Public proof layer
Before you upload anything, see how a strategy can look healthy on the surface while hiding structural risk underneath.
This case study uses illustrative synthetic data. No client data, source code, private signals, exchange API keys, or live account access are used.
Case study
A dual moving average crossover strategy is simple, familiar, and easy to backtest. That makes it a good example for showing how a strategy can appear reasonable while still carrying hidden fragility.
The goal is not to prove that this strategy type is good or bad. The goal is to show how StratVitals reads risk fingerprints from strategy outputs before asking you to submit your own private material.
Failure findings
These findings are educational examples. They show what a first-layer diagnosis looks for in the outputs, not private strategy rules.
A strategy can show positive total PnL while relying heavily on a small number of outsized winners. If the top 3-5 trades explain most of the profit, the strategy may be less repeatable than the headline return suggests.
Example insight: Remove the top 5 winning trades, and the synthetic equity curve turns from profitable to nearly flat. That does not prove the strategy is invalid, but it changes the readiness question.
Trend-following logic often looks strong when the sample contains enough directional movement. The hidden problem appears when the same rules are tested separately in sideways or mean-reverting regimes.
Example insight: The strategy's positive results are concentrated in directional markets. In sideways periods, small losses, false entries, and delayed exits can compound into persistent fee drag.
A strategy that survives with zero-cost assumptions may fail after realistic fees and slippage. This is especially dangerous for higher-frequency systems or strategies that enter and exit during noisy market conditions.
Example insight: When realistic costs are added, many marginal trades stop contributing. The strategy still appears active, but the net edge becomes fragile.
If changing a moving average length from 20 to 21 sharply changes the result, the strategy may be fitted to historical noise rather than a robust market behavior.
Example insight: A robust strategy should not collapse because of a tiny parameter adjustment. Fragility does not automatically mean the strategy is unusable, but it does mean it needs stronger validation before capital is increased.
Max drawdown tells you how deep the pain became. Recovery time tells you how long the strategy stayed damaged. A system that needs a long time to recover may be psychologically and operationally harder to run than the headline numbers suggest.
Example insight: The synthetic strategy recovers eventually, but the recovery window is long enough that many traders would likely stop following it before the next favorable regime arrives.
Diagnosis summary
The conclusion is not "never trade it." The conclusion is: do not scale it until the hidden fragilities are understood, measured, and monitored.
No-upload checklist
No upload. No data collection. Just a quick diagnostic checklist.
Your answers are processed only in this browser session and are not submitted to StratVitals.
Answer the checklist items to see a visible fragility band. Your answers stay in this browser session.
Privacy reminder
StratVitals does not need your source code, exchange API keys, live account access, or proprietary signal formula for a first review. You can start with a redacted description and strategy outputs.
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