Chapter 3: Fueling the Engine — Flawless Data Importation
With your symbol data settings meticulously defined, the next crucial step is to import the historical price data. This data is the fuel for StrategyQuant’s generation and testing engine; its quality and correct importation are vital for the integrity of your entire strategy development process.
The Data Import Interface:
When importing data from a source whose format StrategyQuant doesn’t automatically recognize, you’ll need to manually configure the import parameters. These are typically indicated by cells with a red border or requiring user input.
The No-Nonsense Import Workflow:
- Select Data File: Click “Choose” (or a similar button) to browse and select your historical data file (usually a .csv or .txt file).
- Automatic Format Detection: For data from well-known sources like Dukascopy (often recommended for its quality), StrategyQuant may automatically recognize the file structure and populate all necessary settings. If so, you can proceed directly to “Start import.”
- Manual Configuration (If Necessary): If the format isn’t auto-detected, you must provide the correct details:
- Skip Rows: If your data file contains header lines or descriptive text at the beginning that are not part of the actual price data, specify the number of rows to skip. The default is usually “0”.
- Column Mapping: For each column in your data file, you must assign the correct content type: Open, High, Low, Close, Volume (if applicable and reliable for your market), or Unused (to ignore a column).
- Date and Time Format: This is critical and must exactly match the format in your data file. Pay close attention to:
- Case Sensitivity: Often, month (MM) and hour (HH) designators need to be uppercase.
- Separators: Ensure date and time component separators (e.g., /, ., -, 🙂 are correctly specified.
- Combined Date/Time: If date and time are in a single column (e.g., “22.12.2025 15:36:00”), the mask must reflect this structure (e.g., “dd.MM.yyyy HH:mm:ss”).
- Delimiter: Specify the character that separates values within each row of your data file (e.g., comma
,, semicolon;, tab).
- Broker Profile Configuration (Recommended):
After the data format is fully defined, it’s highly recommended to apply or customize a Broker Profile. This step ensures your data reflects the conditions of your intended trading environment. In this section, you can:- Set the Timezone: Align your historical data to your broker’s server time. This is crucial for accurate session-based strategies and for replicating live market behavior.
- Define Spread: Assign the average or expected spread of your broker to ensure realistic backtesting.
- Input Swap Rates: Include long and short swap values (rollover interest) to simulate overnight holding costs — essential for strategies that hold trades across sessions.
- Initiate Import: Once all settings are confirmed, click “Start import.”
Import Duration:
The time taken to import data can vary from a few minutes for smaller 1-minute datasets to several hours for extensive tick data files, depending on the data size and your computer’s processing power.
A Career Built on Data Integrity:
Remember, the “No-Nonsense Trader” approach emphasizes fundamentals. The quality of your imported historical data directly impacts the reliability of every backtest and robustness check. Flawed data leads to flawed strategies and potentially costly errors in live trading. Take the time to source the best possible data and ensure it’s imported correctly. This diligence is a hallmark of a professional quantitative trader.