Final Analysis Documentation

Step 1: Write Your Query

Navigate to the Final Analysis page and enter your trading strategy in natural language. Be specific about:

• The asset you want to analyze (e.g., BTC, ETH)
• The timeframe (e.g., 1h, 4h, 1d)
• Entry conditions (e.g., "RSI crosses above 50")
• Exit conditions (e.g., "Stop loss 2%, Take profit 5%")
• Time period (e.g., "last 30 days", "from 1/1/2024 to 3/31/2024")

Buy when RSI crosses above 50 and exit when RSI crosses below 50 for BTC 1D from 1/1/2024 to 3/31/2024

Step 2: Review Parsed Parameters

After clicking "Analyze Query", the system will parse your query and display the extracted parameters. You can:

• Review the asset, timeframe, and time constraints
• Check entry and exit conditions
• Click "Edit Parameters" to modify any values before running the analysis

Step 3: Execute Analysis

Click "Execute Analysis" to run the backtest. The system will:

1. Load historical market data for the specified period
2. Calculate all required technical indicators
3. Evaluate entry and exit conditions on each bar
4. Simulate trades and calculate performance metrics

Step 4: Review Results

Once the analysis completes, you will see:

• Performance metrics (win rate, profit factor, Sharpe ratio, etc.)
• Interactive trading chart with entry/exit markers
• Trade history table with detailed P&L
• Equity curve showing account balance over time
• Option to export results as JSON or CSV

Required Information

Performance Metrics

Trading Chart

The interactive chart shows:

• Price candles: OHLC data for the selected timeframe
• Entry markers: Blue markers showing when entry conditions were met
• Exit markers: Green (profit) or red (loss) markers showing trade exits
• Indicators: Technical indicators used in your strategy

Trade History

The trade history table includes:

• Entry and exit dates/times
• Entry and exit prices
• Profit/loss in dollars and percentage
• Number of bars held
• Trade direction (long/short)

How to Edit Parameters

1. Click "Edit Parameters": After your query is parsed, you'll see an "Edit Parameters" button in the top right of the parsed query card.
2. Expand conditions: Click on any entry or exit condition to expand it and see all its parameters.
3. Modify values:
   • Use dropdowns to change indicators, operators, or types
   • Use input fields to adjust numeric values (periods, thresholds, etc.)
   • Use checkboxes for boolean options (like "Use ATR")
4. Save changes: Click "Save Parameters" at the bottom of the card to save your changes.
5. Execute: Click "Execute Analysis" to run the backtest with your updated parameters.

Entry Conditions

Entry conditions define when to enter a trade. You can specify multiple conditions, and they will be combined with AND logic (all must be true).

Buy when RSI crosses above 50 AND price breaks out of swing high for BTC 1D

This creates two entry conditions that must both be met simultaneously.

Sequential Conditions

You can also create sequential conditions that must happen in order using keywords like "then", "after", or "wait for":

First RSI crosses above 50, then price breaks above EMA 20 before entering long

Sequential conditions have a timeout (default 50 bars) to prevent waiting indefinitely.

Exit Conditions

Exit conditions determine when to close a position. Multiple types are supported:

Risk/Reward Ratio (RR)

Use Risk/Reward ratios to automatically calculate profit targets based on your stop loss distance:

Buy BTC when RSI > 30, SL 2%, TP 3RR for last 30 days

Indicator-Based Exits

Set your stop loss or take profit at dynamic indicator values that move with the market:

Buy when RSI > 50, stop below ATR trailing stop

Buy BTC, take profit at swing high

CSV Format

Your CSV file should have one of these formats:

timestamp,value
2024-01-01T00:00:00Z,45.2
2024-01-01T04:00:00Z,48.3
2024-01-01T08:00:00Z,52.1

timestamp,histogram,macd_line,signal_line
2024-01-01T00:00:00Z,12.5,245.6,233.1
2024-01-01T04:00:00Z,15.2,248.3,235.2

value
45.2
48.3
52.1

Using Custom Indicators

1. Reference your custom indicator in your query using its name (e.g., my_custom_signal)
2. After parsing, the system will detect the custom indicator and prompt you to upload a CSV file
3. Upload your CSV file with a name matching the indicator name in your query
4. The system will align your CSV data with market data timestamps and use it in the analysis

Enter long when my_custom_signal crosses above 50 for BTC 1D last 30 days

Example 1: Simple RSI Strategy

Buy when RSI crosses above 50 and exit when RSI crosses below 50 for BTC 1D from 1/1/2024 to 3/31/2024

This strategy enters long when RSI crosses above 50 and exits when RSI crosses back below 50.

Example 2: Breakout with Stop Loss

Buy when price breaks out of swing high and RSI is above 50 SL 2 ATR TP 3RR for BTC 1D starting from 1/1/2024 to march 2024

Enters on breakout above swing high with RSI confirmation. Uses ATR-based stop loss and 3:1 risk/reward ratio for take profit.

Example 3: EMA Crossover

Buy when 12 EMA crosses above 21 EMA for BTC 1H last 30 days

Classic moving average crossover strategy on 1-hour timeframe.

Example 4: Sequential Conditions

When EMA 12/21 crossover happens, then price moves 2 ATR away, then retest EMA 12 before entering long

Three sequential conditions: first crossover, then price movement, then retest before entry.

Example 5: Probability Analysis

What is the probability of BTC making a new high after RSI drops below 30 in the last 90 days?

Analyzes the probability of a specific market outcome rather than executing trades.

What is Monte Carlo Simulation?

When you run a backtest with 10 or more trades, the system automatically performs Monte Carlo analysis by:

1. Resampling your actual trades in random order (1000 simulations)
2. Calculating equity curves for each simulation
3. Generating confidence intervals and risk metrics
4. Identifying worst-case and best-case scenarios

Key Metrics Explained

Interpreting the Equity Curve Chart

The Monte Carlo equity chart displays:

• Dark band (25th-75th percentiles): Where 50% of simulation outcomes fall
• Light band (5th-95th percentiles): Where 90% of simulation outcomes fall
• Median line (50th percentile): The most likely outcome

When Monte Carlo Runs

Risk/Reward Ratios (RR)

Instead of specifying exact take profit percentages, you can use Risk/Reward ratios to automatically calculate profit targets based on your stop loss distance.

Buy BTC when RSI > 30, SL 2%, TP 3RR for last 30 days

Long when MACD crosses above 0, SL 2 ATR, TP 2RR

Indicator-Based Exits

Set your stop loss or take profit at dynamic indicator values that move with the market.

Buy when RSI > 50, stop below ATR trailing stop

Long when price breaks swing high, SL below SuperTrend

Short when EMA 12 crosses below EMA 21, stop above EMA 50

Buy BTC, take profit at swing high

Long when RSI crosses 50, TP at fibonacci 0.618

Buy on breakout, SL 2 ATR, take profit at EMA 200

Combining Exit Strategies

You can mix different exit types for sophisticated risk management:

Buy when RSI > 50 and MACD crosses above 0, stop below ATR trailing stop, TP 3RR for BTC 4H last 60 days

Indicator-based trailing stop with RR-based profit target.

What's Included in Strategy Cards

When you export a strategy, the generated image includes:

How to Share Your Strategy

1. Run Your Analysis: Complete a backtest with your trading strategy
2. View Results: Navigate to the analysis results page or history drawer
3. Click Share: Look for the "Share Strategy" button near your results
4. Download or Share:
   • Download as PNG image
   • Share directly to social media
   • Copy to clipboard

Best Practices for Sharing

Query Writing Tips

• Be specific: Always include asset, timeframe, and date range for accurate results
• Use clear language: "Buy when" is clearer than "if" or conditional statements
• Always specify exit conditions: Include stop loss or take profit to manage risk
• Match timeframes: Use the same timeframe for indicators and backtest period
• Test incrementally: Start with simple strategies and add complexity gradually

Interpreting Results

• Win rate alone isn't enough: Consider profit factor, Sharpe ratio, and max drawdown
• Look for consistency: Check if results are consistent across different time periods
• Review individual trades: Examine the trade history to understand when the strategy works and when it doesn't
• Consider market conditions: Results may vary in different market environments (trending vs. ranging)