Do I need to know how to code to use Agenticks?

No. AlgoAgent accepts prompts and converts them directly into backtestable strategies. AlgoAgent does the same for TradingView indicators. No coding, no Pine Script, no programming background required.

AlgoAgent is the product. You describe a trading idea and it turns that into explicit entry, exit, sizing and risk rules, writes the strategy as sandboxed Python, runs it over the included market history, and hands back every trade so you can judge the idea yourself.

How long can I run a backtest?

As far back as the instrument's own history goes. US stocks and ETFs run from as early as 2000-01-01 through 2026-03-31 and supported futures from 2016, at 1m, 5m, 15m, 30m, 1h and 1d. There is no five-year cap. Results include an equity curve, a full trade log, drawdown analysis, regime breakdown, Monte Carlo resampled from the real trades, and a prop firm pass estimate.

What is the AlgoAgent live automation lane?

On the Agent plan an approved strategy places its own orders through the brokerage you connected with SnapTrade (Interactive Brokers, Alpaca, Wealthsimple, Webull, Moomoo, Coinbase, Kraken, Binance and more). It runs on Agenticks servers, not in your browser, so it keeps running when your computer is off. You approve the strategy, pick the account, set sizing and risk limits, and arm it explicitly. Editing it creates a new version that needs a new approval. Several supported brokers are read-only. Paper-test first.

Quant Trading for Retail Traders

Structured, rule-based, data-driven trading explained for retail traders who want technical tools without needing to code.

Guides in this category

What Is Quant Trading? A Retail Trader's Clear Guide: Quant trading explained for retail traders: what it means, how it works, and how to apply structured, evidence-driven approaches without becoming a programmer.
Quant Trading vs Discretionary Trading: What Actually Changes?: A clear look at what changes when a discretionary trader moves toward a rule-based process, from decision-making to performance review.
How Retail Traders Can Use Quant Workflows Without Becoming Programmers: The practical tools and methods that let retail traders apply structured, data-driven approaches without writing code.
Rule-Based Trading: How to Turn Chart Ideas Into Testable Systems: A step-by-step look at converting a chart-based trading idea into a defined rule set that can be evaluated and improved.
Why Most Traders Misuse Indicators and What Quant Traders Do Differently: The structural difference between using indicators as signals versus using them as structured inputs to a defined process.
The Beginner's Guide to Systematic Trading Workflows: A plain-language overview of how systematic trading workflows are structured from idea to evaluation.
How to Build a Trading Process That Does Not Rely on Guessing: Practical steps for building a trading process with defined entry conditions, risk rules, and review standards.
Quant Trading Terms Every Retail Trader Should Know: A glossary of the most common quant trading concepts, from backtesting and Sharpe ratio to drawdown and expectancy.
How to Think Like a Quant Without Coding Full-Time: The mental frameworks that separate quant-style decision-making from reactive trading, explained without technical jargon.
From Chart Reading to Data-Driven Trading: The Practical Transition: How discretionary traders can gradually shift toward structured, data-backed workflows without abandoning what already works.
How to Trade Quant Without a Math Degree: Quant trading is about defined rules and tested evidence, not advanced mathematics. How retail traders apply a quantitative process using structured tools instead of building models from equations.
Quant Trading for Retail Futures Traders: A practical look at applying quant methods to futures: defining rules, testing them across regimes, and reviewing risk before automation, all without an institutional research desk.
What Makes a Trading Strategy a Quant Strategy: The line between discretionary and quant trading is whether the rules are defined and testable. What separates a quant strategy from a chart-reading approach, explained without jargon.
ES vs NQ: Which Index Future Should You Trade?: NQ moves faster and further. ES is steadier and cheaper per point. How the two differ on range, tick value and margin.
Micro Futures Explained: What MNQ Is and How It Works: MNQ is one tenth of an NQ contract, so a point is $2 instead of $20. What that means for your margin, your risk and your position size.
Using ChatGPT for Trading: What It Can and Cannot Do: ChatGPT is a great study partner for trading ideas, but it can't see live prices or prove a strategy works. Here's how to use it well and where you still need a tool that actually tests the idea.
How to Research a Market With AI: Researching a market with AI means asking a plain question about what usually happens after a setup, then letting the AI pull real price history to answer it with numbers. Here's how to do it, one step at a time.

Agenticks

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