What it is
This article explains the settings and market conditions you can use when building simulator policies - entry filters and stop/target replay. It helps you interpret results and build meaningful rules without needing to know how Tessera computes every label behind the scenes.
What you can do
- Scope simulations to the right account, dates, symbol, and side
- Build entry filter trees with AND/OR groups
- Filter on sessions, regimes, volatility, structure, and alignment at entry
- Replay stop-loss and take-profit distance changes on past trades
- Understand coverage, baseline vs filtered metrics, and when labels show as unknown
How it works
Scope parameters
| Setting | What it controls |
|---|---|
| Account | Which broker account’s closed trades are included |
| Date range / timeframe | Which trades by exit date (e.g. last 30 days, custom range, all-time) |
| Symbol | Optional - limit to one instrument |
| Side | Optional - long only, short only, or both |
The cohort uses the same date and timezone rules as the Trade Log. See Timezones and dates.
Entry filter actions
| Action | Effect |
|---|---|
| Remove | Trades that match the condition tree are removed from the filtered set |
| Keep only | Only trades that match the tree are kept |
You can nest conditions in AND / OR groups. Each leaf compares a market field at entry to a value (equals, in list, greater/less than for numbers).
No lookahead: every field is evaluated from candles at or before your entry timestamp.
Market conditions you can filter on
Trading sessions
Whether the trade opened during a named session window, such as:
- London, New York, Tokyo, Sydney
- Overlaps (e.g. London-Tokyo, London-New York)
Useful if your edge is session-specific.
Market condition (regime)
A broad label for the state of the market at entry:
| Label | Plain meaning |
|---|---|
| Accumulation | Quiet, compressed conditions |
| Expansion | Volatility picking up |
| Trend | Directional movement is dominant |
| Range | Sideways, mean-reverting conditions |
| Unknown | Not enough data at entry to classify |
Direction - longer horizon
Overall price drift leading into your entry: up, down, or flat. Flat means the move was too small to treat as clearly directional - not “no data.”
Direction - shorter horizon
Recent drift just before entry: again up, down, or flat with the same flat rule. Use both horizons to distinguish a long-term trend from a short-term pullback.
Structure (trend strength)
Buckets such as weak, medium, or strong trend - based on trend-strength style measures (e.g. ADX-style) at entry.
Volatility
Several related fields, including:
- ATR regime - whether volatility is low, normal, or elevated relative to recent history
- Bollinger squeeze - whether bands are tight (compression) or not
- Bollinger zone / position - where price sits relative to the bands
Higher-timeframe alignment
A score from 0 to 1 indicating how well longer-timeframe direction aligns with your trade direction (long or short). Higher = more agreement.
Entry window statistics
Numbers describing the price path up to entry, for example:
- Net percentage change over the window before entry
- Range (high − low) as a percentage of starting price
- Recent change over a shorter slice of that window
Useful for momentum or mean-reversion style filters.
Trade direction
Filter on whether the trade was long or short.
Exit replay parameters (stop-loss and take-profit)
When simulating management rules (not entry-only filters):
| Parameter | Meaning |
|---|---|
| Stop distance override | Counterfactual stop placed at a specified distance from entry |
| Take-profit distance override | Counterfactual target at a specified distance from entry |
| Replay legs | Test stop only, target only, or both |
Tessera scans historical candles from entry through your actual exit (plus a forward window when needed) to see whether stop or target would have been hit first on each bar.
Simulated PnL adjusts proportionally from your real trade - it does not re-size positions or re-simulate commissions from scratch.
Exit Placement reports use the same engine with recommendations per market context slice.
Reading results
Baseline - metrics for all closed trades in scope.
Filtered / simulated - metrics after your policy.
Delta - simple difference between the two.
Coverage
- Trades total - how many closed trades in scope
- Trades with entry bar - how many had a usable candle at entry for context
- Trades missing entry bar - gaps in market data; those trades may get unknown labels or limited condition evaluation
If coverage is weak, treat filter results with extra caution.
Limitations
- Only stop-loss and take-profit distance replay is supported for exit management today - not breakeven or trailing stops.
- Entry filters do not change per-trade PnL unless you are in exit-replay mode.
- Labels depend on market data quality; missing candles → unknown or reduced coverage.
- Condition trees are capped at 16 levels of nesting and 256 rules and groups total per policy - split across policy versions if you need more.
- The simulator still cannot model new entries or trade-sequence cascades - see Simulator overview and Understanding when results change.