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What a trading schedule is

A trading schedule defines when a strategy is allowed to open new trades. Schedules are a risk and behavior control layer:
  • reduce exposure during unwanted periods
  • keep behavior consistent with your intent
  • prevent trades in low-liquidity or high-risk windows
By default, schedules usually affect entries, not exits.
Schedules are filters, not signals.

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Common schedule types

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Day-of-week schedules

Examples: 
Trade only on Monday, Wednesday, Thursday, and Friday.
Do not trade on weekends.
Use cases:
  • avoid weekend volatility in crypto
  • match your preferred monitoring days
  • remove periods with historically weak performance

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Time-of-day schedules

Examples: 
Only trade between 08:00 and 20:00 UTC.
Do not open trades after 22:00 UTC.
Use cases:
  • avoid low-liquidity hours
  • exclude high-slippage windows
  • align with your workflow

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Session-based schedules

Examples: 
Trade only during London and New York sessions.
Avoid the Asian session.
Use cases:
  • focus on high-liquidity sessions
  • reduce noise during off-hours
  • better match volatility expectations
Sessions are timezone-sensitive. Always specify timezone when sessions matter.

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What schedules affect

In most strategies, schedules control:
  • whether entry logic is evaluated
  • whether a new position can be opened
Typically schedules do not:
  • close open trades automatically
  • override exit logic
If you want “close at a certain time,” you must define it as an exit rule.

Time & session logic

Learn the difference between filters and triggers.

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Timezone behavior

Schedules depend on timezone. If timezone is:
  • explicitly defined → schedule is evaluated in that timezone
  • missing → Trinigence uses a safe default and shows it
Best practice:
  • use UTC for consistency unless you have a reason not to

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Combining schedules with filters

Schedules are commonly combined with indicator filters. Example: 
Trade only during London session AND only when the 4h trend is bullish.
This typically:
  • reduces trade frequency
  • reduces exposure
  • improves selectivity
But it can also reduce trade count too far if overdone.

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Defaults and assumptions

If schedule is:
  • explicit → applied exactly
  • implied (“weekdays only”) → inferred conservatively
  • ambiguous → ATI asks for clarification

What Trinigence fills automatically

See how schedule gaps are handled.

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Common mistakes

Schedules restrict entries. Exits must be defined separately.
Narrow schedules can eliminate trades and create misleading backtests.
Session rules can shift by an hour depending on timezone assumptions.
Schedules improve behavior, but they don’t create edge.

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Best practices

  • Start with simple rules (weekdays only)
  • Use UTC when possible
  • Avoid over-restricting early
  • Validate trade count after adding schedules
  • If you need “close at time,” define an explicit exit

Schedule & filters

See how schedules fit into strategy structure.

Trade frequency & exposure

Schedules directly change frequency.

How to read results

Check trade count after scheduling.

Common pitfalls

Scheduling mistakes that mislead.

Time & session logic

Time-based conditions in detail.
Schedules reduce opportunity.
Use them to reduce risk - not to force profitability.