Simulating Strategies

The Simulate tab in the Strategy Lab lets you test a strategy idea against historical data before committing real capital.

All computation runs in your browser — results appear instantly and you can adjust parameters and re-run as many times as you like.

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Setting Up a Simulation

Configure the following parameters:

Parameter	What it controls
Asset	The trading pair to simulate (e.g. BTC-EUR)
Timeframe	Candle duration (1h, 4h, 1d)
Drop sensitivity	How much price must drop to trigger a buy (sigma)
Rise sensitivity	How much price must rise to trigger a sell (sigma)
Buy amount	EUR spent per buy order
Sell amount	EUR received per sell order
Starting capital	Total EUR allocated to the strategy
Fee %	Exchange fee per trade (default 0.25%)

If you navigated from the Explore tab, the asset and timeframe are pre-filled.

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Reading the Results

Results appear in layers, from simple to detailed:

Verdict (top level)

The hero number: portfolio end value. This is the single most important number.

Below it:

• Capital safety badge: safe or insufficient
• Summary sentence: “Over 1,440 daily candles, this strategy would have made 10 buys and 5 sells.”

Computed Thresholds

Two boxes showing the calculated buy and sell thresholds:

• Buy threshold (e.g. -4.2%) — “A drop of 4.2% or more triggers a buy”
• Sell threshold (e.g. +6.1%) — “A rise of 6.1% or more triggers a sell”

These are derived from the sigma values and the asset’s historical volatility.

Performance Comparison

Your strategy compared to two benchmarks:

• Monthly DCA — buying a fixed amount every month
• Buy and hold — buying once at the start

This shows whether the strategy’s active management adds or loses value compared to simpler approaches.

Fee impact is shown transparently.

Charts

Two-panel chart:

• Top panel — candle-to-candle price change with buy/sell threshold lines
• Bottom panel — price chart with trade markers and ACB line

Trade markers:

• Solid dots — executed trades
• Faded dots — ignored trades (blocked by capital, ACB, or inventory rules)

Narrative

A “What happened” section that surfaces problems in plain language:

• Capital ran out during a buy cluster
• Sells were blocked because price was below ACB
• Inventory was insufficient for sell triggers

If everything looks healthy, you get a clean bill of health.

Expandable Details

For deeper analysis:

• Signal breakdown (how many buys/sells executed vs ignored)
• Portfolio state over time
• Equity curve (strategy vs DCA vs buy & hold)
• Cash-over-time chart with danger zone

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Understanding Ignored Triggers

Not every signal results in a trade. The simulation shows exactly why:

Buy triggers ignored because:

• Insufficient capital — allocated capital is fully deployed
• Signal clustering — multiple buy signals arrive faster than capital recycles

Sell triggers ignored because:

• ACB protection — price is below the average cost base (Aurono never sells at a loss)
• No inventory — nothing to sell yet

Ignored triggers are not bugs — they are safety constraints working as designed.

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Suggestions

If the simulation reveals issues, suggestion cards appear:

• “Capital insufficient — try raising buy sigma to reduce trigger frequency”
• “Many sells blocked by ACB — try raising sell sigma for more patience”
• “Idle capital — try lowering buy sigma to deploy capital faster”

Click a suggestion to re-run instantly with adjusted parameters.

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Creating a Strategy from Simulation

When you are satisfied with the results, click “Create strategy”. This navigates to the strategy creation form with all parameters pre-filled:

• Symbol and timeframe
• Buy and sell amounts
• Allocated capital
• Computed drop and rise percentages

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Key Principles

• The simulation uses the same logic as Aurono’s live engine
• All computation runs client-side — no backend calls needed
• Results are deterministic — same parameters always produce the same outcome
• The tool answers: “Can this strategy survive its own rules?” — not “Will this make money?”