Arena Blog

Auditing 40,000 backtests, our Fibonacci strategy came up short. Before cutting it we asked: is it our config? A better exit made it 20 points better — and we retired it anyway. Why "beats Buy & Hold" isn't the bar.

We audited 40,000 of our own backtests — and benched several of our own strategies in the process. Here is what we killed, what we reactivated, and the uncomfortable core lesson: whether a strategy is "good" depends less on the strategy than on the asset class it runs in.

A thesis says trading platforms are going "agentic" — AI monitors, signals, executes. The structural part is right. The blind spot sits where money is lost.

A chart claims to "prove" liquidity leads crypto. The thesis is serious — the chart isn't proof. What it shows, what it doesn't, and how to test it honestly.

Five weeks ago it was 10,000 backtests; today it's over 40,000. With 4x the data, the "beats Buy & Hold" rate falls from 64% to 52%, four in five runs land below 50% win rate, and one memecoin still holds its 197,923% record. What selection bias does to sample size — on real numbers.

A smart-money indicator paints clean zones that price seems to respect. Backtest it honestly and the magic fades. The reason is mechanical — repainting and vanished losers — not your skill.

We ran the same RSI/SMA crossover across the top 50 coins and the top 50 US stocks — identical rules, identical window. On crypto it beats the buy-and-hold benchmark 80 % of the time; on stocks, 4 %. Why a trend-following strategy works in one market and bleeds in the other.

"Price gaps always fill" is a myth. What the evidence actually shows — for stock gaps, and for the CME gap, which became history in May 2026.

Dual Momentum supposedly beats Buy & Hold on return AND drawdown. Our GTAA-5 backtest (2007–2026) says otherwise: not on return — but clearly on drawdown.

The 200-day line is the most-cited trend filter in markets: invested above it, out below it. We tested it as a standalone strategy across 110 assets. The result is not one-size-fits-all — on crypto it beats Buy & Hold on return AND drawdown AND Sharpe; on index ETFs it gives up almost no return while nearly halving the drawdown; on single stocks it works poorly. An honest map of where regime timing pays and where it doesn't.

RSI(2) mean reversion, honestly backtested (2018–2026): on stocks it loses badly to buy & hold; on crypto it wins — for an uncomfortable reason.

Most people don't trade out of greed but out of fear — cash bleeds in silence. That necessity feeds an industry built to drain those traders. Why the only durable defense is learning to verify.