Batchtesting with HaasLabs

A single backtest tells you how one configuration performed. But what if the optimal timeframe is 30 minutes instead of 15? What if a different RSI length would have doubled your returns? Answering these questions manually means running dozens or hundreds of backtests one at a time. HaasLabs automates this.

What Is HaasLabs?

HaasLabs (Backtest Labs) runs a parameter sweep across your script's settings. You define which parameters to vary and their ranges, and the lab runs a backtest for every combination in parallel. The results are sorted and ranked so you can identify the best configuration without manual trial and error.

Example: instead of guessing the right timeframe and RSI length, you tell the lab to test four timeframes (15m, 1h, 4h, 12h) and six RSI lengths (9 to 24, step 3). The lab runs 4 × 6 = 24 backtests and shows you which combination produced the highest ROI.

Access HaasLabs from the sidebar under HaasScript > Backtest Lab.

Creating a Lab

Step 1: Name and Script

Click Create your first lab from the landing page. The New Lab Config modal opens:

1. Enter a Name for the lab (e.g., "My lab")
2. Click Next

The Select Script modal appears. Choose the script you want to optimize. Use the sidebar to filter:

• All -- every script available
• Favorites -- scripts you starred
• Built-in -- HaasOnline original scripts
• Custom -- scripts you wrote

Select a script and proceed to the lab configuration page.

Configuring the Lab

The lab configuration page has two panels: Lab Configuration and General Settings on the left and Parameters on the right.

Lab Configuration

Algorithm -- Choose how the lab explores parameter combinations:

Algorithm	Behavior
Brute Force	Tests every possible combination exhaustively. Guaranteed to find the best result within your defined ranges, but can take a long time with many combinations.
Intelligent	Uses a genetic algorithm that evolves parameters over generations. Faster for large parameter spaces, but may not explore every combination.

Intelligent algorithm settings:

| Setting | What it controls |
| --- | --- |
| Maximum generations | How many evolutionary cycles to run |
| Maximum population | Number of configurations tested per generation |
| Maximum Elites | Number of top performers used as the base for the next generation. Elites are mutated (based on Adjust rate) and, if Mix rate is above 0, bred with another elite or a random result to produce the next population |
| Mix rate (%) | Probability of combining parameters from two parent configurations (0-100) |
| Adjust rate (%) | Probability of randomly mutating a parameter value (0-100) |

Higher populations and generations produce more thorough results but take longer. For most use cases, the defaults are a reasonable starting point.

General Settings:

Setting	Description
Account	Exchange account for the backtests
Market	Trading pair
Position mode (if Futures)	One-way or Hedge
Margin mode (if Futures)	Cross or Isolated
Leverage (if Futures)	Leverage multiplier (1x to max)

Parameters

The Parameters panel lists every configurable setting from your script, organized into sections (Trade Settings, Strategy Parameters, etc.). Each parameter row shows:

Column	Purpose
INCL	Toggle to include or exclude this parameter from the sweep
NAME	Parameter name
VALUE RANGE/SELECTION	Define the values to sweep
POSSIBILITIES	How many variations this parameter contributes

A parameter can be either:

• Fixed -- one value, no variation. The lab uses this value in every backtest.
• Range/Specific -- either a min, max, and step, or a set of specific values. Can be set by clicking the parameter's cogwheel.
• Multi-select -- choose specific values from a list (e.g., select "15 Minutes, 1 Hour, 4 Hours, 12 Hours" from available intervals)

The footer shows the total number of backtests the lab will run, calculated as the product of all parameter possibilities. In the example above, 4 timeframes × 6 RSI values = 24 backtests using BruteForce. This number updates live as you adjust parameters, so you can manage the scope. Intelligent algorithm shows the Maximum Population × Maximum Generations.

When to Use Which Algorithm

Use Brute Force when:

• The total number of backtests is manageable (under a few hundred)
• You need definitive results with no gaps
• You are optimizing a small number of parameters

Use Intelligent when:

• The parameter space is large (thousands of combinations)
• You want a fast approximation
• You are exploring broadly and plan to do a finer sweep later

Running and Monitoring

Click the green Start button to begin. The lab runs backtests in parallel:

• Labs Progress -- shows overall completion (populations tested, generations run) with a progress bar
• Backtest Progress -- individual backtest status bars for each population in the current generation
• Cancel -- the red Cancel button stops the run early, preserving any completed results

Reading Results

The results table lists every completed backtest ranked by performance. Key columns:

Column	Description
GEN / POP	Generation and population number (for Intelligent algorithm)
ORDERS / TRADES / POSITIONS	Activity counts
FEE COSTS	Total fees incurred
REALIZED PROFIT	Net profit after fees
ROI	Return on investment (percentage)
Parameter columns	The values used in that backtest (e.g., Interval, RSI Length)

ROI values are color-coded: green for positive, red for negative. Sort and scan the table to find which parameter combinations performed best. All results can also be downloaded as a single CSV file.

Result Options

Each row in the results table has an Options column. Hover over the icons to access:

Icon	Action
Report	Detailed results overview for this backtest
Chart	Candlestick chart with plotted indicators and trade markers
Log	Timestamped execution log with all script actions
Positions	Individual position records (entry, exit, profit, etc)
Orders	Every order placed during the backtest
Export settings	Opens a JSON popup of the exact parameter configuration. Download or copy it for import into a bot or the script editor
Create bot	Takes the configuration and creates a trade bot from it directly

The Create bot action is the end goal. Once you identify the best parameters, clone them directly into a live or simulated bot with one click -- no manual re-entry of settings.

Practical Tips

Start small, then expand. Do a coarse sweep with wider parameter steps first (e.g., SMA length 10 to 50, step 10). Then narrow into the best performing range with finer steps.

Watch the backtest count. Each additional parameter range multiplies the total. Sweeping 3 parameters with 4 values each already produces 64 backtests. Be selective about which parameters you vary.

Use fixed parameters strategically. Lock down parameters you are confident about and only sweep the ones where you are unsure. Every fixed parameter reduces the total backtest count.

Test across markets. Run the same lab on different trading pairs. A configuration that dominates on BTC/USDT may fail on a low-volume altcoin pair with different volatility.

Save before starting. Click Save before running the lab. If you want to revisit a configuration or tweak it later, you will not have to rebuild it from scratch.