Arena Blog

A Bitcoin model published in August reaches $785,000 in 2030 at 60 % a year. Where its line stands today, what rate the target now needs, and why the same method would have given anything from $47,000 to $19 million.

"3 for 3" sounds like a perfect Bitcoin indicator until you ask: three out of how many? Pi Cycle, where the count is known, hit four tops and stayed silent at four others, the highest among them.

We pre-registered a Wyckoff spring backtest: rules locked first, 10 pairs, placebo control. The result is a clean nothing — and short-term even negative.

Look-ahead bias corrupts backtests when macro data is revised after the fact. Why we rebuilt our regime history to be strictly point-in-time — and proved it.

Daily backtests compute the signal from the close and fill at that same close — a price you can no longer trade. We recomputed 7,000+ trades twice (close fill vs. next open) to size the distortion. Result: smaller than the myth.

A backtest claiming a 100% win rate and 34 million percent returns is circulating. We're rebuilding it — and setting the rules before we compute.

The copper/gold ratio is sold as a macro and Bitcoin signal. What it actually measures, where it fails, and why a viral "Bitcoin cycle" indicator built on it has look-ahead bias.

Most traders writing their own backtests accidentally look into the future. The result: spectacular backtests, collapsing live performance. A look at the subtlest methodology mistake in systematic trading — from the common `shift(-N)` to the innocuous `.mean()` aggregation without rolling window — and why we manually check every Backtesting Arena strategy for bias before release.

A buy signal fires — but the unlock calendar says a large tranche of supply hits the market in nine days. Do you take the trade? Using Hyperliquid and the FDV debate as the case: what the FDV-to-market-cap ratio really means, what token unlocks empirically do to price — and the one point-in-time trap that quietly makes almost every retroactive test worthless.

TradingView is excellent for charting and visual analysis — but for the question whether a strategy systematically works across assets, it isn't built. Why fast, comparable backtesting requires a different class of tool.