Is this becuase of the bad data in backtest?

"""
To address the issue of unexpectedly high costs when closing short call positions in a backtest, here are some steps and considerations based on the information gathered:
1. **Order Execution Details**: Use the `on_order_event` method in your algorithm to log detailed information about each order execution. This will help you track the fill prices, fees, and any slippage that might have occurred. You can also use the `OrderTicket.get_order_fee()` method to understand the fee structure applied to your trades.
2. **Market Conditions Analysis**: Investigate the market conditions at the time of order execution. High volatility or low liquidity can lead to unfavorable fill prices. Ensure your algorithm accounts for these factors by using appropriate volatility models or liquidity checks.
3. **Data Accuracy Verification**: Ensure the historical data used in the backtest is accurate and free from anomalies. Data errors can lead to unexpected results in backtests. You might want to cross-verify the data with another source or check for any known issues with the data provider.
4. **Risk Management Settings**: Implement risk management strategies to handle large price movements or unexpected costs. You can use QuantConnect's risk management models, such as the Maximum Drawdown Model, to halt trading if certain thresholds are breached.
5. **Simulate with Different Parameters**: Run the backtest with varying parameters or under different market conditions to see if the issue persists. This can help identify if the problem is systemic or specific to certain conditions.
6. **Consult Documentation and Examples**: Review QuantConnect's documentation and examples related to options trading and order execution. This can provide insights into best practices and common pitfalls.
By following these steps, you can better understand and mitigate the risks associated with high costs in closing short call positions during backtests. If you need further assistance with specific code implementations or adjustments, feel free to ask!
"""

Sources: Short Call Backspread - QuantConnect.com, Long Call Backspread - QuantConnect.com, Protective Call - QuantConnect.com, Terminal Link - QuantConnect.com, Bear Call Ladder - QuantConnect.com

Yes - that's a data error.

To confirm it and demonstrate it clearly, click on the graph icon beside the ticker to see the stock chart (it only charts the Close value).

It will show a trade icon along that chart - hovering the mouse over the icon will show the details of the trade. Zoom in to a week's period (click and drag the mouse over the desired time frame) - it should still look decent, with no extreme yet.

If you zoom in to 3 days or less, then the trade icon will show the extreme value, obviously out-of-whack with the actual market values.

Creating a custom OHLC chart in your project would further demonstrate that none of those curves approach the extreme value of your trade.

Report the data issues here:

The automatic Margin Call is triggered because of the extreme value shown in the corrupted values - this is not a Live data issue, only a back test data issue.

Let us know if you have more questions

Power thru and keep coding!

Marc