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What this feature is

When you create a strategy, Trinigence may provide:
  • warnings (risk flags and potential issues)
  • suggestions (improvements you can apply)
The goal is not to judge the strategy -
it’s to prevent the most common failure modes before you go live.
Warnings are about survivability and clarity - not about “good” or “bad” trading.

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When warnings appear

Warnings usually appear when Trinigence detects patterns like:
  • missing risk controls (no stop loss)
  • unrealistic TP/SL for the timeframe
  • too few trades (weak statistical confidence)
  • excessive filters (almost no trades)
  • high exposure / always-in-market behavior
  • ambiguous logic (can be interpreted multiple ways)
  • potential overfitting signals (fragile parameters)

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Types of warnings

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Missing or weak downside protection

Examples:
  • no stop loss defined
  • stop loss extremely wide relative to volatility
  • stop loss defined for long but not for short
Why it matters:
  • tail events can dominate outcomes
  • backtests can look fine until they don’t

Take profit & stop loss

Best practices for TP/SL.

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Too few trades

If trade count is very low, metrics become unreliable. Why it matters:
  • results can be driven by luck
  • small sample hides real risk
Suggestion:
  • test a longer period
  • loosen filters slightly
  • validate on multiple markets

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Over-filtering (strategy inactivity)

If filters remove most entries, the strategy may:
  • look “perfect” because it barely trades
  • be impossible to evaluate meaningfully
Suggestion:
  • start with baseline entries/exits
  • add one filter at a time

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High exposure / constant market risk

If exposure is high, the strategy is almost always in a position. Why it matters:
  • drawdowns can compound
  • risk rises in volatility spikes
Suggestion:
  • add regime filters
  • restrict trading windows
  • reduce position sizing

Trade frequency & exposure

Understand exposure as real risk.

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Parameter fragility (over-optimization risk)

If small parameter changes alter behavior dramatically, the strategy may be fragile. Suggestion:
  • simplify indicators
  • use standard parameters
  • test stability across ranges

Indicator parameters

Learn how parameters affect robustness.

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How to interpret suggestions

Suggestions are typically framed as:
  • “Add SL if missing”
  • “Consider a volatility filter”
  • “Try reducing trade frequency”
  • “Validate across multiple ranges”
A good workflow:
  1. accept safety suggestions first (SL, exposure)
  2. validate that behavior stays aligned with intent
  3. only then optimize performance

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What suggestions are not

Suggestions are not:
  • guaranteed improvements
  • financial advice
  • a promise of better returns
They are structured guidance to reduce obvious risk.

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Common suggestion patterns

Most common. Prevents tail losses and makes strategies backtestable under stress.
Helps avoid never-hitting TP or constant stop-outs.
Improves statistical confidence and makes debugging easier.
Reduces exposure in high-risk or low-liquidity periods.
Checks robustness and regime dependence.

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Best practices

  • Treat warnings as “must-review”, not “must-fix”
  • Fix survivability issues before performance tuning
  • Use suggestions to guide iterations, not to chase metrics
  • Always validate changes using trade history

How to read results

Use a stable process to evaluate improvements.

Common pitfalls

Mistakes that warnings try to prevent.

Position sizing basics

Sizing-driven risk warnings.

Trading schedules

Reduce exposure intelligently.

Improving a strategy

Turn suggestions into a clean iteration loop.
If a warning surprises you, it usually means the risk was invisible - not absent.