Advanced Market
Algo Backtester.

Comprehensive Guide & Documentation

Welcome to the Digitaleyepath Quant Simulator. This tool is a 100% offline, client-side algorithmic trading backtester. Your proprietary market data and trading logic never leave your browser, ensuring absolute privacy for your strategies. Below is a detailed guide on how to utilize all 10 advanced features implemented in this engine.

1. Dataset Ingestion (Historical Price CSV)

The engine requires sequential price data to simulate market movements. You must paste your historical data into the CSV text area. The parser is flexible but expects data in chronological order.

2. Capital & Position Sizing

Risk management dictates long-term survival. The simulator allows you to define:

• Starting Capital: Your initial equity (e.g., $10,000).
• Position Size (%): The percentage of your current rolling balance allocated to a single trade. If set to 50% on a $10,000 account, the first trade risks $5,000. This simulates fractional compounding.

3. Realistic Execution: Fees & Slippage

Theoretical models often fail because they ignore the cost of execution.

• Trade Fee (%): Simulates broker commissions. A 0.1% fee is applied to both entry and exit legs, reducing your net profit factor.
• Slippage (%): Simulates the market impact of your market orders. An entry slippage of 0.05% means you buy slightly higher than the actual close price, and sell slightly lower.

4. Core Strategies (Entry Logic)

Select the logic the engine uses to trigger a "Buy" signal:

• Mean Reversion: Assumes assets return to a mean. Triggers a buy after two consecutive daily price drops.
• Momentum: Assumes trends persist. Triggers a buy after two consecutive daily price increases.
• SMA Crossover: A classic technical indicator. It calculates a 10-period Fast Simple Moving Average and a 30-period Slow SMA. Buys when the Fast SMA crosses above the Slow SMA.
• RSI Oversold: Calculates a standard 14-period Relative Strength Index. Triggers a buy when the RSI dips below 30 (oversold conditions).
• Monte Carlo: Executes random entries (20% probability per day). Used to stress-test your Take Profit and Stop Loss parameters against sheer market noise.

5. Exit Logic: Take Profit, Stop Loss & Trailing Stops

Once in a trade, the engine monitors the price against your risk parameters daily:

• Take Profit (TP): Exits immediately if the return hits this threshold.
• Static Stop Loss (SL): Exits if the price drops below your entry price by this percentage.
• Trailing Stop Loss (Toggle): If enabled, the SL is not anchored to your entry price. Instead, the engine tracks the highest price achieved during the trade. The Stop Loss is dynamically adjusted to trail this peak, locking in profits.

6. Analytics & CSV Export

The engine calculates advanced metrics like the Sharpe Ratio (using a 0% risk-free rate assumption for simplicity) to measure risk-adjusted return, and tracks Maximum Consecutive Losses to help you assess psychological drawdown.

You can review every trade in the interactive Trade History Log. To perform deeper analysis in Excel or Python, click the Export Trade Log button (the icon next to "Run Simulation") to download the raw trade array natively to your device.