Direct Answer
MESA Stochastic is a John Ehlers refinement that applies the stochastic formula to roofing-filtered data instead of raw price, then smooths it with a Super Smoother. This removes the trend component that distorts an ordinary stochastic. Values run between 0 and 1, where readings near 1 mean the filtered price is at the top of its recent range and readings near 0 mean the bottom.
Mesa Stochastic: Formula, Meaning, Signals, Examples and How to Use It
How Is Mesa Stochastic Calculated?
MESA Stochastic is a John Ehlers refinement that applies the stochastic formula to roofing-filtered data instead of raw price, then smooths it with a Super Smoother. This removes the trend component that distorts an ordinary stochastic.
Formula: Stoch = (Filt - lowest Filt over N bars) / (highest Filt over N bars - lowest Filt over N bars); MESAStoch = SuperSmoother(Stoch)
Inputs:
- Close prices
- Roofing filter cutoffs
- Stochastic lookback N (often 20)
Worked example. With a filtered value of 1.0 inside a recent range from -1.5 to 2.5, the raw stochastic value is 0.625 before smoothing. The inputs are illustrative numbers, not market data.
Reading it. Values run between 0 and 1, where readings near 1 mean the filtered price is at the top of its recent range and readings near 0 mean the bottom. Because the trend was filtered out, the line swings through the range more evenly than a conventional stochastic.
Limits. Band-limiting hides longer moves, so a persistent trend shows as little signal. The result depends on the roofing cutoffs and the lookback.
What is Mesa Stochastic?
MESA Stochastic is a John Ehlers refinement that applies the stochastic formula to roofing-filtered data instead of raw price, then smooths it with a Super Smoother. This removes the trend component that distorts an ordinary stochastic.
How to use Mesa Stochastic
Values run between 0 and 1, where readings near 1 mean the filtered price is at the top of its recent range and readings near 0 mean the bottom. Because the trend was filtered out, the line swings through the range more evenly than a conventional stochastic. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.
Strengths
- Applying the stochastic formula to roofing-filtered data removes the trend drift that normally pins an ordinary stochastic at one extreme.
- The final Super Smoother step removes the step-like jumps of a raw stochastic, giving a smooth line that turns without jagged moves.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- Rescaling over the highest and lowest N filtered values means one large swing sets the range and flattens the next several bars.
- The 0 to 1 scaling is relative to the recent range, so the same output value can reflect very small or very large price movements.
- 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.
Frequently Asked Questions
Is Mesa Stochastic a buy or sell signal?
No. Values run between 0 and 1, where readings near 1 mean the filtered price is at the top of its recent range and readings near 0 mean the bottom. Band-limiting hides longer moves, so a persistent trend shows as little signal. 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 Mesa Stochastic?
Mesa Stochastic takes these inputs: close prices; roofing filter cutoffs; stochastic lookback N (often 20). 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 Mesa Stochastic be used by itself?
Band-limiting hides longer moves, so a persistent trend shows as little signal. The result depends on the roofing cutoffs and the lookback. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Mesa Stochastic work on every timeframe?
The calculation (Stoch = (Filt - lowest Filt over N bars) / (highest Filt over N bars - lowest Filt over N bars); MESAStoch = SuperSmoother(Stoch)) 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 Mesa Stochastic give false signals?
Rescaling over the highest and lowest N filtered values means one large swing sets the range and flattens the next several bars. The 0 to 1 scaling is relative to the recent range, so the same output value can reflect very small or very large price movements. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Mesa Stochastic be backtested?
Rebuild Mesa Stochastic from close prices 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.