Broadcom and Palantir illustrate why an attractive industry label does not settle a recommendation's merit. One is presented through an AI chip narrative and the other through a software and government narrative. To score either fairly, capture its own original promotion date and benchmark window. Do not rank their displayed price changes as if both investors had started on the same day or held for the same duration.

IonQ and Taiwan Semiconductor provide another useful contrast in the sample lookup. Both can appear in technology newsletters, but the underlying businesses have different commercial maturity, financing needs, and operating risks. A strong result from one would not validate every technology promotion by the same writer. Review each recommendation's original reasoning, its downside disclosures, and the conditions that would have invalidated the thesis.

Eli Lilly and Hims & Hers likewise should not be merged into a single healthcare success story. They represent different business models and regulatory exposures. Rocket Lab and SoFi add still different sources of risk. The displayed lookup snapshots are starting points for case studies, not verified 365-day returns. Their dates also need reconciliation with article publication dates before they can support a historical scorecard.

Patterns that can distort the verdict

A newsletter with several related picks may really be making one large sector bet. When that sector rises, the writer can appear to have repeated independent successes. When it falls, the same concentration can dominate losses. Compare sector exposure, position overlap, and broad market conditions before attributing every favorable outcome to stock-selection skill.

Survivorship bias is another problem. Delisted, acquired, bankrupt, and renamed companies still belong in the record. Corporate actions require careful treatment so a split or cash merger does not create a fictional gain or loss. Repeated promotions also need a rule. Counting the same rising stock several times can inflate the apparent hit rate without adding independent evidence.

Subscription costs change the investor's result. Suppose a hypothetical $10,000 account gains 8%, or $800, before paying a $300 annual research bill. The remaining gain is $500, equal to 5% of the starting account before trading costs and taxes. That is not the same as an 8% net return. A larger account dilutes the percentage impact of a fixed fee, but it does not turn weak recommendations into strong ones.

How to judge a newsletter rather than its best advertisement

Ask whether the publisher preserves losing recommendations and gives clear, dated exit instructions. A buy-only teaser archive measures the promotion's subsequent path, not necessarily the results of a subscriber following the full service. Both can be useful, but they answer different questions. Do not combine an advertised winning exit with an unadvertised losing position still marked at a convenient date.

Review the distribution of outcomes, maximum drawdowns where available, and the proportion of picks beating the benchmark. A high win rate can coexist with poor returns if losses are much larger than gains. An arithmetic average of individual picks is also not a portfolio return. Real portfolio results depend on allocation sizes, overlapping holding periods, cash balances, transaction costs, and rebalancing rules.

A useful newsletter may teach research habits or identify companies worth studying even if its picks do not outperform. That educational value should be judged separately from performance claims. For an investment comparison, require a complete, dated, cost-aware record against the same benchmark periods. The available sample does not justify assuming that buying every teaser will beat a low-cost index fund. This is a framework for evaluating claims, not a recommendation to buy a fund or subscribe to a service.