Using DeFi Liquidity Data to Analyze Pools and Optimize Execution

# backtesting.how to backtest


How to Backtest a Python Trading Strategy with LumiBot
======================================================

.. meta::
   :description: Run a Python trading strategy backtest with LumiBot, choose a historical data source, and inspect trades, logs, charts, and tear sheets.

Backtesting is a vital step in validating your trading strategies using historical data. With LumiBot, you can backtest strategies across various data sources such as **ThetaData** (our recommended vendor), **Polygon.io**, **Yahoo Finance**, **Polymarket CLOB prediction-contract history**, or even your own custom **CSV** files. This guide will walk you through each step of backtesting, explain the data sources, and introduce the files that LumiBot generates during backtesting.

.. note::

   **Why Backtest?**
   
   Backtesting allows you to see how your strategies would have performed in the past, helping you identify weaknesses or strengths before deploying them in live markets.

Installing LumiBot
-----------------------------------

Before you begin, make sure LumiBot is installed on your machine. You can install LumiBot using the following command:

.. code-block:: bash

    pip install lumibot

To upgrade to the latest version of LumiBot, run:

.. code-block:: bash

    pip install lumibot --upgrade

Once installed, you can use an IDE like **Visual Studio Code (VS Code)** or **PyCharm** to write and test your code.

.. tip::

   **Quick Setup for VS Code**
   
   1. Download and install **Visual Studio Code** from the official website: https://code.visualstudio.com/.
   2. Open VS Code and install the Python extension by going to **Extensions** and searching for **Python**.
   3. Create a new project folder for LumiBot.
   4. Open a terminal in VS Code and install LumiBot using `pip install lumibot`.
   5. You're ready to start backtesting with LumiBot!

.. tip::

   **Want hosted backtests instead?**

   `BotSpot <https://botspot.trade/sales?showLogin=1&utm_source=documentation&utm_medium=how_to_backtest&utm_campaign=lumibot&utm_content=hosted_backtests_tip&prompt=I%20want%20to%20backtest%20a%20Lumibot%20strategy%20on%20BotSpot.%20Please%20help%20me%20set%20up%20hosted%20backtesting%2C%20compare%20strategy%20variants%2C%20and%20prepare%20paper%20or%20live%20deployment.>`_ can help you create or revise Lumibot code with AI, run supported backtests on hosted data, compare multiple variants in parallel, and inspect charts, trades, logs, artifacts, and audit history without wiring the full local environment first.

Choosing a Data Source
-----------------------------------

Historical data is separate from the broker you use for paper or live trading.
Set ``BACKTESTING_DATA_SOURCE`` to select a historical provider without changing
your strategy. **This setting overrides a data-source class passed in Python.**
See :ref:`Choose your backtest data <backtest-data-source-selection>` for the
selection rules and setup examples.

LumiBot supports several data sources for backtesting, each suited for different asset types and backtesting needs. Here's an overview of the available sources:

**1. ThetaData (Recommended)**

- Deep historical coverage for U.S. equities and options with SIP-quality filtering.
- Offers free tiers plus paid plans with higher rate limits and multi-year history.

.. important::

   **Get Your ThetaData Account**

   Sign up at `ThetaData <https://www.thetadata.net/>`_. Use the promo code ``BotSpot10`` for 10% off the first order—ThetaData uses this code to credit BotSpot for the referral.

For more details, see the :ref:`ThetaData Backtesting <backtesting.thetadata>` section.

**2. Yahoo Finance**

- Free stock and ETF data for daily trading backtests.
- Suitable for longer-term strategies but not ideal for intraday backtesting.

For more details, see the :ref:`Yahoo Backtesting <backtesting.yahoo>` section.

**3. Polygon.io**

- Offers intraday and end-of-day data for stocks, options, forex, and cryptocurrency.
- Provides up to two years of free data; paid plans offer more advanced features and faster data retrieval.
- Best suited for existing workflows; new LumiBot users should consider ThetaData first for the BotSpot10 promo and deeper coverage.

For more details, see the :ref:`Polygon.io Backtesting <backtesting.polygon>` section.

**4. Pandas (CSV or Other Custom Data)**

- Allows for full flexibility by using your own custom datasets (e.g., CSV, database exports).
- Ideal for advanced users but requires more manual configuration.

For more details, see the :ref:`Pandas Backtesting <backtesting.pandas>` section.

**5. Polymarket CLOB**

- Uses real Polymarket CLOB price-history data for prediction-contract close-price bars.
- Trades CLOB outcome tokens as ``prediction_contract`` assets priced between ``0`` and ``1``.
- Uses LumiBot's normal market and limit backtesting fills from loaded Polymarket bars while enforcing prediction-contract price bounds, tick-size rules, minimum order size rules, market-close behavior, and resolved-market settlement when metadata is available.
- Keeps prediction-contract backtests on Polymarket/Pandas bars so they do not fall through to stock, Yahoo, or IBKR data paths.

For more details, see the :doc:`Polymarket broker guide <brokers.polymarket>`.

Running a Backtest with Polygon.io
-----------------------------------

Once you've selected your data source and built your strategy, you can run your backtest using the `run_backtest` function. This function requires:

- **Data source**: (e.g., Yahoo, Polygon.io, ThetaData, or Pandas)
- **Start and end dates**: The period you want to test.
- **Additional parameters**: Strategy-specific parameters.

Here's an example of a backtest using **Polygon.io**:

.. important::

   **You Must Use Your Polygon.io API Key**

   Make sure to replace `"YOUR_POLYGON_API_KEY"` with your actual API key from Polygon.io for the backtest to work.

.. code-block:: python

    from datetime import datetime
    from lumibot.backtesting import PolygonDataBacktesting
    from lumibot.strategies import Strategy

    class MyStrategy(Strategy):
        parameters = {
            "symbol": "AAPL",
        }

        def initialize(self):
            self.sleeptime = "1D"  # Sleep for 1 day between iterations

        def on_trading_iteration(self):
            if self.first_iteration:
                symbol = self.parameters["symbol"]
                price = self.get_last_price(symbol)
                qty = self.portfolio_value / price
                order = self.create_order(symbol, quantity=qty, side="buy")
                self.submit_order(order)

    if __name__ == "__main__":
        polygon_api_key = "YOUR_POLYGON_API_KEY"  # Replace with your actual Polygon.io API key
        backtesting_start = datetime(2025, 1, 1)
        backtesting_end = datetime(2025, 5, 1)
        result = MyStrategy.run_backtest(
            PolygonDataBacktesting,
            backtesting_start,
            backtesting_end,
            benchmark_asset="SPY",
            polygon_api_key=polygon_api_key  # Pass the Polygon.io API key here
        )

Optional: Using Environment Variables for Backtest Configuration
-----------------------------------------------------------------

Instead of specifying `backtesting_start`, `backtesting_end`, and data sources in your code, you can set these environment variables:

- ``IS_BACKTESTING``
- ``BACKTESTING_START``
- ``BACKTESTING_END``
- ``BACKTESTING_DATA_SOURCE``

If they are set, LumiBot will automatically pick them up. For example:

.. list-table::
   :header-rows: 1
   :widths: 20 60 20

   * - **Variable**
     - **Description**
     - **Example**
   * - IS_BACKTESTING
     - Read only by runners that explicitly check it. Setting it to **"False"** does not turn a ``backtest()`` call into a broker run; see :doc:`strategy_run_modes`.
     - False
   * - BACKTESTING_START
     - Start date in the format "YYYY-MM-DD".
     - 2025-01-01
   * - BACKTESTING_END
     - End date in the format "YYYY-MM-DD".
     - 2025-05-01
   * - BACKTESTING_DATA_SOURCE
     - Selects the historical provider and overrides the class in code. Use ``none`` to keep an explicitly supplied class. See :ref:`supported values and defaults <backtest-data-source-selection>`.
     - Polygon

Below is a short example showing how you might rely *entirely* on environment variables and **omit** any explicit date or data source definitions in code. Set ``BACKTESTING_DATA_SOURCE=Polygon`` in your environment to use Polygon.io (API key still required):

.. code-block:: python

    from lumibot.strategies import Strategy

    class MyStrategy(Strategy):
        parameters = {
            "symbol": "AAPL",
        }

        def initialize(self):
            self.sleeptime = "1D"

        def on_trading_iteration(self):
            if self.first_iteration:
                symbol = self.parameters["symbol"]
                price = self.get_last_price(symbol)
                qty = self.portfolio_value / price
                order = self.create_order(symbol, quantity=qty, side="buy")
                self.submit_order(order)

    if __name__ == "__main__":
        # Set in environment: BACKTESTING_DATA_SOURCE=Polygon
        # Set in environment: BACKTESTING_START=2025-01-01
        # Set in environment: BACKTESTING_END=2025-05-01
        polygon_api_key = "YOUR_POLYGON_API_KEY"  # Still required for Polygon
        result = MyStrategy.run_backtest(
            None,  # Auto-selects from BACKTESTING_DATA_SOURCE env var
            polygon_api_key=polygon_api_key
        )

For more information about running backtests, refer to the :ref:`Backtesting Function <backtesting.backtesting_function>` section.

.. tip::

   For a full list of supported configuration environment variables (audit telemetry, remote cache, profiling, etc.),
   see :ref:`Environment Variables <environment_variables>`.

Files Generated from Backtesting
===================================

When you run a backtest in LumiBot, several important files are generated. These files provide detailed insights into the performance and behavior of the strategy. Each file is crucial for understanding different aspects of your strategy's execution.

Tearsheet HTML
-----------------------------------

LumiBot generates a detailed **Tearsheet HTML** file that provides visual and statistical analysis of your strategy’s performance. The tear sheet includes:

- Equity curve
- Performance metrics (e.g., Sharpe ratio, drawdown)
- Benchmark comparisons

For more information, see the :ref:`Tearsheet HTML <backtesting.tearsheet_html>` section.

Trades Files
-----------------------------------

The **Trades File** logs every trade executed during the backtest, including:

- The asset traded
- The quantity of the trade
- The price at which the trade was executed
- The timestamp of the trade

This file is essential for reviewing your strategy's trading behavior and identifying any potential issues or optimizations.

For more information on how to interpret the **Trades Files**, see the :ref:`Trades Files <backtesting.trades_files>` section.

Indicators Files
-----------------------------------

The **Indicators File** logs any technical indicators used in your strategy, such as moving averages, RSI, or custom indicators. This file helps you understand how your strategy responded to market conditions based on specific indicators.

For more information, see the :ref:`Indicators Files <backtesting.indicators_files>` section.

Conclusion
-----------------------------------

LumiBot’s backtesting feature provides a powerful framework for validating your strategies across multiple data sources. By following this guide, you can quickly set up your environment, choose a data source, and begin backtesting with confidence.

For further details on each data source and the files generated during backtesting, refer to the individual sections listed above.