No, you cannot simply add them up. When multiple strategies share one pool of capital, each strategy's backtest return is calculated under the assumption that "all of this money belongs to it alone." Adding the percentages together assumes the same money is used multiple times at once, which has no real-world mathematical meaning. The correct approach is to first convert each strategy's profit and loss back into dollar amounts, simulate the inflow and outflow of cash and the available balance in the same capital pool in chronological order, and finally divide the total profit and loss by the peak capital actually occupied to get a portfolio-level return.
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Why percentages cannot be added
When a strategy backtests at a 30% annualized return, it usually means "if I give it an independent, fixed amount of capital, it earns 30% of that amount." Two strategies each earning 30%, added together to 60%, implicitly assumes that "the first pot of money earns 30% while a second, identical pot of money independently earns 30% at the same time." But under shared capital, the second pot does not exist independently — it is the same pot as the first.
Research has specifically pointed out this structural error: when you directly sum the percentage returns of multiple trades, each trade's denominator is its own entry price. These denominators are not the same quantity, so the summed result does not correspond to "the return on $1 of principal," nor does it correspond to "the return on total invested capital," nor does it correspond to any fixed dollar amount. Therefore, it has no well-defined real-world interpretation. The fix is straightforward: first sum the dollar amounts, and only calculate one percentage at the end, using total profit and loss divided by the capital actually deployed.
What you actually need to simulate under shared capital
When backtesting software handles a "common capital pool," the logic is not to add up each strategy's return. Instead, all strategy signals enter the same account and compete for buying power according to some priority rule. When buying power is exhausted, lower-priority or lower-weight signals are skipped. This means the final portfolio return depends on which signals were actually executed and which were squeezed out, not on the sum of what each strategy "would earn if run independently."
This leads to an easily overlooked consequence: if two strategies frequently issue entry signals at the same time, shared capital will cause one of them to be skipped. The skipped trade might happen to be the profitable one. Trading system research has documented such a case: when insufficient buying power caused about 34% of trades to be skipped, the system's overall performance dropped by more than 12 times, while the skipped trades contributed 72% of all trading profits. In other words, capital constraints are not just "earning a bit less" — they can systematically filter out the best opportunities.
A reproducible comparison framework
Suppose you have 10,000 USDT and two strategies, A and B.
Independent capital backtest results: A runs on 10,000 and earns +20% (profit 2,000). B runs on 10,000 and earns +20% (profit 2,000). Intuitively, you might think "if both run together, I should earn 4,000, which is 40%." But that is wrong, because you do not have 20,000.
Actual simulation under shared capital: In the same 10,000 account, process A's and B's signals in chronological order. Suppose A opens a position first and occupies 8,000. B then issues a signal but only 2,000 remains available, so B can only open a position of 2,000 in size (or is completely skipped). At the end of the period, A earns 8,000 × 20% = 1,600, and B only earns 2,000 × 20% = 400 (if not skipped). Total profit is 2,000, and the portfolio return is 20%, not 40%. If B is completely skipped due to insufficient funds, total profit is only 1,600, for a return of 16%.
This example shows that the portfolio return under shared capital is usually lower than the simple sum of each strategy's independent returns, but it may be higher than the return of a single strategy (if the two strategies you chose do have a diversification effect, the portfolio's volatility and drawdown may be lower than a single strategy's). The value of a portfolio lies in risk-adjusted improvement, not in stacking percentages on top of each other.
What you should look at instead
Do not look at "Strategy A annualized 30% + Strategy B annualized 25% = portfolio annualized 55%" as if it were addition. Instead, look at the portfolio equity curve produced by your backtesting software or your own simulation: starting from the same initial capital, execute all signals in chronological order, record every unit of capital actually occupied, every skipped signal, and the total equity at the end of the period. The return and maximum drawdown calculated from this curve are what this pool of money could realistically experience.
If two strategies have highly overlapping trading hours and both tend to go all-in under similar market conditions, the compression effect of shared capital on results will be obvious. If their signals are scattered across different times, the friction from capital constraints will be smaller. Before deciding whether to put two strategies into the same account, looking at the degree of overlap in their signal timing and their respective position sizes is more useful than looking at their individual backtest returns.
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