GT AI Backtest — Strategy Testing & Optimization Guide

Назва статті**:** GT AI Backtest — User Guide / Manual

Опис статті: Learn how to use GT AI Backtest to build, test and optimize crypto trading strategies on real historical data.

Посилання на статтю (slug): gt-ai-backtest-user-guide

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Заголовок сторінки: GT AI Backtest — Strategy Testing & Optimization Guide | GT APP
Meta description: Learn how to use GT AI Backtest to build, test and optimize crypto trading strategies on real historical data, run AI-generated setups and launch them into live trading in GT APP with one click.
Meta keywords: GT AI Backtest, GT APP, crypto backtest, AI trading strategies, strategy optimizer, DCA backtesting, Trend Changer, futures backtest, spot backtest
Заголовок для соціальних мереж (70 сим): GT AI Backtest — Strategy Testing & Optimization Guide
Опис для соціальних мереж (120 сим): Build, backtest and optimize crypto strategies with AI, DCA and safety orders, then launch them into live trading in GT APP in one click.

GT AI Backtest — User Guide / Manual

GT AI Backtest is an AI-powered crypto backtesting platform designed for building, optimizing, and validating algorithmic trading strategies using real historical data. It works both as a strategy builder and a trading bot simulation environment, helping traders test ideas, analyze results, and deploy automated trading models directly into GT APP.

AI Backtest works equally well for beginners exploring strategy logic and for advanced traders building high-precision trading algorithms.

Feature	GT AI Backtest	Typical Backtest Tools
Completely free to use	✔	Limited, trial
AI-generated strategies	✔	✖
Multi-coin batch testing	✔	Limited
DCA + Martingale modeling	✔	Often unavailable
One-click launch to live trading	✔	✖
High-fidelity slippage & fee modeling	✔	Partial

Don’t have time to create your own? Launch strategies created and tested by leading LLM models in one click.

0. Flow Overview (How to use Backtest in 1 minute)

Select a coin and parameters on the left.
View the results on the right (AI strategies + backtest).
Scroll down, examine the chart, and entry/exit points.
View Strategy Parameters and Trades for analysis.
Optimize the strategy if necessary.
Click Launch Strategy.
Trade in GT APP.

1. Overview of the Interface

The platform consists of two main areas.

Left Panel — Strategy Setup,
Right Panel — AI Strategies & Backtest Results.

GT AI Backtest — User Guide / Manual
GT APP backtest main screen screenshot

1. Left Panel — Strategy Setup

Here, the user creates, configures, and optimizes the strategy.

Contains the following blocks:

GT APP backtest Strategy Setup screenshot

1.1 Market Setup

Coin Selection (Symbol)
Period Selection (Date Range)
Timeframe Selection (Timeframe)

Any changes here immediately recalculate the backtest results and are displayed on the right.

1.2 Trading Parameters

Entry parameters that determine the logic of the trade:

Direction (Long / Short)
Trend Changer toggle
Initial Margin (Collateral)
Leverage
Take Profit %
a. Trailing Take Profit toggle
b. Trailing Deviation (if toggle is switched on)
Enable Stop Loss toggle
a. Stop Loss % (if toggle is switched on)

1.3 DCA / Safety Orders

For users who want to work with averaging:

Enable Safety Orders
a. Safety Order Size %
b. Number of Safety Orders
c. Max Simultaneous SO
d. Martingale Ratio
e. Price Deviation
f. Martingale on Deviation

These parameters simulate the strategy’s behaviour during a drawdown.

1.4 Total Margin Required

The bottom of the block always displays:

the total amount required for the strategy to work,
the total cost of the position,
the “Optimize Strategy” button, which leads to the optimization page.

This area helps the user understand whether their deposit is sufficient.

1.5 Optimize Strategy

The Optimize Strategy button in the left block takes you to the optimization page.

The engine includes realistic slippage modeling, orderbook depth approximation, maker/taker fee simulation, and rolling-window volatility analysis to ensure accurate replication of real trading conditions.

2. Right Panel — AI Strategies & Backtest Results

The right side of the screen is dynamic: it displays everything that the system has calculated based on the selected parameters.

2.1 Daily AI / LLM Strategies

At the top, there are 4 cards from top LLM models:

Claude
GPT
Grok
DeepSeek

Each card displays:

the coin selected by the model,
trading pair,
the projected profitability (PnL %),
a Run button to launch the strategy.

This is a quick way to start trading “like an AI.”

GT AI Backtest — User Guide / Manual
4 cards Strategy Setup from top LLM models screenshot

2.2 Backtest Results

Below is a block of backtest results for the current user strategy:

Total Trades
Win Rate
PnL (USDT)
PnL (%)
Average Profit per Trade

All values are updated instantly when you change the parameters on the left.

If you want, you can share your backtest results with anyone. Just click “Share” and send the link.

GT AI Backtest — User Guide / Manual
GT APP backtest results screenshot

2.3 Backtest Chart

The chart shows:

all strategy entry and exit points (buy/sell orders)
the chart also has a panel of standard trading tools on the right.
visualisation of the short or long trend, if the setting is enabled.

The most important element in this block is the button “Launch Trading”.

You can choose where to start: Binance, HyperLiquid, or launch demo trading on GT APP.

GT AI Backtest — User Guide / Manual
GT APP backtest Chart screenshot

Launch Strategy

Once users have:

configured the parameters,
optimized the strategy,
seen a suitable result on the chart,

Once they click Launch Trading, all configured data will be automatically transferred to their GT APP, so there is no need to re-enter anything manually — everything will appear on the screen instantly.

(A registered GT APP account and an active exchange connection are required to launch.)

3. Strategy Parameters Overview

Below the chart is the Strategy Parameters block, which contains:

selected trading pair,
timeframe,
indicator signals,
TP/SL parameters,
number of safety orders,
backtest period.

This is a short summary of the strategy in a convenient, compact format.

GT AI Backtest — User Guide / Manual
GT APP backtest Parameters Overview screenshot

4. Trades List

Next are horizontal trade cards.

Each card displays:

trade type (LONG/SHORT),
entry price,
exit price,
time,
trade P&L.

Clicking on any card opens detailed information, allowing you to analyze each trade and optimize your strategy.

GT AI Backtest — User Guide / Manual
gt-app backtest Trades List screenshot

Data Sources & Execution Model

GT AI Backtest uses:

Binance historical market data (candles, ticks, volume)
CEX/DEX orderbook snapshots
real-fee maker/taker execution rules
slippage modeling based on liquidity depth
liquidation price simulation
leverage and margin engine identical to real exchange behavior

This ensures high-fidelity replication of real-world trading conditions and makes every backtest statistically meaningful.

5. Strategy Optimizer — Optimization Page (Full Explanation)

Optimization helps you automatically test multiple parameter combinations to find the most profitable version of your trading strategy.

The optimization window is divided into three key vertical blocks, each of which affects the final result.

GT AI Backtest — User Guide / Manual
GT APP backtest Optimization Page screenshot (Left, Middle and Right Block)

5.1 Left Block — Market Setup (Selection of Coins & Timeframes)

This block determines which coins and timeframes will be optimized.

Key elements:

1) Symbol Selection (multiple coins simultaneously)

The user can:

select a single coin,
or a group of coins (e.g., BTC, ETH, SOL, AVAX, etc.),
see a list of all added coins below the block.

The optimizer will test each coin using the selected parameters and then show the top performers.

2) Timeframe Selection

You can select:

a single timeframe (e.g., 5 minutes),
or multiple timeframes (5 minutes, 15 minutes, 30 minutes, 1 hour, etc.).

Each timeframe undergoes a separate optimization cycle.

3) Date Range

Period selection — for example: 1 Week or 1 Month, or Custom. The period selection affects the amount of data and calculation time.

4) Direction (Long / Short)

Optimization only takes into account the selected direction. If you’re considering testing in both directions, select both.

5) Initial Margin Notice

A hint appears below the block: “Optimizer uses Initial Order Size = $500 from your backtest settings. Position size = Margin × Leverage.”

This is important — the optimizer relies on the settings specified in the main Backtest window.

5.2 Middle Block — Core Parameters Optimization (TP, SL, Leverage)

The center column controls the key parameters that most influence the strategy’s outcome.

Take Profit Range (%)

Allows you to specify the testing range:

Minimum TP (e.g., 0.3%)
Maximum TP (e.g., 5%)
TP step (e.g., 0.3%)

The optimizer automatically runs all possible values from the minimum to the maximum with the selected step.

Leverage Range

Parameters:

Minimum leverage (e.g., 1x),
Maximum leverage (e.g., 20x),
Testing step (e.g., 1x).

A larger range allows you to determine: at what leverage the strategy is most effective and safe.

Stop Loss Range (%)

Allows you to test the strategy’s behavior at different SL levels:

SL range,
Step (e.g., 1%).

The goal is to find a balance between security and maximum PnL. These parameters are the core of optimization. A properly chosen range significantly increases the strategy’s effectiveness.

5.3 Right Block — DCA / Safety Orders Optimization (Optional)

This block can be enabled or disabled as desired. When the toggle is active, the optimizer cycles through the averaging parameters.

Important: DCA behavior optimization introduces a huge number of combinations, therefore optimization time grows exponentially.

Number of Safety Orders Range

Determines:

Minimum number of safety orders
Maximum number of safety orders
Change step

The optimizer tests different averaging structures.

Martingale Ratio Range

Setting the subsequent order size amplification:

Range (e.g., 1.10 – 1.50)
Step (e.g., 0.10)

Gives an understanding of whether and how much to amplify positions when the price falls.

Price Deviation Range (%)

Determines the depth at which safety orders are triggered:

PD min (e.g., 2%)
PD max (e.g., 5%)
PD step

This affects the risk and frequency of averaging.

GT AI Backtest — User Guide / Manual
GT APP backtest Optimization Results screenshot

5.4 Running Optimization

After setting all ranges, the user clicks: Run Optimization. The process of trying all possible parameter combinations begins.

The following appears on the screen:

1) Progress Bar
Shows how much of the calculations have already been completed.

2) Log Output / Event Log
Shows:

Coin,
Current parameter combination,
PnL,
Calculation time.

3) Tests Counter
Shows how many tests have been completed and how many remain.

5.5 Optimization Results — Choosing the Best Strategy

After completion, the user sees a list of top combinations sorted by key metrics:

PnL (profit first),
Win Rate,
Number of Trades,
Safety Order Structure,
Leverage & SL/TP Combination.

Each line represents a completed strategy.

Clicking the “Apply to Backtest” button instantly transfers the selected set of parameters back to the Backtest window.

After this, the user:

sees the results on the chart,
can examine the trades,
and, if necessary, click Launch Trading.

GT AI Backtest — User Guide / Manual