Arena Blog
Data-driven insights on trading strategies, backtests, and market analysis.
1–12 of 38 posts · page 1 of 4
The Strategy Library: Not a Leaderboard, a Toolbox
25+ strategies, and the honest question is never "which is best?" It's: which fits what, and when? Four truths that run through the whole library — timeframe decides, "beats B&H" often means losing less, win rate isn't profit, and fit beats breadth.
The 200-Week Moving Average and Young Coins: Why the Obvious Fix Backfires
Young coins without 200 weeks of history skip the 200-week filter automatically. We tested the obvious fix across 207 coins — it made everything worse.
Bitcoin's Liquidity Fair Value: Why the Model Fails the Test
The Bitcoin liquidity fair value chart shows R²=0.85 — and claims BTC is "348% above fair value". We ran the cointegration test. It fails.
A Backtest With a 100% Win Rate: We're Testing It — Rules Set Before We Compute
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.
Opening Range Breakout: Real Strategy, Oversold Story
ORB is sold as the holy grail of intraday trading. What the strategy really is, why the viral result misleads, and what makes or breaks an honest ORB backtest.
Filters: A Regime Gate Is Not a Magic Switch
A filter that rescues one strategy can strangle the next. We ran 189 filter combinations on crypto — and exactly one survives the strictest overfitting test. What that reveals about the 200 WMA, ATR, Altcoin Season and the Bullmarket gauge.
Triple Strike Reversal — A Strategy Not Made to Stand Alone
Most trading strategies are sold to you as complete solutions. "Run this system, make money." Enter signal. Exit signal. Repeat. Base rate win percentages plastered across the landing page.
When Fees Kill a Strategy: Why We Benched Our Second-Most-Popular One
Our backtest engine used to compute returns before costs. We built a net-of-cost layer that re-prices every fill at a realistic fee — and it flipped our second-most-popular strategy negative after fees. Here is the math, the numbers, and why "beats buy-and-hold" is half a truth until you pay the fees.
We Rebuilt Our Worst Strategy Correctly — It Worked — and Cut It Anyway
Our Bollinger Squeeze strategy lost to Buy & Hold by double digits on crypto. Before deleting it, we rebuilt it to the modern standard (TTM Squeeze). The rebuild turned positive — and we retired it anyway. Why "it works now" isn't enough.
We Fixed Our Fibonacci Strategy — and Retired It Anyway
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.
Why SMC Indicators Look Better Than They Backtest
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.
Why the same strategy crushes crypto and bombs the S&P 500
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.
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