toptraders · cross-lab v2 · algorithm report

momts 4h, long and short — a bull-phase algorithm

xl-momts-4h-ls · 4h bar · window 2020-09-01 to 2026-08-13 · 548 instruments · book $1m

1. What it does

• Entry: time-series momentum: the return over a window left a band around zero
• Filter: the price is above its own long moving average — the market's side matches the rule's side
• Exit: on a trigger flip: the position closes when the same rule prints the opposite sign
• Side: long and short
• The decision is made at the bar close and the order goes at the next open. The rule sees no data after the trigger bar.

2. The two constraints

The equity curve

3. The nulls

Every number above is quoted against a distribution, not an average. p95 means five per cent of the random runs came out better than that level. A rule that sits inside the cloud has proved nothing.

Each control prints its number of runs: a p95 without its n is not a band but a single number of unknown precision. The relabelling takes ONE fixed permutation per run and holds it for the whole window; reshuffling on every bar would pay turnover the real book never pays and would understate the control.

The own-phase null is measured on that phase, not the whole window: comparing a phase result with the noise total would compare three years with one.

4. What it traded

The instrument list is rebuilt quarterly by dollar turnover, with no survivor selection: a name that was large and died is traded in the quarter where it stood at the top. Instruments measured: 548. Trades in the window: 9029, trades started before it: 0.

Never touched: names the desk does not trade, leveraged tokens, and anything past a seam in the series — past a seam it is a different instrument.

5. The timing audit

Verdict: clean. Trades checked: 100 of 9029. Mismatches: 0.

DSR and the trial count

The rest of the metrics

The six tiles above are a headline, not the set. Here it is in full, including the tail check: the share of the best three trades and the total without them. One without the other reads wrong in both directions.

Distribution of trades in R

R is how many units of risk a closed trade returned. The passport carries percentiles, not buckets, so percentiles are what stands here: a histogram off five numbers would draw a shape nobody measured.

The rules in full

The field and what it means. Thresholds, windows and multipliers are not here: an algorithm is reproduced from those, and the desk does not print them. The bot reads them from an internal file on its own machine.

Returns by year

The years come from the same months as the grid below. A partial year carries its month range. The controls have no monthly series in the artefact — only their window total is printed, and the desk will not invent yearly numbers for them.

The shape of the result

The four figures below are drawn from the same published values as the tables: the monthly grid, the drawdown, the windowed sharpe and the trades in R. No rule settings are in them.

By month

The sign of the month is the colour, the size is the saturation.

Drawdown over time

How long the book sat below its own peak. More honest than the single worst-drawdown number: both the depth and the length are visible.

Sharpe over a rolling six-month window

One window for every desk report. It shows whether the sharpe was bought by a single lucky stretch.

Trades in units of risk

The halves of the window

Cycle phases

An algorithm is not required to work in every phase. Its best phase is in the headline; the statistics outside that phase are printed too, and the drawdown outside it is part of the passport, not a footnote.

Costs and funding

On $1m

• AN EXIT ALWAYS FILLS: a position cannot be left open, and a perp the desk holds will be closed at any price. The bar-share cap therefore applies to entries only, while the exit's addition is capped at min(participation, 1). How many exits did not fit their bar is in exits_over_cap, and the heaviest one in max_exit_participation
• AN EXIT ON A BAR WITHOUT TURNOVER is counted separately (exits_without_turnover) and stays out of max_exit_participation: there participation is unmeasurable, not infinitely large. An empty max_exit_participation means no exit had measurable participation, not that exits took no part of a bar
• PARTICIPATION IS TAKEN AGAINST THE BAR'S FULL TURNOVER, a quantity known only at its close, while a real order sees the book at the moment it is sent. The error is optimistic, so the share skipped here is a LOWER bound
• the model does not know the order book: it cannot tell a bar whose turnover was one trade from a bar built out of a thousand
• AN EXIT ON BAR t IS FILLED BY THE BOT AT THE OPEN OF t+1. This is a standing caveat of the desk's paper topology: the engine closes the trade by its own rule, while the bot's book moves on the next bar. The difference between them is the price of the schedule, not of the rule.

6. What this leaves

controls failed: DSR, sharpe

Failed: DSR, sharpe. No account and no panel row are opened for such an algorithm. The row stays here because a negative result is published the same way as a winning one.