Last Updated: July 15, 2026
Automated backtesting lets you write a trading strategy in plain English and run it across months or years of historical market data in minutes, not months. Instead of clicking through bars one at a time in manual replay, you describe your entry rules, exit rules, stop loss, and target in a text box. Zella AI parses your description into structured trading rules, runs every trade automatically, and delivers a full results dashboard with every individual trade visible on a chart. TradeZella offers plain English automated backtesting with built-in ICT indicators, pre-built templates, and AI-powered analysis of your results.
This tutorial walks through every step of the process, from typing your first strategy to inspecting individual trades on a chart. If you want the conceptual overview of what automated backtesting is and why it matters, start there. This article shows you exactly how the automated backtesting feature works inside TradeZella, step by step.
The entire process takes a few simple steps: navigate to the backtesting section, describe your strategy, fill in any missing details, confirm the parsed setup, run the backtest, and review your results. Most traders complete the setup in under two minutes. The backtest itself runs in two to three minutes depending on the time period and complexity. Here is each step in detail.
To start an automated backtest in TradeZella, go to the Backtesting tab in the left sidebar. Click the "Create Session" button in the top right corner. A dropdown appears with two options: "Backtest on your own" (manual bar replay where you step through it yourself) and "Automated backtest" (describe your strategy in plain words and let Zella AI run hundreds of trades for you). Select "Automated backtest" to begin.
When you open a new automated backtest in TradeZella, you see a text box with a simple prompt: "Describe entry, exit, stop, target, position sizing..." You write your strategy the same way you would explain it to another trader.
For example, an EMA crossover strategy looks like this:
"Go long when the 9 EMA crosses above the 21 EMA on the 5-minute chart; go short when the 9 EMA crosses below the 21 EMA. Place the stop loss just beyond the most recent swing low (for longs) or swing high (for shorts). Target a 2R take profit. Exit early if an opposite EMA crossover occurs before the target is reached."
That is the entire input. No Pine Script, no Python, no MQL5. Plain English.
A checklist below the text box confirms your strategy covers all four essential components: entry/exit criteria, stop loss strategies and profit taking, markets and trading days, and trade holding. Green checkmarks appear as Zella AI detects each component in your description.
After writing your strategy, you can click the "Enhance" button. Zella AI reviews your description and adds any missing details, clarifies ambiguous language, and strengthens the rules for more precise execution. This is optional. If your strategy description already covers everything, you can skip straight to "Continue."
If you do not want to write from scratch, the sidebar shows pre-built templates you can use as starting points. Each template is a complete strategy with entry rules, exit criteria, stops, and targets already defined. Templates include ICT concepts like 4h FVG + CHoCH + SMT, Asian range manipulation, iFVG Trading Model, and Break and Retest, all configured for futures instruments like /MNQ and /MES.
Every template is tagged by asset class (Futures), style (Intraday), and methodology (ICT, SMT). Click any template to pre-fill the strategy box, then customize it to match your own rules. This is especially useful if you trade fair value gap trading patterns or other ICT concepts and want a starting point that already understands the terminology.
Before continuing, you can click "+ Add" to open the controls panel. Controls are structured settings that override any conflicting information in your strategy text. The available controls are:
Controls are optional. If you include everything in your plain English description, you do not need to add any. But if you want to guarantee a specific symbol or session window regardless of what the text says, controls give you that precision.
After you click "Continue," Zella AI analyzes your strategy description. If any critical information is missing, it asks you structured follow-up questions instead of guessing. This typically includes four questions:
Question 1: Which market or symbol do you want to backtest? Options include ES (E-mini S&P 500), NQ (E-mini Nasdaq), MES (Micro E-mini S&P 500), MNQ (Micro E-mini Nasdaq), or you can specify your own symbol including stocks and forex pairs.
Question 2: What time period? Choose from the last 12 months, 6 months, 3 months, or specify a custom date range.
Question 3: Which trading session? Select Entire day (24/7), New York (09:30-16:00 ET), London (03:00-11:30 ET), Asia (19:00-03:00 ET), or add a custom window. You can select multiple sessions.
Question 4: What starting balance? Choose $10,000, $50,000, $100,000, or specify your own amount. This determines position sizing and percentage-based metrics.
If your strategy text or controls already specify these details, Zella AI skips the questions and moves straight to confirmation. The system only asks what it genuinely needs.
Before running the backtest, TradeZella shows you a confirmation page with everything Zella AI parsed from your strategy. This page displays:
Review this page carefully. If anything looks wrong, click the edit icon to adjust or "Go back" to modify your strategy. You can also click "Save" to save the setup as a template for future use without running it yet.
When everything looks correct, click "Run backtest." The system shows a "Preparing strategy..." screen while it processes, which typically takes two to three minutes depending on the time period and number of trades generated.
Once the backtest finishes, you get a full results dashboard with two tabs: Overview and Trade Log.
The Overview tab shows your strategy's performance at a glance:
Headline metrics: Win rate, profit factor, net P&L, total trades, and average win vs average loss. These are the first numbers you should check. A profit factor above 1.3 with at least 50 trades suggests a potentially viable edge.
Equity curve: A line chart showing your account balance over time. Look for consistent upward slope. A curve that spikes and crashes suggests the strategy is inconsistent or dependent on a few lucky trades.
Monthly P&L: A bar chart showing profit and loss by month. This reveals whether your strategy performs consistently or has large variance between periods.
Risk and return metrics: Sharpe ratio (risk-adjusted return), max drawdown management (largest peak-to-trough decline), Calmar ratio (return vs max drawdown), and Sortino ratio (downside-adjusted return). These advanced metrics help you compare strategies on a risk-adjusted basis, not just raw P&L.
Direction breakdown: How many long vs short trades the strategy took, and the win rate for each direction. If one direction significantly outperforms the other, you may want to filter your strategy to trade only in the stronger direction.
Below the metrics, Zella AI provides a written analysis of your backtest results. This is not a generic summary. Zella AI reads the actual data and tells you what it means:
This is the difference between looking at numbers and understanding what they mean. The trading expectancy might be negative, but Zella AI tells you exactly why and what to change.
Yes. The Trade Log tab shows every single trade the backtest generated, in order. Each row displays the trade number, date, direction (long or short), entry price, exit price, position size, P&L, exit reason (Target Hit or Stop Hit), and running balance.
This is one of TradeZella's key differentiators. TradingView's Strategy Tester gives you an equity curve and summary stats but does not let you click into individual trades on a chart. NinjaTrader shows a trade list but requires coding to set up the backtest in the first place. Most Pine Script or Python backtests give you aggregate metrics and nothing else. TradeZella shows every individual trade so you can identify patterns that summary stats hide: are the losses clustered on specific days? Do stops get hit by one tick before reversing? Are targets too ambitious for the session?
Click any trade in the log to open a detailed chart view. This shows the exact entry and exit on a TradingView chart with color-coded markers: entry price in blue, exit price in red or green, stop loss level, and target level. You can switch between timeframes (1m, 2m, 3m, 5m, 15m, 30m, 1h, 4h, 1d) to see the trade from different perspectives.
The trade detail panel also shows P&L, entry time, exit time, duration, position size, and exit reason. This level of detail turns a backtest from a numbers exercise into an execution review. You can see exactly where the strategy entered, where it placed the stop, and why it exited, just like reviewing a live trade in trade replay software.
A backtest is step one. Here is what to do with the results:
If the results look promising (profit factor above 1.3, positive expectancy, max drawdown under 20% of account): Save the strategy as a Strategies entry in TradeZella, then move to backtesting vs forward testing to validate with 20-30 paper trades at reduced size before going live.
If the results are marginal (profit factor between 1.0 and 1.3): Look at the Zella AI analysis for specific fixes. Common adjustments include tightening session filters, adjusting risk-reward ratio targets, or adding a higher timeframe confirmation. Run the modified strategy as a new backtest and compare.
If the results are negative (profit factor below 1.0): The strategy does not have an edge in the tested conditions. Check whether the issue is directional (long vs short breakdown), time-based (specific sessions underperforming), or fundamental (the entry logic does not predict direction). Modify the rules and test again, or try a different strategy entirely.
TradeZella offers both methods. Manual backtesting uses bar replay where you advance the chart bar by bar at speeds from 0.5x to 10x, placing orders as you would in live trading. Automated backtesting runs the same rules across the entire dataset in minutes.
Use automated backtesting when you want statistical validation across a large sample (50+ trades). Use manual replay when you want to practice execution, build muscle memory, or test discretionary elements that cannot be written as rules. Most traders use automated first to validate the edge, then manual replay to practice the execution
No. TradeZella's automated backtesting uses plain English. You describe your strategy the same way you would explain it to another trader. Zella AI parses your description into structured rules and runs them across historical data. There is no Pine Script, Python, or any other programming language involved.
Setup takes one to two minutes. The backtest itself runs in two to three minutes depending on the time period and number of trades generated. A six-month test on a futures instrument typically completes in under three minutes. Compare this to manual bar replay, which can take hours or days to generate the same number of trades.
TradeZella supports futures (ES, NQ, MES, MNQ, CL, GC, RTY, and more), stocks, forex pairs, crypto, and options. The system includes session filters for New York, London, and Asia, plus custom time windows for any instrument.
Zella AI asks you specific follow-up questions for any missing details. Common questions include which symbol to test, what time period to use, which trading sessions to include, and what starting balance to apply. If your description and controls already cover everything, the system skips the questions and moves straight to confirmation.
Yes. The Trade Log tab shows every trade with date, direction, entry price, exit price, position size, P&L, exit reason, and running balance. Click any trade to open it on a TradingView chart with entry, exit, stop, and target markers at any timeframe from 1-minute to daily.
TradeZella has built-in ICT indicators including fair value gaps, order blocks, breaker blocks, CHoCH (change of character), SMT divergence, and liquidity sweeps. The pre-built template library includes ICT strategies like 4h FVG + CHoCH + SMT and Asian range manipulation. You can also write any ICT concept in plain English and Zella AI will parse it. See the best backtesting software comparison for how this differs from competitors.
Use automated for statistical validation (50+ trades across months of data in minutes). Use manual replay for execution practice and testing discretionary elements. Most traders start with automated to validate the edge, then use replay to practice the execution before going live. TradeZella offers both in the same platform.
