STRATEGY VALIDATION.

Don't risk real capital on a hunch. We run rigorous historical simulations using Python and VectorBT to prove your edge.

5yrs+

Tick Data

100+

Metrics

Monte

Carlo Sim

Python

Core Logic

Why Backtest?

A strategy that looks good in your head often fails when exposed to market realities like slippage, commission, and black-swan events.

We don't just "run a test". We stress-test your logic. We simulate variable slippage, check for curve-fitting, and perform Walk-Forward Analysis to ensure your parameters are robust, not just lucky.

Deliverables

Detailed HTML Report (Tearsheet)
Equity Curve & Drawdown Analysis
Monthly/Yearly Returns Heatmap
Trade-by-Trade Log (CSV)
Python Source Code (Optional)

backtest_engine.py

import vectorbt as vbt
import pandas_ta as ta

# 1. Define Signal Logic
entries = ta.rsi(close) < 30
exits = ta.rsi(close) > 70

# 2. Run Simulation
pf = vbt.Portfolio.from_signals(
  close, entries, exits,
  fees=0.001,
  slippage=0.0005
)

# 3. Analyze Stats
print(pf.total_return())
print(pf.max_drawdown())

What's Inside The Report?

We deliver a comprehensive standalone HTML file that you can open in any browser. It contains interactive charts and data tables.

1. Equity Curve & Drawdown

Visualize the growth of your capital over time. The "Underwater Plot" beneath the equity curve shows exactly how deep your drawdowns were and how long they lasted (Recovery Factor).

2. Returns Heatmap

A calendar view showing returns for every month and year. This helps identify seasonality effects—e.g., does your strategy underperform in December? Or is it weak on Mondays?

3. Trade Analysis

A histogram of your trade returns. We check for "Fat Tails"—are your wins coming from a few lucky outliers, or is the edge consistent across hundreds of trades?

4. Worst-Case Scenarios

We simulate what happens if execution delays occur (Slippage Analysis). We also highlight the "Max Consecutive Losses" to help you prepare psychologically.

Performance Metrics Analysis

CAGR

Compounded Annual Growth Rate

Sharpe Ratio

Risk-Adjusted Return

Max Drawdown

Worst Peak-to-Valley Drop

Win Rate

% of Profitable Trades

Sortino

Downside Risk Ratio

Calmar

CAGR / Max Drawdown

Expectancy

Avg Profit per Trade

SQN

System Quality Number

Refinement Process

We know that the first result is rarely the final one. That's why we include 10 Custom Changes in our package. Tweak parameters, add filters, or adjust stop-loss logic after seeing the initial results.

Standard

₹1,000 - ₹3,000

For standard indicators (RSI, MACD) and single timeframe logic.

Start Basic Backtest

Complex

₹3,000 - ₹7,000

For multi-leg options, multi-timeframe, or custom math logic.

Start Complex Backtest

* Disclaimer: Backtesting results are hypothetical and simulated on historical data. They do not account for liquidity risks, market impact, or future market conditions. Past performance is not indicative of future returns. Simulation includes estimated slippage and commission but real-world execution may vary.

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