> ## Documentation Index
> Fetch the complete documentation index at: https://kalpi.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Avg. Winning & Losing Trade

> Isolate the average size of your profitable executions versus your losing executions to calculate your Risk/Reward ratio.

While the Average Trade Profit blends all executions together, looking at the **Average Winning Trade** and **Average Losing Trade** in isolation reveals the true internal mechanics and risk management structure of your algorithmic strategy.

## The Formulas

To calculate these metrics, the engine splits your execution ledger into two distinct groups:

> **Average Winning Trade** = Gross Profit / Total Number of Winning Trades
>
> **Average Losing Trade** = Gross Loss / Total Number of Losing Trades

## Calculating Your Risk/Reward Ratio

Once you have these two numbers, you can instantly calculate your system's structural **Risk/Reward Ratio** by dividing the Average Win by the Average Loss.

| Strategy Archetype | Avg. Win | Avg. Loss | Risk/Reward | Tactical Reality |
| :- | :- | :- | :- | :- |
| **Trend Following** | ₹3,000 | ₹1,000 | **1:3** | Will be highly profitable even with a terrible Win Rate (e.g., 35%). Losses are cut immediately; winners run massively. |
| **Mean Reversion** | ₹1,000 | ₹1,000 | **1:1** | Requires a Win Rate heavily above 50% just to break even after transaction fees. |
| **High-Risk Scalping** | ₹500 | ₹2,500 | **5:1** | Highly dangerous. Relies on an extreme Win Rate (90%+). One bad loss wipes out five consecutive wins. |

> [!TIP]
>
> If your Average Losing Trade is consistently larger than your Average Winning Trade, you must implement stricter stop-loss parameters in the Kalpi Basket Builder to cut your downside risk faster.


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