Blog/Crodl Quant: Build and Backtest Strategies on Mac
General
Crodl Quant: Build and Backtest Strategies on Mac
Meet Crodl Quant, a Mac desktop workspace for Rune strategies, AI-assisted coding, historical backtesting, saved research, and paper forward testing.
A trading idea becomes easier to evaluate when you can define its rules, test it against historical data, and inspect the trades it produces.
Crodl Quant brings that workflow into a desktop application. It combines interactive charts, a strategy editor, AI-assisted coding, historical backtesting, and saved research in one workspace.
You can move from an idea to a working script, run a simulation, and return to the chart to understand what happened.
What can you do with Crodl Quant?
The chart is the centre of the Crodl workspace. Zoom into individual candles, pan through history, change timeframes, and use drawing tools and studies to examine price behaviour.
More ways to read every candle
Crodl Quant includes Heikin Ashi charts, Volume Candles, Volume Bars, Heikin Ashi Volume Bars, Renko charts and Range charts. Choose a view that helps you examine the price behaviour behind your idea, and customize candle appearance, chart styles and timeframes.
Heikin Ashi smooths price action to make trends easier to follow. Volume Candles change candle width with trading volume, while Volume Bars build bars around traded volume instead of fixed time intervals. Heikin Ashi Volume Bars combine volume-based bars with Heikin Ashi smoothing.
Renko and Range charts provide alternative ways to explore price movement. Multi-chart layouts let you compare markets and timeframes side by side in the same crypto charting workspace.
See where volume concentrates
VPVR, or Visible Range Volume Profile, shows how trading volume is distributed across prices in the visible chart. Fixed Range Volume Profile lets you select a particular range and inspect its volume distribution, point of control and value area.
Volume Bubbles highlight unusually high volume directly on candles. They serve a different purpose from Volume Candles and Volume Bars: one highlights volume on the chart, one changes candle width, and one changes how bars are built.
Feature
What it helps you examine
Heikin Ashi
Smoothed price action and trends
Volume Candles
Trading activity through candle widths that change with volume
Volume Bars
Bars built around traded volume rather than fixed time intervals
Heikin Ashi Volume Bars
Volume-based bars with Heikin Ashi smoothing
Volume Bubbles
Unusually high volume highlighted directly on candles
VPVR
Volume distribution across prices in the visible chart
Fixed Range Volume Profile
Volume distribution, point of control and value area in a selected range
Renko and Range charts
Price movement through alternative chart types
Custom chart settings
Candle appearance, chart styles and timeframes
Multi-chart workspace
Markets and timeframes viewed side by side
Build your strategy with AI
Describe your rules, review the generated Rune code and run a backtest. Crodl Quant's AI-assisted strategy builder helps you develop and refine an idea using your locally installed Claude Code or Codex CLI agent.
Rune also lets you write custom trading indicators and strategy rules directly. Keep the code and its plotted behaviour together as you refine the experiment.
Go beyond the headline result
Historical backtesting lets you test strategy rules with fees and slippage, then examine individual trades. Compare strategy inputs and use walk-forward testing to evaluate behaviour across chronological training and testing periods.
These views help you investigate how a strategy behaves across settings and time. Review the assumptions and trade analysis alongside the performance summary.
When you run a strategy, you can inspect its entries and exits alongside the candles. That makes it easier to connect the strategy’s rules with the trades in its results.
Use the workspace according to the question you are trying to answer:
Tool
Research question
Interactive charts and studies
What price behaviour am I trying to describe?
Rune strategy editor
Can I express the idea as explicit rules?
AI assistant
Can I develop and revise a script using supported tools?
Historical backtester
What trades do these rules produce under my chosen assumptions?
Saved runs
Which source, settings and candles produced this result?
Strategy Finder and research tools
How sensitive is the result to inputs, time periods and costs?
Paper forward testing
How does the simulation behave as new completed candles arrive?
Each view answers a different part of the research question. A plotted signal helps explain an entry; the trade list shows the simulated outcome. Keep both in view when deciding what to investigate next.
Turn your rules into a Rune strategy
Crodl uses Rune, its scripting language for strategies and indicators. The built-in editor lets you write and revise your logic alongside the chart, compile the script, and review diagnostics before testing it.
You can start with a template or develop your own rules. Change an input, adjust an entry condition, or revise an exit, then test the updated version against your selected history.
Keeping the editor and chart together makes iteration easier: the code, its plotted signals, and the resulting trades stay close to each other.
Build with an AI assistant
Crodl Quant uses locally installed Claude Code and Codex CLI agents for supported coding and research tasks. With your chosen CLI installed and signed in, you can describe an idea in ordinary language and work with the agent to develop a Rune script.
For example, a request could be:
Build a Supertrend strategy for the 4-hour chart with 1% take profit and 1% stop loss. Compile it, run a backtest, and show me the overview.
This is an example of the workflow, not a recommended trading setup. The assistant can help write and revise the script, respond to compiler feedback, and run supported backtesting actions. You can follow its progress as it works.
The calculations come from Crodl’s backtesting engine. The assistant helps you work with the tools; it does not replace the simulation with an estimated or invented result. You still need to review the rules, settings, and output.
AI features require your own Claude Code or Codex CLI installation and authentication. An AI account or provider subscription is not included with Crodl Quant.
Test the assumptions behind the idea
A useful backtest needs more than an entry signal. Market history, trading costs, position sizing, and execution assumptions all affect the outcome.
Crodl lets you select historical data and configure settings such as fees, slippage, position size, take profit, and stop loss. You can then examine the completed simulation through its overview, performance views, and trade list.
Metrics such as net profit and loss, maximum drawdown, trade count, win rate, and profit factor provide different views of the same run. Reviewing individual trades helps explain those numbers and can reveal behaviour that a headline return alone would miss.
Keep your research connected
Crodl retains saved runs with their strategy source, settings, and candle snapshots. You can reopen earlier work and inspect the context behind a result instead of trying to reconstruct the conditions from memory.
Strategy Finder and the research tools support broader investigation, including comparisons across strategy inputs, chronological training and holdout periods, walk-forward experiments, and cost sensitivity checks.
These tools help you ask more useful questions: Does the idea depend on one narrow setting? How does it behave on a later period? What happens when trading costs increase?
How should you review a backtest?
Review the settings, individual trades and performance summary together. A result is easier to interpret when you can trace it back to the rules and assumptions that produced it. Use the first run to check whether the script behaves as intended before comparing alternative versions.
Check the rules before judging the return
Take the Supertrend example above. The request specifies a timeframe and percentage exits, but you still need to review the generated strategy. Check how it defines an entry, which direction it trades, and how the take-profit and stop-loss conditions are represented.
A script that compiles has passed a code check. You still need to inspect its behaviour. Open several trades on the chart and compare the entries and exits with the rules you intended to test.
Useful questions for that review include:
Does each entry correspond to the condition described in the strategy?
Are the exit settings consistent with the experiment?
Are position size, fees and slippage configured as intended?
Are you comparing runs over the same market history?
Can you explain an unexpected trade from the source and settings?
If something is unclear, revise one part of the experiment and run it again. Changing several rules at once makes it harder to understand which change affected the output.
Read the metrics as a group
Net PnL describes the simulated outcome, while maximum drawdown shows a different aspect of the path taken to reach it. Trade count provides context for how much activity the run contains. Win rate and profit factor add further views, but neither explains the strategy on its own.
For example, two runs can finish with similar net PnL while producing different trade sequences and drawdowns. Inspect the trade list to understand that difference rather than selecting a version from the headline number alone.
Saved runs help you retain that context. Keep the strategy source, settings and candle snapshot attached to the result so you can revisit the experiment without reconstructing it from memory.
Compare inputs, later periods and costs
A promising result gives you questions to investigate. Use input comparisons to examine whether nearby settings behave similarly. A single attractive combination deserves closer inspection before you treat it as a useful configuration.
Chronological training and holdout periods let you separate the period used to develop an idea from a later period used to examine it. Walk-forward experiments extend that investigation across successive periods. These research workflows help you examine consistency; they cannot establish how future markets will behave.
Cost sensitivity checks ask another practical question: how much does the result depend on the fee and slippage assumptions? Keep the strategy rules unchanged while investigating costs so you can understand what the comparison measures.
A clear research note can be short: what changed, what stayed fixed, what happened, and what you want to test next. That is more useful than collecting attractive results without their context.
Observe simulated behaviour as new data arrives
Paper forward testing provides a separate way to observe a strategy using newly received, completed market candles. It uses a bar-based simulation and does not place exchange orders.
Local alerts are also available for monitoring configured conditions. Crodl must remain open and your Mac must stay awake for local alert monitoring to continue.
Historical backtesting, paper simulation, and live trading are different activities. During the beta, Crodl Quant focuses on research and backtesting and does not execute live exchange trades. A future update is planned to let you connect strategies developed in Crodl Quant to your Crodl bot for live execution.
A practical first session
Download and open the Mac beta.
Sign in with your Crodl access token or an eligible invite code.
Select a supported market, timeframe, and historical dataset.
Open a strategy template, write Rune code, or work with the AI assistant.
Review the backtest settings and run the simulation.
Inspect the trades, save the run, and revise the idea as needed.
The current beta targets Apple Silicon Macs running macOS 14 or newer. Windows support is coming soon. Guest invites are bound to one installation, and AI features need separate provider setup.
For more charting and strategy guides, browse the Crodl blog.
Frequently asked questions
What is Crodl Quant?
Crodl Quant is a desktop workspace for building and investigating trading strategies. It brings charts, Rune scripting, AI-assisted coding, historical backtesting and saved research together. You can inspect the simulated trades on the chart and revisit the source and settings behind a saved run.
Which Macs can run the beta?
The current beta targets Apple Silicon Macs running macOS 14 or newer. Access requires a Crodl access token or an eligible invite code, and guest invites are bound to one installation. Follow the Mac setup guide for the installation and access workflow.
Is Crodl Quant coming to Windows?
Yes. Windows support is coming soon. The current invited beta is for Apple Silicon Macs running macOS 14 or newer.
Is an AI subscription included?
No. Crodl Quant uses locally installed Claude Code and Codex CLI agents. You need to install and sign in to your chosen CLI; a provider account or subscription is separate from Crodl Quant. The assistant helps with supported coding and research actions, while the backtesting engine performs the simulation calculations.
Does Crodl Quant place live exchange orders?
Not during the beta. Historical backtests and paper forward tests simulate strategy behaviour without placing exchange orders. In a future update, you will be able to connect strategies developed in Crodl Quant to your Crodl bot for live execution.
That connection is planned and is not available in the current beta. For context on Crodl's trading platform, visit the Crodl website and read the Trading Triggers documentation.
Do local alerts keep running when my Mac sleeps?
Local alert monitoring requires Crodl to remain open and your Mac to stay awake. Account for that requirement when planning a monitoring session. Local alerts, historical tests and paper simulations serve different purposes, so review which workflow you are using.
Where can I ask about beta access?
Start with Crodl Quant and its setup guide. For questions, visit the Crodl Discord. Check the current access requirements before installing, since the application is an invited beta and release testing is ongoing.
Information disclaimer: Crodl Quant is currently an invited beta, with release testing ongoing. Historical results depend on the data and assumptions used; backtests and paper simulations do not predict future performance or guarantee profitable trading.
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