As I understand it, Return percentages and drawdown percentages are calculated based on maximum allocation capital. If an Algo with 500k max. capital allocation generated 1000k profits in the past, does it mean 100k allocation to that particular Algo would have generated 200k profits. Or something different.
Why returns are not calculated on deployed capital
Hi @nijinwilson
The returns generated by an Algo may or may not be directly proportional to the capital allocated. Let me explain with an example.
Suppose an Algo has:
Minimum allocation: ₹1,00,000
Maximum allocation: ₹5,00,000
Also assume that trading 1 lot requires a margin of ₹60,000.
Now, if a user allocates ₹1,00,000, the Algo will trade only 1 lot, since trading 2 lots would require approximately ₹1,20,000, which exceeds the allocated capital.
On the other hand, if a user allocates ₹5,00,000, the Algo can trade 8 lots, utilising around ₹4,80,000 of the allocated capital.
In such a scenario, the return generated per lot remains the same, but the overall portfolio-level return and capital utilisation differ because the number of lots traded is different.
This is one of the reasons why returns cannot always be scaled linearly based on the capital allocated.
Regarding your second question, the platform displays performance metrics based on the maximum allowed capital allocation because it provides a standardised and consistent benchmark for all users. Since every user may allocate a different amount of capital, calculating historical performance based on individual allocations would result in different return percentages for the same Algo, making comparisons difficult.
By using the maximum capital allocation as the reference, every user evaluates the Algo using the same historical dataset and the same benchmark, making it easier to compare different Algos on an equal footing before making a deployment decision.