Optimization

Parameter optimization (sweeps) test your strategy across many parameter combinations to find the best configuration.

Running a Sweep

Via CLI

bash

tradectl sweep \
  -d data/prepared.bin \
  -r order_size=50:500:50 \
  -r threshold=0.5:2.0:0.1 \
  -p leverage=5 \
  --balance 10000 \
  --taker-fee 0.0004 \
  --maker-fee 0.0002 \
  --top 20 \
  --min-trades 5 \
  -o results.json

Flag	Description	Default
`-d, --data <PATH>`	Path to prepared data file	(required)
`-r, --range <KEY=MIN:MAX:STEP>`	Parameter range to sweep (repeatable)	(required)
`-p, --param <KEY=VALUE>`	Fixed parameters (repeatable)	—
`--balance <FLOAT>`	Initial balance	10000
`--leverage <FLOAT>`	Leverage multiplier	1.0
`--taker-fee <FLOAT>`	Taker fee rate	0.0004
`--maker-fee <FLOAT>`	Maker fee rate	0.0002
`--slippage <FLOAT>`	Slippage percentage	0.0001
`--top <N>`	Show top N results	20
`--min-trades <N>`	Minimum trades to include	5
`-o, --output <PATH>`	Save results as JSON	—

Via Dashboard

Go to Backtests > New Optimization
Select strategy and configure base settings
Define parameter ranges and step sizes
Select ranking metric (PnL, Sharpe, Calmar, Score)
Click Run

Progress and results stream in real-time.

Ranking Metrics

Metric	Description
PnL	Net profit percentage
Sharpe	Risk-adjusted return
Calmar	PnL / max drawdown
Win Rate	Percentage of winning trades
Profit Factor	Gross profit / gross loss
Score	`pnl% / (1 + max_dd%) * trade_factor`

Batch Engine

Sweeps use the BatchStrategy trait — a Structure of Arrays (SoA) interface that evaluates many parameter sets simultaneously in a single pass through the data:

rust

pub trait BatchStrategy {
    fn process_ticker(&mut self, ticker: &TickerEvent);
    fn check_trade(&mut self, trade: &TradeEvent);
    fn force_close_all(&mut self);
}

Optimization ​

Running a Sweep ​

Via CLI ​

Via Dashboard ​