Glossary

Trading & backtesting glossary

Plain-English definitions for every metric, check and indicator on Stratsemble — the same explanations that sit behind each on the site. Each one says what it means and its catch, because a definition that hides the downside is how people get fooled. It's a reference, not advice.

Reading a result

The headline numbers a backtest reports — and why the biggest one is rarely the one that matters.

Total return: How much the strategy grew your money over the whole period, after costs. It's the headline — but on its own it hides how much risk you took and whether just buying and holding would have done better.
vs Buy & hold: The strategy's return minus simply buying and holding the same asset. This is the honest scoreboard: a big return that still trails buy & hold means the strategy added work and risk for nothing.
Buy & hold: What the asset itself did over the same window if you'd just bought it and done nothing — the benchmark the strategy has to beat. If the strategy can't clear this line, all its trading added risk and cost for nothing.
Monthly excess over buy & hold: Each cell shows how many percentage points the strategy beat (green) or lagged (red) simply buying and holding that month — the excess, not the strategy's own return. A neutral 0 means it matched buy & hold; a grey · is a month with no backtest data; edge months are partial (hatched). Tap or hover any cell for the strategy return, the buy-&-hold return and the exact excess.
CAGR: The smoothed yearly growth rate — the steady annual return that would produce the same end result. Easier to compare across different time spans than a raw total.
Win rate: The share of trades that made money. High isn't automatically good: a strategy can win often and still lose overall if its few losers are large.; Read: does win rate matter? →
Profit factor: Gross profit divided by gross loss. Above 1 means winners outweigh losers; below 1 loses money overall. Around 1.0 is a coin flip after costs.
Time in market: How much of the period the strategy actually held a position. A decent return with low exposure can mean less risk — or just luck in a few short windows.
Trades: How many round-trip trades the strategy made. Too few (under a handful) and any result is mostly luck — there isn't enough evidence to trust it.
Best trade: The single most profitable trade. If one trade carries most of the return, the strategy is fragile — remove that one lucky trade and little is left.
Worst trade: The single biggest losing trade — a reminder of how bad one position got, which averages and totals quietly smooth over.
Costs & slippage: Every backtest here charges a flat 0.05% per side on every entry and exit (costs & slippage) — a stand-in for commission plus the small gap between the price you'd want and the price you'd actually get. Real slippage widens on fast or thin moves, so there it can cost more than this. Leaving costs out is the most common way a backtest flatters itself; they're always on here.

Risk & drawdown

How much pain a result hid behind its average — the losses, the wait to recover, the ride.

Max drawdown: The worst peak-to-trough drop along the way — the deepest hole you'd have been sitting in. It's the pain you'd have had to stomach without giving up.; Read: what's a good max drawdown? →
Worst drawdowns: The deepest peak-to-trough falls, with dates and timing. 'To trough' is how long the fall took; 'Underwater' is how long until you got back to the old high; 'Recovered' says whether you ever did. It's the pain a single max-drawdown number hides — long underwater stretches are where people give up.
Sharpe ratio: Return earned per unit of wobble (volatility). Higher means a smoother ride; roughly, above 1 is good. Its blind spot: it treats rare, huge losses too kindly.; Read: what's a good Sharpe ratio? →
Sortino ratio: Like Sharpe, but it only counts downside wobble — it doesn't punish a strategy for big up-moves. A fairer read of pain-adjusted return.
Calmar ratio: Annual return divided by the worst drawdown. It asks a blunt question — how much yearly gain did you get for the deepest hole you had to sit through? Higher is a better reward-for-pain trade.
Ulcer index: A single number for how much time you spent underwater and how deep — it punishes long, deep drawdowns more than brief dips. Lower is a calmer ride; two strategies with the same return can have very different ulcers.
Time underwater: The share of the period the strategy spent below a previous high — i.e. how often you'd have been staring at a losing position waiting to get back to even. Long stretches are where people give up.
Recovery factor: Total return divided by the worst drawdown — roughly, how many times over the strategy earned back its deepest pain. Above ~2 is healthy; near or below 1 means the gains barely covered the drawdowns.
Tail ratio: The size of the best days versus the worst days (95th vs 5th percentile of daily moves). Above 1 means the big up-days outweigh the big down-days; below 1 means the crashes are bigger than the pops.
Volatility: How much the portfolio's value bounced around, per year. More volatility means a rougher ride for the same destination.

Is the edge real? (reality checks)

The checks and views that interrogate a good backtest — the statistical ones can only rule an edge out, never prove it will pay forward.

Robustness: Whether an edge survives small changes to its settings. A result that only works at one exact number is probably curve-fit to the past; one that keeps working across a range of nearby settings is far more likely to be real.; Run the robustness check →
Robustness heatmap: We re-run the strategy across a grid of nearby settings. The more of those settings that still beat buy & hold, the more robust the edge; if only one isolated setting worked, it was probably fit to the past. The colour follows whichever metric you pick, but the verdict is always judged on beating buy & hold.; Run the robustness check →
Resampling your trades: We redraw your trades with replacement a thousand times to see how much the result leaned on a handful of specific (lucky) trades rather than a repeatable edge — the compounded return is the same whatever order they came in, so this is about WHICH trades you happened to get, not their sequence. A result that survives redrawing is sturdier than one that falls apart. (Different from the noise floor, which tests whether random TIMING would have done as well.); Run the robustness check →
Noise floor (vs random): We take your trades and slide their entries to random dates a thousand times — same asset, same number of trades, same holding lengths, same sides — and see how often random timing did as well as your rules. If you can't clearly beat random entries with the same activity, the 'edge' is probably luck. On a strongly trending asset even random entries do well, so beating buy & hold still matters more. It does NOT correct for cherry-picking (that's the deflated Sharpe).; See how the luck test runs →
Deflated Sharpe (cherry-picking check): When you scan one strategy across many assets and keep the best, some of that top result is luck — try enough assets and one looks good by chance. This takes the winner's risk-adjusted edge over buy & hold and discounts it for how many assets you tried, leaving the share that's more than selection luck. A high number means the best result probably isn't just the luckiest of the bunch — it does NOT mean the strategy will make money forward, only that this scan didn't manufacture the result by trying a lot. It counts only the assets in THIS scan: every other strategy, window and scan you've tried makes the real correction harsher, so read it as a best case, not a point estimate. Measured on daily returns vs buy & hold, adjusted for the fact that nearby days move together; a strategy that mostly sits in cash and wins by dodging a few crashes shows a small, choppy daily edge, so a low number there means 'not proven here', not 'disproven'. The winner shown is the one that beat buy & hold by the most; scoring it on its risk-adjusted edge is a deliberately conservative way to run the check. A different kind of luck from the noise floor (random timing on one result) and Monte-Carlo (which trades carried it) — these checks can only disprove a strategy, never prove one. Same scan, same number (no randomness).; See the multiple-testing haircut →
Tuning-luck check: When you sweep a setting and keep the value that looks best, some of that is just luck — a value that happened to fit the past. This splits the history into slices every possible way, and for each split picks the setting that looked best on the 'training' slices, then checks where it lands on the slices it never saw. The number is how often that best-looking setting slips to the middle of the pack or worse out-of-sample: high means the winning setting was mostly fit to the past; low means the tuning didn't obviously overfit — which is NOT the same as 'the strategy works', and says nothing about profit going forward. It covers only the SETTINGS axis (it needs a real range of settings, not near-identical ones); if you also scanned many assets, that's a separate kind of luck the deflated Sharpe covers. The many train/test splits reuse the same slices of history in overlapping combinations, so their count reflects how thoroughly it's checked, not an independent sample size. Don't re-run it hunting for a lower number.; See the multiple-testing haircut →
Walk-forward / out-of-sample: Tune the strategy on one slice of history, then test those settings — untouched — on a later slice it never saw; roll forward and stitch the unseen slices together. The gap between the hindsight-tuned result and the walk-forward result is the overfitting you can't actually use. The closest a backtest gets to honest — but it's still ONE out-of-sample path over relatively few trades, so pair it with the robustness heatmap and Monte-Carlo, and don't re-run it hunting for a good-looking result.; Run a walk-forward test →
Folds that count: History is split into folds, each with an out-of-sample slice. A fold only counts toward the verdict if its out-of-sample slice had enough real trades (at least 3) to mean something; and the verdict needs at least 3 of the 4 folds to count — otherwise the sample is too thin to judge honestly.; Run a walk-forward test →
Is it just leveraged beta?: Measured only on the bars you were invested: 'beta' is how much your position moved per unit of the asset's move, and 'R²' is how tightly it tracked. Beta near 1 with a high R² means you basically held the asset — so any excess is the TIMING of plain exposure, not a separate return source. Above ~1.15 is leverage or oversized bets: bigger swings both ways, more risk, not skill. This check can only rule an edge OUT (show the result is just exposure) — it can NEVER prove one; whether the timing itself is real is what the noise-floor and walk-forward checks are for. The benchmark includes dividends while your P&L is price-only, so beta reads a touch low on high-yield names.
Was it just market beta?: The same idea as the leveraged-beta check, but against the BROAD MARKET (the S&P 500 for stocks, Bitcoin for crypto) instead of the asset itself. Measured only on the bars you were invested: 'beta' is how much your returns moved per unit of the market's move, 'R²' is how tightly they tracked it. High beta with a high R² means the result was largely broad-market exposure, not a separate edge — you'd likely have captured much of it from the index itself. It can ONLY rule a market-beta explanation out; a low R² is not evidence of skill, and whether the timing is real is what the noise-floor and walk-forward checks are for. The market reference is a fixed, transparent one (never a best-fit benchmark); for a stock index it includes dividends while your P&L is price-only, so beta can read a touch low on high-yield names.
Market regimes: How the strategy did when the market was rising (bull) or falling (bear) — set from the benchmark versus its own trailing average, using only past data (no look-ahead). The high-volatility row is a separate, overlapping slice: the most volatile roughly-quarter of days measured across the whole period. A strategy that only makes money in bull markets is fragile; one that holds up across conditions is sturdier — the honest test of 'did this have an edge, or just ride the market up?'
Prop-firm rules check: Would this strategy have survived a funded-account challenge (FTMO/Topstep/Apex-style)? It overlays a firm's published risk limits — max daily loss, max or trailing drawdown, profit target, minimum trading days — on your strategy's own ABSOLUTE account equity (not the vs-buy&hold number shown elsewhere; a firm measures the account). Because firms enforce those limits INTRADAY and daily bars only have closes, we test every breach against the bar's worst intraday point: a computed BREACH is the read worth knowing (worst case, the account reached that level — we assume the position was held through the bar's range), while a clean run is only 'didn't breach on a daily basis' — never a promise you'll pass, since the intraday path and the firm's exact costs/instrument differ. It slides the challenge across every non-overlapping window and reports the distribution (not one cherry-picked start), and refuses to state a rate when there are too few windows. The honest next step is never 'buy the challenge' — it's to forward-test it on paper, then on your own broker.; Run the prop-firm rules check →
Data quality: An automatic check of the underlying price data for gaps, stale feeds, or implausible jumps — problems in the data, not the strategy, that could quietly distort a result.; How data quality is handled →
Bar-by-bar replay: Replays the strategy's history one bar at a time with the future hidden, so you can watch each mechanical trade commit at a bar's close before the next bar exists — a visceral demonstration that the engine acts only on past data. The guarantee lives in the closed-bar-safe engine (it fills at the next open, never on the bar it just used to decide); this replay just unveils those already-computed, causal results in time order. The chart's vertical scale only ever uses the bars revealed so far, so nothing about the future leaks in early. It describes what the rules did; it is not a prediction and not a game — there's nothing to 'call'.
Trades on the price: Your strategy's actual entries (●) and exits (○) drawn on the asset's own price, so you can see WHERE it bought and sold — not just an equity curve. It shows exactly what the engine did: entries and rule exits fill at the next open, a stop at its level (or at that day's open if the day opened past it), costs and slippage on, no look-ahead. Green/red mark whether each trade made or lost money — that's data about what happened, not a verdict. It describes the past; it makes no claim about the future.

Technical indicators

What each indicator MEASURES — and its blind spot. None of them predicts the future; each is a gauge with a catch.

Simple moving average: The plain average of the last N closing prices, re-figured each bar — it smooths jumpy price into a single trend line. The catch is lag: it reacts late to turns, and it weights a price from N bars ago exactly the same as today's.
Exponential moving average: A moving average that leans on recent prices more heavily, so it turns faster than a simple average of the same length. Faster means it also reacts to more noise — so it whips back and forth more in choppy, directionless markets.
Weighted moving average (WMA): A moving average that weights the most recent bars more heavily than older ones (a straight ramp of weights), so it turns sooner than a simple average of the same length. That quicker turn is bought with more sensitivity to noise — it whips back and forth more in choppy, sideways markets.
Hull moving average (HMA): The Hull moving average combines several weighted averages to cut the lag a plain average carries, so it hugs turns more closely. The speed has a cost, not a free one: it tends to overshoot past a genuine move and ring back, and it whipsaws more in directionless markets.
Double EMA (DEMA): The double exponential moving average subtracts a second smoothing from the first to react to turns faster than a same-length EMA. Faster comes at a price: it tends to overshoot a real move and whip around more in flat, sideways markets — the reduced lag is not free.
Triple EMA (TEMA): The triple exponential moving average stacks three smoothings to react to turns even faster than DEMA. The trade-off is steeper: more overshoot and ringing after a move, and more whipsaw when the market goes nowhere — quicker turns are paid for in noise, not free.
Arnaud Legoux MA (ALMA): A moving average that weights its recent window with a Gaussian curve whose peak you can slide toward the newest bar (quicker turns, less smoothing) or the oldest (smoother, slower). Sliding it toward the present trims lag but costs more whipsaw in sideways markets. It only ever reads past bars, never the future.
Volume-weighted MA (VWMA): A moving average that weights each bar by how much traded, so busy bars pull it more than quiet ones. It leans on the volume feed — strip volume out, or on a thin or volume-less asset, and there is nothing to weight by, so it stops rather than fake a line. Like any average it still lags turns and whipsaws in ranges.
Kaufman Adaptive MA (KAMA): A moving average that adjusts its own smoothing bar by bar. When recent price has moved in a clean, direct line it tightens up and tracks price closely; when price is just chopping sideways it loosens so the noise moves it less. Adaptive is not foresight — it only reads how directional the recent bars were (an efficiency ratio measured over past bars), never what comes next, so it still lags real turns and can lurch when a long quiet stretch finally breaks into a trend. Steadier tracking in trends is paid for with that regime-change lurch, not avoided. It needs a good stretch of history — on the order of a hundred-plus bars — before it settles into a stable value that no longer shifts much with how much history you happened to load; below that it shows nothing rather than a fabricated line.
MACD: The gap between a fast and a slow moving average (the MACD line), plus a slower average of that gap (the signal line). It gauges momentum — the line pulling above its signal is read as momentum turning up — but because it's built from lagging averages it still turns after price does, and drifts around zero in sideways markets.; Read the honest MACD study →
Bollinger bands: A moving average with an upper and lower band set a number of standard deviations away, so the band widens when price is volatile and pinches in when it's calm. A close outside a band means price is statistically stretched for its recent range — but stretched is not the same as about-to-reverse: in a strong trend price can 'walk the band' for a long time.; Read the honest Bollinger study →
Keltner channel: A band around a moving average set a multiple of average true range wide — a volatility-based cousin of Bollinger Bands that measures range with the true bar range instead of the spread of closes, so it reacts differently to gaps. Same idea, same catch: 'outside the band' means stretched, not turning.
Donchian channel: The highest high and lowest low of the last N bars, drawn as a channel; a close above the top is a new N-bar high — the classic breakout trigger. Here the channel deliberately excludes the current bar, so a 'new high' can't peek at the very bar it's testing (no look-ahead). The catch: breakouts fail often in range-bound markets, buying the top just before a snap-back.
RSI: The Relative Strength Index measures how one-sided recent moves have been — the size of gains versus losses over the last N bars, on a 0–100 scale. Readings near the top (conventionally 'overbought') or bottom ('oversold') mean price has moved a lot one way; it's a gauge of stretch, not a prediction of a turn, and in a strong trend it can sit pinned at an extreme while price keeps running.; Read the honest RSI study →
Stochastic oscillator: Shows where the latest close sits inside the recent high–low range — 0 at the bottom of the range, 100 at the top — with a smoothed second line (%D). Near the top is called 'overbought', near the bottom 'oversold', but like any range gauge it stays pinned near an extreme through a strong trend, so a stretched reading is not a reversal signal.
Stochastic RSI: The Stochastic formula applied to RSI instead of to price: it shows where RSI sits within its own recent range, on a 0–1 scale. Because it stretches an already-smoothed indicator, it's faster and noisier than plain RSI — it hits the extremes far more often, so it's more often wrong there. It gauges how stretched momentum is, not a prediction of a turn.
Commodity channel index (CCI): The Commodity Channel Index measures how far the typical price (high, low and close averaged) has stretched from its recent average, scaled by its own average deviation. On very quiet ranges that deviation is tiny, so CCI can spike past ±100 on almost no real movement — it reads stretch, and calm markets exaggerate it.
Aroon: Aroon measures how RECENTLY the highest high and lowest low happened inside a lookback window: Aroon Up sits near 100 just after a fresh high, Aroon Down near 100 just after a fresh low, and the oscillator is the gap between them. It gauges how young a trend is, but it only reacts once a new extreme actually prints — so it confirms moves late and chops around zero in a sideways range.
Williams %R: Williams %R marks where the close sits inside the last N bars' high–low range, on a −100 (at the low) to 0 (at the high) scale — it is essentially the Stochastic %K flipped negative. Like any stretch gauge it can pin to an extreme and stay there through a strong trend, so 'oversold' near −100 can keep getting more oversold.
Awesome oscillator: The gap between a fast (5-bar) and a slow (34-bar) average of each bar's midpoint — positive when the fast average leads the slow one. It's essentially a moving-average crossover in disguise, so it carries the same catch: it lags turns and whipsaws in sideways markets.
Rate of change (ROC): The percent change in price versus N bars ago — the simplest momentum gauge: positive means today's price is above the price N bars back. It's raw and unsmoothed, so it reacts fast but is jumpy, and it says nothing about whether that move is likely to continue or reverse.
Time-series momentum: Measures the asset against ITSELF over time — its own trailing return over roughly a year, skipping the most recent month (the '12-1' rule, which drops the short-term bounce-back), scored against the average of its own history. A positive reading means recent momentum is above that historical average — it can read positive even while the raw return is negative — and it does not rank or compare different assets. A slow read with a long (~2-year) warm-up, prone to whipsaws and to being caught out by sudden crashes.
SuperTrend: A trailing line placed a multiple of average true range above or below price that flips from bearish to bullish as price crosses it. It adapts its distance to volatility and trails trends closely — but it flips late at turns and whipsaws in sideways markets, giving back part of a move at each flip.
Parabolic SAR: Wilder's 'stop and reverse' — a trailing dot that accelerates toward price as a trend runs and flips the trend when price crosses it. Each dot is projected from the prior bar, so it never peeks at the bar it's testing. It trails winners tightly, but it reverses often, so it whipsaws badly in sideways markets and gives back part of every move at each flip.
ADX / DMI: The Directional Movement system: +DI and −DI show which side — up or down — is winning, and ADX (0–100) shows how strong the trend is regardless of direction. A high ADX means a real trend is present, but ADX rises only AFTER a trend is underway and says nothing about which way — so it's a filter, not a signal.
Ichimoku cloud: The Ichimoku 'cloud' is a band built from midpoints of past highs and lows, shifted forward so it derives only from past data: price above the cloud is a bullish regime, below is bearish, inside is a neutral zone. It's a trend/regime filter that lags turns by design and whips around the cloud edge in choppy markets. (We deliberately leave out the one Ichimoku line that looks backward in time — using it would be look-ahead.)
Tenkan & Kijun lines: The two fast midlines inside Ichimoku: the Tenkan (conversion) is the midpoint — highest high and lowest low, averaged — of about the last 9 bars, and the Kijun (base) is the slower ~26-bar version. Here they mostly shape the cloud rather than fire signals of their own: this strategy trades only whether price is above or below the cloud, so these two lines are the raw material behind it, not triggers.
On-balance volume: A running total that adds a bar's volume on an up-close and subtracts it on a down-close, so the line climbs when volume flows in on up-days. Its absolute level is arbitrary — it depends on where your data happens to start — so only the crossing of its own moving averages (a difference, in which the arbitrary offset cancels) carries information, never the raw number, and on a thin or volume-less feed it says very little.
Money flow index: A volume-weighted cousin of RSI — it measures stretched buying versus selling pressure on a 0–100 scale, weighting each bar by its volume. Strip the volume out on thin or volume-less data and it behaves much like RSI (though it scores each bar by its money-flow level, not the size of the move), and like any stretch gauge it can stay pinned at an extreme through a strong trend.
Chaikin money flow: Measures where each bar's close finished inside its high–low range (a close near the high suggests buying pressure), weights that by volume, and averages it to a reading between −1 and +1 — above zero suggests accumulation, below zero distribution. It lags turns and whipsaws sideways. A bar with no range contributes a neutral zero rather than a fabricated ±1, but it doesn't blank the reading; only a volume-less feed (or the warm-up) leaves no reading at all.
Force Index: Multiplies each bar's price change by its volume and smooths the result, gauging the conviction behind a move — above zero, buyers pushed price up on real volume; below zero, sellers did. Its size is in price-times-volume units, so a raw level means nothing across different assets: read its zero-cross, not an absolute number. It needs a real volume feed and stops on a volume-less one.
Chaikin oscillator: Tracks the momentum of accumulation — it takes a running money-flow line (volume weighted by where each bar closed inside its range) and measures a fast versus slow average of it, so above zero means buying pressure is building and below means it is fading. It reads the CHANGE in that flow, never its raw running level (which has no fixed zero and would depend on where your data starts). It needs a real volume feed.
Average true range: The typical size of a bar's move, gaps from the prior close included — a pure volatility gauge, not a direction one. It's the yardstick behind volatility-adaptive tools (SuperTrend, Keltner, ATR stops): bigger ATR means wider swings, so stops and bands set from it sit further from price on jumpy assets. The catch: it's in the asset's own price units, so an ATR of $5 is huge on a $20 stock and tiny on a $2,000 one — you can't compare raw ATR across assets, and a single gap or spike inflates it for many bars.
Choppiness index: Rates how much the market has been ranging versus trending over the last N bars, on a 0–100 scale: it compares how far price actually travelled (the summed bar ranges) with the net high-to-low distance it covered. High readings (roughly above 60) mean a lot of back-and-forth for little net progress — a choppy, sideways market; low readings (below about 40) mean a straighter, trending move. It gauges trendiness, not direction, and it describes the recent past, not what comes next.
Vortex indicator: Plots two lines — VI+ measures how much upward bar-to-bar movement built up over the lookback, VI− the downward, each divided by the true range. When VI+ leads VI− the recent movement has been mostly upward, and the other way round when VI− leads. It reads which direction's movement dominated a window, not a call on a turn; like any crossover gauge it lags turns and whipsaws when the two lines weave together in a sideways range.
Typical price: The high, low and close of a bar averaged into one number — a slightly smoother stand-in for the close that several indicators (like CCI and money-flow) are built on, because it reflects where the bar actually traded rather than only where it settled. It is a price, not a verdict: on its own it says nothing about direction or edge; it is just an alternative price source to build a rule on.
Median price: The bar's midpoint — its high and low averaged. A simple, steadier stand-in for price that ignores where the bar closed, so it is smoother than the close but discards what the close tells you about who won the bar. Like any price it carries no direction or edge on its own; it is just an alternative price source for a rule.
Heikin-Ashi candles: Each candle redrawn from an average of its own open/high/low/close and the prior candle's averaged values, so the chart looks smoother and trends look calmer. The smoothing is cosmetic — it adds lag, not information — and it hides the real intraday drawdown: a calm-looking Heikin-Ashi chart is not the account you'd have lived through. Every backtest here still fills and scores on the REAL price, never the smoothed candle.
Fair value gap: A three-candle price imbalance — the gap left between the first candle's high and the third candle's low when the middle candle jumps clear of both. It marks a band of prices the move skipped over, which some traders watch as a level price may trade back into later. It is drawn only from closed bars and confirmed at the third candle's close, never the candle still forming, so it can't peek at the bar it's testing. The catch: it describes where price has already been, not where it is going — an untouched gap need not ever be revisited, and a gap price does return to can break straight through it as readily as it turns there.; Read the honest FVG study →
Volume: How many shares or contracts changed hands in a bar — the fuel behind the volume indicators (OBV, MFI, CMF). It can be informative on liquid names, but noisy and patchy on thin ones, and free daily feeds sometimes report it split-adjusted or incomplete — so a volume signal is only as trustworthy as the feed under it.
Standard deviation (σ): A measure of how spread out recent prices are around their average — the width behind Bollinger Bands. A bigger σ means a wider, more volatile range; but it treats an up-move and a down-move the same, and leans on a tidy bell-curve spread that real markets, with their fat tails and crashes, don't quite follow.

Risk controls

The exits and sizing rules you can add to a strategy — each one a trade-off, not a free lunch.

Stop-loss: An automatic exit if the price falls a set % below your entry (for a short, rises that far above it), to limit how much one trade can lose. It is live from the day you buy. If a day opens past your stop, the exit is taken at that day's open, not at the stop — a stop can't protect you from a gap, so a loss can be bigger than the % you set. The catch: normal wobble can stop you out just before the price recovers, so a tight stop can quietly cut your returns.
Take-profit: An automatic exit once a trade is up a set %, to lock in a gain. It is booked at your target price even when the day opens past it, and if the same day also reaches your stop, the stop is counted — both choices lean cautious, so a real order could have done a little better. The catch: it also caps your winners, so it can close a big trend early and leave money on the table.
Trailing stop: A stop that follows the price up and only ever moves in your favour: it sits a set % below the best daily close since you bought (or your entry price, if that is higher), and exits if the price falls to it (mirrored for a short). It starts checking on the day after you buy, so your first day is covered only by a stop-loss or ATR stop if you set one — a fall on that first day exits at the next day's open and can cost more than the %. If a day opens past the stop, the exit is at that open, so a gap can cost more than the % too. It lets winners run while protecting gains — but a sharp dip that later recovers will still stop you out.
ATR stop: A stop placed a multiple of recent volatility below your entry (above it, for a short) — ATR (average true range) is the typical size of a bar's move, so the stop sits wider on jumpy assets and tighter on calm ones. It adapts to the asset instead of a fixed %, but a bigger multiple means a deeper loss before it triggers. Like any stop, if a day opens past it, the exit is at that open, so a gap can cost more than the stop's distance.
Time stop: Exit a trade after a set number of bars whatever the price, so dead trades don't tie up your capital indefinitely. Handy for rules that should work quickly — but it can also close a slow winner before it pays off.
Position sizing: How much of your capital goes into each trade. 'Fixed %' always commits the same share; 'Risk %' sizes each trade so that hitting its stop costs a set % of capital — smaller when the stop is far away, larger when it's near. A day that opens through the stop can cost more than that %. Risk sizing needs a stop to measure against.; Open the position-size calculator →

Portfolios

What happens when you blend several strategies or assets — diversification, contribution, and whether optimizing the mix even helps.

Correlation: How much the legs moved together, measured only on days they both traded. Low or negative means they offset each other (real diversification); high means they're basically one bet wearing several hats.
Contribution: How much each leg added to (or subtracted from) the portfolio's total return, after its weight. The contributions add up exactly to the portfolio's return.
Was it just the index?: How much of the blend's day-to-day movement was simply the broad market. Beta is how far it tended to move for each 1% the index moved; R² is the share of its daily wobble the index explains (0 to 1). A high R² means the ride was mostly the market; a low one is not evidence of skill — that's what the luck checks are for.
Stress the weights (does optimizing help?): A sharper question than the blend above: does CHOOSING each leg's weight from past performance actually beat just splitting equally, out-of-sample? We apply walk-forward to the weights — pick the allocation that looked best on each past slice, then test it untouched on the next slice it never saw, and stitch those unseen slices together. Because maximizing past return over a buy-and-hold blend always concentrates 100% on the single best past leg (there is no diversified 'optimum' to find), that is exactly what it does — and the winner changing fold to fold IS the instability. The honest headline is the comparison: optimized-from-the-past vs a plain equal split (1/N), both measured against holding the same assets equally. Usually 1/N does as well or better — the well-known result, and the reason we do NOT sell an optimizer. It resets the weights each period (unlike the hold-once blend above), the numbers mean 'beat an equal hold', not 'made money', and it is one out-of-sample path — never a recommendation to use any particular weights.
Blended buy & hold: What you'd have made by just buying the same assets in the same weights and holding them — no strategy, no trading. It's the yardstick the blend has to clear; beating it by only a little isn't worth the extra work and risk.
vs Blended buy & hold: The blended strategies' return minus that same weighted buy & hold. This is the honest scoreboard for a portfolio: if combining strategies can't clear a plain passive split of the same assets, the extra complexity earned nothing.

Track record & forward testing

The evidence that actually accrues over time — a forward test on data the rules were never fit to, checked against your own real fills.

Your record: Every strategy you test, forward-prove, and check against your own real fills accretes into a track record that's yours — and one that can't be rebuilt overnight. It's a real switching cost, honestly earned: the value is the accumulated evidence you can trust your own rules, not a score.
Held up out-of-sample: A forward test that has accumulated enough out-of-sample trades to tell its edge from luck AND is still beating buy & hold at that point. It's the strongest evidence a test here can give — genuinely earned on data the rules were never fit to — but still not a promise the edge lasts.
Real fills checked: Real broker fills you've logged against a forward test, so you can see how far the honest simulation drifted from your actual execution. Once you've verified our numbers with your own trade — your broker, your money, we never touch a cent — no unchecked tool can claim the same.
Log reconciliation: A side-by-side of the trades you logged against the trades the sim's rules took over the same window. It only reconciles — it does NOT score your discipline, because it genuinely can't: when a sim signal has no matching fill in your log, that's either a trade you chose not to take OR one you took and never logged, and nothing in the data can tell those apart. So it names what your log doesn't cover, shows where your fills and the sim's timing differed (both ways, never just the misses), and asks you to log the rest — it never tells you a number you 'gave up'. The sim's own entry/exit is one rule seen with hindsight, not the right answer to grade yourself against.
Signals your log doesn't cover: Sim trades in your logged window with no matching entry in your log. Crucially this is NOT 'signals you skipped': it's either trades you didn't take, or trades you took and haven't logged — this tool can't distinguish those, so it never counts them as a discipline failure. Logging the rest is what completes the picture.
Proof clock: A forward test only means something once it has enough out-of-sample trades to tell a real edge from luck. This shows how far along that road it is — the target is estimated from this test's own trades (the same math as the trade sample-size calculator), and it refines as more trades close. You can't rush it, and that's the point: trades your rules couldn't have been fit to are the only ones that count. Reaching the target is genuine out-of-sample evidence — still never a promise the edge lasts. If the test isn't beating buy & hold yet, it says so plainly instead of showing a countdown.

Alerts & signals

Mechanical heads-ups when your own rule triggers — never advice, and you always place any trade yourself on your own broker.

Alerts: A mechanical heads-up that one of your own rules just triggered on the daily close — not advice, and not a signal to follow blindly. You place any trade yourself on your own broker; we never touch your funds or your account. The trigger is measured on the close, but a real fill happens at the next open and can differ. Best used only after you've forward-tested the strategy — a backtest alone isn't proof.
Notification channels: Get a fired alert somewhere other than email — a Discord channel in this version. It's a mechanical notification that your own rule triggered, never advice: we only ever post a message, and we never place, route, or size an order. You paste a Discord webhook URL you create in your own server; it's stored encrypted and shown back only masked. Email always fires too. If a webhook stops working (you deleted it), the channel quietly disables itself so it doesn't keep failing.
Copy this signal to your broker: A plain-text restatement of what your own rule signalled — the action (buy/sell), the asset, the signal date, and a reference-only price — that you copy and re-enter yourself on your own broker. It deliberately carries NO size: sizing a trade to your circumstances would be personalized advice, so you always decide the size. We never place, route, or size an order, and never touch a cent. The price is our data-feed reference, not an order price, and our symbol is a data key — confirm the exact instrument on your broker, since symbols differ across venues. After you trade, you can log what you actually got on your forward test to compare sim vs reality.
Alert expiry: An alert that's been sitting idle eventually expires, so abandoned alerts don't quietly eat your quota — hit Renew to reset the clock (the clock also resets whenever it fires). An alert that's currently holding a position never expires (the exit signal is still owed), and higher plans expire later or not at all. Expiring only stops the watching; it doesn't delete your signal history.

Today's Setups

The honest census made live today — each day's firings shown with their measured record, misses foregrounded. A fact to test, never a tip.

Its census record: How this strategy's backtest did against simply buying and holding this name, over the one ~5-year window — beat, lagged, or too thin to judge. The same honest scoreboard as the rest of the site, not a judgement of today's trigger: a strategy that lagged overall can still fire today.
Its record on this name: Of this rule's past trades on this name, how often they closed in profit after real costs versus in the red — both sides, misses foregrounded. A past frequency, not a probability for today: held so far, not proof — and too few trades means no number is shown at all.
How long it took: Among the past trades that closed up, the typical time to get there, and how often it did NOT within about a quarter. A horizon, never a date; it describes the past, not a promise about this trigger.
Ordinary day vs real move: Today's move measured in units of this name's own typical daily range (its ATR). Under roughly one ordinary day is just normal wobble — nothing has happened yet; a large multiple is an unusually big day worth a careful look. It sizes the move, it does not call a direction.
The business behind it: For a company stock, a few plain facts from its filings — free cash flow, debt, returns — stated as facts, never a buy/sell rating. Not applicable to crypto, commodities or funds (no company to check); 'no financials on file' when we could not read them.

The Hunt

The quality-ladder screener — every name graded on four plain checks and grouped by a rung. A grade of quality to test yourself, never a ranking of how likely a move is.

Rung: A quality tier — Top Shelf, Strong, Workable, Stretch or Bottom Shelf — set mainly by the business-quality check, strongest first (a name whose business isn't shown sound sits near the bottom whatever its chart). A grade of quality, not a forecast that the name will rise; names are grouped by it, never ranked by how likely a move is.
Quick move (NEAR): The shelf for names set up for a quick +12% move — judged on business, trend, and how far the name tends to move. Speed is the defining check here.
Back toward its high (FAR): The shelf for names set up to work back toward their own 1-year high — judged on business, trend, and the size of that gap. Speed is not tested here.
Business check: Whether the company turns a profit and carries its debt, from the figures it files — graded sound, flagged or unproven. Not applicable to a fund or commodity, which has no company behind it.
Trend check: Whether the name is going up, sideways or falling, read from its distance to its own 20-, 50- and 200-day moving averages.
Move check: Whether a +12% move is within reach over about 60 trading days, on the name's own recent volatility — how much it tends to move, not the odds that a move pays off.
Gap check: Whether the name trades meaningfully below its own 1-year high — a price the market actually traded, a plain fact, never a third-party price target.

Go deeper

These are the pieces. The full recipe — the honesty rules the engine can't bend — is on the methodology page, and you can put any of these to work in the free backtest sandbox.

See what actually beats buy & hold — most don't, here are the rare few that do →