That Viral Strategy Dashboard Probably Won’t Survive a Real Backtest

A strategy dashboard made the rounds recently claiming +124R over a few months, a 61% win rate, a profit factor above 2, and a maximum drawdown of about six points of R. The equity curve was a nearly straight line. We rebuilt the strategy rule-for-rule and ran it through an honest backtest. The result: a profit factor of 0.86 — a losing system.

How a losing strategy produces a beautiful dashboard

• No transaction costs. Fast index futures strategies live or die on slippage. A backtest with perfect fills flatters every entry, and short-hold systems get flattered the most.
• Cherry-picked conditions. The dashboard highlighted its “best hours.” When we tested exactly those hours, they performed worse than the rest — the classic signature of parameters selected after seeing the results.
• An implausibly smooth equity curve. Real strategies breathe: they have losing weeks and flat months. A max drawdown of 6R against 124R of profit is not a sign of genius; it is a sign the curve was built by fitting to the data it is drawn on.

The checklist we run before believing any result

1. Reproduce it faithfully. Code the exact published rules — not your improved version — and confirm you get their trade count and win rate before you judge anything.
2. Charge for every trade. Slippage on entry and exit plus commissions, scaled to the instrument. If the edge dies here, it was never an edge.
3. Stretch the window. Anything under six months of data is a regime bet. Run a full year minimum, through both trend and chop.
4. Test the claimed filters out-of-sample. If the “best conditions” only work in the sample they were discovered in, they are noise.
5. Check the loss geometry. High win rates with small targets and wide stops hide rare catastrophic losses that a short backtest may simply never have hit.

The uncomfortable takeaway

Most shared strategies are not lies; they are honest overfitting. The author really did see those numbers — on the data the rules were tuned on, without costs. That is why we publish failures alongside winners here: the failure rate is the base rate. When something does survive slippage, a year of data, and out-of-sample checks, that survival means something. Everything else is a screenshot.