Daily Straddle Heatmap
AlgoTest heatmaps make it easier for you to understand a clear picture of your trading performance. These heatmaps visually represent data like time, performance metrics, and win rates. Think of them as a map highlighting where your strategies work best and where they stumble. For example, a heatmap might reveal that trades during certain hours of the day consistently yield higher profits.
We are taking four heatmaps today. Let’s understand what we can learn from them.
BankNifty Short Straddle:
- Best Time Slot: The 09:16 time slot performed the best with a total profit of 11,619, primarily at SL levels 10, 20, and 30.
- Worst Time Slot: The 11:15 and 12:15 slots show significant losses, with total losses exceeding -7,000.
- SL Impact: Lower SL levels (10, 20) seem more effective in reducing losses, while higher SL levels (70-100) yield consistently larger losses.
FinNifty Short Straddle:
- Best Time Slot: The 09:45 and 10:15 time slots performed well, with total profits of 1,824 and 385, respectively.
- Worst Time Slot: The 11:15 and 12:15 slots show the most significant losses, with totals exceeding -6,000.
- SL Impact: SL levels of 10-20 tend to limit losses effectively, while levels above 50 result in deepening losses.
MidCapNifty Short Straddle:
- Consistent Losses: This instrument underperformed across almost all time slots and SL levels, with cumulative losses reaching -190,675.
- SL Levels: Losses increase drastically at SL levels above 30, showing a poor risk-reward ratio for this instrument.
- Time Slots: The 10:15 slot was less negative compared to other times but still yielded a loss of -7,420.
Nifty Short Straddle:
- Mixed Performance:some text
- The 09:16 time slot showed moderate losses (-5,798) but performed better than other slots.
- The 10:15 slot stands out as the only profitable entry time (+2,591).
- SL Levels: Lower SL levels (10, 20) are effective in reducing the overall losses, while higher levels exacerbate the drawdown.
- Worst Time Slots: The 11:15 and 12:45 slots exhibit significant losses (-30,518 and -22,939, respectively).
