Custom data backtest equity affected by holdings cost

Hi Santiago,

The sharp spikes in your equity curve could be due to the spread costs incorporated into your simulated trade fills. In QuantConnect, QuoteBar objects let LEAN incorporate spread costs into your simulated trade fills to make backtest results more realistic. This is intended behavior and is designed to provide a more accurate representation of live trading conditions.

If you're using custom forex data, it's important to ensure that the data is accurate and correctly formatted. If there are any errors or anomalies in the data, this could potentially cause unexpected results in your backtests.

If you believe there's a bug or issue with the platform, I recommend submitting a support ticket so the QuantConnect team can investigate. You can also submit a data issue if you believe there's a problem with the data you're using.

Here's an example of how to handle QuoteBar data in Python:

def on_data(self, slice: Slice) -> None:
    quote_bar = slice.quote_bars.get(self._symbol)   # None if not found

And here's how to iterate through the QuoteBars dictionary:

def on_data(self, slice: Slice) -> None:
    for symbol, quote_bar in slice.quote_bars.items():
        ask_price = quote_bar.ask.close

Sources:

• Handling Data
• Forum Discussion