Why PredixLab Covers Only the S&P 500 and Nasdaq-100

PredixLab covers only the constituents of the S&P 500 and the Nasdaq-100, and the limit is deliberate. For an individual investor, the scarce resource is not data but attention, and index inclusion is a pre-filter that someone else has already applied under published rules. Covering less, and reviewing all of it every trading day, leaves a short list worth a closer look.

Most research tools for retail investors take the opposite approach and compete on breadth: more securities, more exchanges, more filter fields. That breadth is valuable to professionals with a full working day and a defined process. For a non-professional investor with an hour in the evening, it is mostly a search problem. The useful information is there, but it sits under a great deal of noise. The reasons PredixLab draws its boundary at two indices follow from that problem.

Why not just a watchlist? The attention budget

An individual investor can realistically follow perhaps 20 to 30 stocks closely. Following a stock properly means knowing its recent range, how it usually trades and when something has changed. That kind of attention does not scale, and beyond a few dozen names, monitoring turns into skimming.

The second constraint is that good entry points are rare. For most of the year, any given stock sits somewhere unremarkable: not extended, not oversold, not breaking out. A setup that meets a disciplined investor's criteria appears in a single name only a handful of times a year. Across 25 stocks, that adds up to a modest number of genuine opportunities, and some arrive when no one is looking.

The two constraints pull in opposite directions. Seeing more opportunities requires watching more stocks, but watching more stocks by hand runs straight into the attention limit. The way out is to divide the work. A systematic process reviews a broad universe every day, and the investor evaluates what it surfaces.

Together, the S&P 500 and the Nasdaq-100 span roughly 500 to 600 stocks, depending on how many names appear in both. That is about twenty times the 20 to 30 stocks one person can follow closely, yet still small enough to review in full every trading day. PredixLab runs that review as a scheduled nightly process on daily data, not intraday quotes. After the US close, it updates prices and calculates trend, momentum, volatility and volume indicators. It then publishes two outputs: AlphaRank, a daily list of the 15 stocks its model ranks highest, and Pivot, which flags possible turning points and on many days flags nothing at all. A day with no Pivot events is a normal day, not a malfunction. A tool meant to save attention should be willing to say that nothing in particular deserves it.

Why these two indices? Inclusion is a published pre-filter

Before PredixLab runs a single calculation, index providers have already screened these companies, using rules anyone can read.

Under the S&P U.S. Indices Methodology, a company added to the S&P 500 must currently have a total market capitalization of at least US$22.7 billion (as of November 2026; S&P adjusts this threshold over time). It must also pass liquidity and public-float tests and report positive as-reported earnings over its most recent quarter and over the last four quarters combined. The Nasdaq-100 covers 100 of the largest non-financial companies listed on Nasdaq, and each security must trade at least US$5 million a day on average.

Size, liquidity and, for the S&P 500, a record of earnings: these are the properties that make daily price and volume data meaningful. A large, actively traded stock rarely moves on a single order, and its chart reflects the views of many participants. Building on index membership means starting from companies that already clear that bar.

Why not the whole market? More names, more noise

If coverage matters, screening every US listing looks like the obvious next step. In practice, the names a whole-market screen adds are mostly smaller, thinly traded companies. Their prices can be moved by single large orders, their data are more prone to gaps, and their volatile numbers tend to crowd the top of any screen sorted by movement. A daily review across that universe would spend much of its output, and much of the reader's attention, on moves that carry little information.

This is the less-is-more argument in its plainest form. Beyond a certain point, adding names adds more noise than opportunity, and the filtering job simply moves back to the user.

How other tools choose breadth

The leading platforms make the opposite choice, and they make it well. By their own descriptions, they offer far wider coverage and many more screening options:

Coverage and screening figures are as stated on each company's own pages, checked in November 2026, and may change. Plans and features differ by tier. The last column is PredixLab's own summary, not the company's wording.

For many users that breadth is exactly the point. A trader working across asset classes needs TradingView's range. A fundamental investor building a valuation model benefits from Koyfin's or Stock Rover's depth of metrics. Seeking Alpha's Quant Ratings and top-stock lists are themselves an attempt to compress a large universe into a shorter one. But breadth has a cost, and it falls on the user. A screener with hundreds of fields assumes the user already knows which few fields matter. PredixLab trades breadth for a smaller universe and does more of the filtering before the results reach the screen.

What does covering only two indices cost?

The choice has real costs, and they deserve equal weight.

• No small or mid-sized companies. Anything outside the two indices is out of scope, including companies that may later grow into them.
• Index membership is not a quality guarantee. S&P applies its criteria at addition, not as a test for continued membership, so a constituent can report losses and remain in the index. The Nasdaq-100 has no profitability test. Large companies can still fall sharply.
• Survivorship affects any history built on index lists. PredixLab's backtests carry documented limitations, including largely missing delisted companies, prices that mostly exclude dividends and some optimistic fill assumptions. The problem, and where PredixLab's own backtests fall short, is covered in Survivorship bias in backtesting.
• Not for intraday trading. Data update once per trading day after the US close.
• A list to review, not a list to buy. PredixLab does not assess valuation. A signal is an input to analysis, not an instruction to trade, and a model score is not a probability of profit.

Investors who need multi-asset charting, global coverage or deep fundamental metrics will find them in the broader platforms above, and many will reasonably use both kinds of tool. The method and its limitations are documented in How PredixLab works. The signal and backtest code is open source.

Covering less, reviewing more closely

The test of a research tool is not how much it contains but how much of the user's time it gives back. PredixLab's answer is to start from a universe that published index rules have already narrowed, review all of it every trading day, and hand over a short daily list to review. Less coverage, chosen carefully, leaves more attention for the decisions that matter.

The Free plan requires no credit card. It includes the market overview, price charts and the stock screener, with daily signals, options activity and signal performance on a 10-day delay. Premium provides the latest published data for $20 a month or $192 a year, using the same models, so upgrading changes how current the data are, not how accurate the signals are.

For information and independent analysis only, not investment advice. Data can be delayed or wrong, models can fail, and past performance doesn't predict future results.