Custom Prices and Signals in BigQuant Backtests

Summary

This guide shows how to use BigQuant’s custom-data backtest input to simulate trades with user-defined buy and sell signals and a chosen execution price. The supplied historical data must include date, instrument, open, close, and volume fields. To make the engine use the desired price, the guide says to place it in the open field and configure both buying and selling to use that field. Because orders are submitted one day before they are filled, the example shifts each signal forward by one row and fills missing signals with zero.

The example derives a custom price from adjusted stock data, creates sample signals, and writes the resulting rows to a platform data table for use by a backtest strategy. It recommends checking recorded fills against the intended prices. This is a platform-specific simulation workflow, not evidence that such fills are achievable in live markets; the example does not discuss slippage, liquidity, or other execution constraints.

Key ideas

• BigQuant can use supplied historical data as the price source for a backtest.
• The custom dataset needs date, instrument, open, close, and volume columns.
• The desired fill price is placed in the open column and selected for buys and sells.
• Signals are shifted to account for the platform’s next-day order execution convention.
• Recorded simulated fills should be checked against the intended prices.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.