Direct Answer
Percent of Stocks Above 200-Day Moving Average is a breadth measure used to measure how widely a market move is being participated in across constituents. The production page must define the exact calculation convention before interpreting higher or lower readings, because platform and provider implementations can differ.
Percent of Stocks Above 200-Day Moving Average: Formula, Meaning, Signals, Examples and How to Use It
How Is Percent of Stocks Above 200-Day Moving Average Calculated?
The percentage of stocks in an index or universe whose latest close is above their own 200-day moving average. It is the standard long-term trend breadth measure.
Formula: % above 200-day = stocks with close above their 200-day moving average / total stocks x 100
Inputs:
- Daily closes for every stock in the universe
- 200-day moving average for each stock
- Constituent list
Worked example. If 290 of 500 stocks close above their 200-day averages, the reading is 58.0%. The inputs are illustrative numbers, not market data.
Reading it. Readings above 50 percent mean most stocks are in long-term uptrends and readings below 50 percent mean most are not. The line moves slowly, so a sustained rise or fall is read as a change in the market's underlying health.
Limits. The 200-day average lags, so the reading turns well after price does. Large rallies from deep lows can leave it low for months because many stocks are still below their long averages.
Indicator overview
| Attribute | Value |
|---|---|
| Category | Breadth |
| Asset classes | Indexes, Equity markets, Sectors, Industries |
| Output type | Ratio/index/scalar |
| Parameters | Varies by implementation; document exact settings on use |
What is Percent of Stocks Above 200-Day Moving Average?
Percent of Stocks Above 200-Day Moving Average is a breadth measure used to measure how widely a market move is being participated in across constituents. The production page must define the exact calculation convention before interpreting higher or lower readings, because platform and provider implementations can differ.
For Swoopr, the canonical profile separates definition, calculation, interpretation and decision use. That keeps readers from collapsing a descriptive metric into a trading strategy. An indicator can describe trend, momentum, volatility, participation, positioning or risk without providing a complete entry, exit, sizing or portfolio decision.
What does it measure?
Percent of Stocks Above 200-Day Moving Average measures specific market properties in the Breadth domain. The practical value is repeatability: the same inputs and formula can be applied across a defined dataset, allowing users to compare readings through time or across instruments when the calculation convention is held constant.
How to read Percent of Stocks Above 200-Day Moving Average
Interpretation depends on the market property being measured. A descriptive reading is not automatically predictive. The same numerical state can lead to different outcomes in a strong trend, quiet range, event-driven gap or illiquid market. Always combine with context from price structure, volume, and broader market regime before drawing conclusions.
Strengths
- A 200-day average smooths out most intermediate swings, so a stock's side of the line changes rarely and the percentage moves steadily.
- It is the most widely quoted long-term threshold, so published readings from different sources are easy to cross-check.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- A stock deep below its average and one just below it count the same, so the percentage cannot separate a mild pullback from a lasting collapse.
- Dividends and splits can shift a stock's average if prices are not adjusted, so the count depends on whether the data are split-adjusted.
- Correlated indicators can create false confidence by repeating the same underlying information.
Editorial and risk note
This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance. Where multiple valid definitions exist, Swoopr states the alternatives and the reason for selecting its primary convention.
Frequently Asked Questions
Is Percent of Stocks Above 200-Day Moving Average a buy or sell signal?
No. Readings above 50 percent mean most stocks are in long-term uptrends and readings below 50 percent mean most are not. The 200-day average lags, so the reading turns well after price does. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions.
What is the best setting for Percent of Stocks Above 200-Day Moving Average?
Percent of Stocks Above 200-Day Moving Average takes these inputs: daily closes for every stock in the universe; 200-day moving average for each stock; constituent list. There is no universal best setting for the tunable ones, so test them across instruments, regimes and out-of-sample periods and favor stable parameter regions over one historical winner.
Can Percent of Stocks Above 200-Day Moving Average be used by itself?
The 200-day average lags, so the reading turns well after price does. Large rallies from deep lows can leave it low for months because many stocks are still below their long averages. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Percent of Stocks Above 200-Day Moving Average work on every timeframe?
The calculation (% above 200-day = stocks with close above their 200-day moving average / total stocks x 100) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it.
Why does Percent of Stocks Above 200-Day Moving Average give false signals?
A stock deep below its average and one just below it count the same, so the percentage cannot separate a mild pullback from a lasting collapse. Dividends and splits can shift a stock's average if prices are not adjusted, so the count depends on whether the data are split-adjusted. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Percent of Stocks Above 200-Day Moving Average be backtested?
Rebuild Percent of Stocks Above 200-Day Moving Average from daily closes for every stock in the universe using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline.