One strong month proves very little
A single +20% month can result from skill, favourable market conditions, concentrated exposure, leverage, luck or some combination of those factors. It is evidence about one period, not proof of a sustainable return rate.
Sustained 20% monthly returns become mathematically extreme
If 20% net growth were repeated every month with full reinvestment, $10,000 would mathematically grow to about $89,000 after 12 months and roughly $795,000 after 24 months. Those numbers show how demanding the assumption becomes; they are not forecasts.
See the compounding mathematics in detail →
The key question is what risk produced the return
High returns should be evaluated together with maximum drawdown, leverage or amplification, position concentration and the size of losing trades. A return figure without the path used to produce it gives an incomplete picture.
Compare return and drawdown properly →
Track-record length matters
Three strong months, 12 months and several years are very different samples. The longer a strategy operates across changing market conditions, the more useful its history becomes. Even a long record, however, cannot guarantee future results.
Average return can hide volatility
An average monthly result does not mean each month was close to the average. Large positive months can offset losing months, and a smooth average can conceal significant swings in capital.
Net return matters more than headline return
If a programme charges a performance fee or other costs, compare the return that remains after fees. Gross strategy performance and investor-level net return are not interchangeable.
Understand performance fees and net return →
What evidence would make a high return more credible?
Look for independently inspectable live results, a meaningful number of trades, transparent drawdown, clear fees, understandable leverage or amplification and a record long enough to include different market conditions. Screenshots and projected compound charts are not substitutes for live evidence.
Use the full result-verification checklist →
How to use a 20% assumption responsibly
Use it as a scenario for understanding mathematics, not as an expectation. Then stress-test weaker months and adverse moves before deciding whether the underlying risk is acceptable.
Model a 20% scenario in the Soniqe calculator →
Apply the framework to Sonic AI
If you are researching Sonic AI, compare any investor-level return scenario with the underlying public trading record, programme structure, fees and drawdown rather than assuming a historical average will repeat.