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    <title>EdgeLab — systematic trading research</title>
    <link>https://edgelabtrading.com/</link>
    <description>Honest, tested systematic trading strategies — rules, backtests and code.</description>
    <language>en</language>
    <item>
      <title>SPY vs QQQ vs gold vs bitcoin: the best asset, risk-adjusted</title>
      <link>https://edgelabtrading.com/blog/best-asset-risk-adjusted/</link>
      <guid>https://edgelabtrading.com/blog/best-asset-risk-adjusted/</guid>
      <pubDate>Wed, 08 Jul 2026 09:00:00 +0000</pubDate>
      <description>Stocks, gold, bonds and bitcoin over 11 years, ranked honestly. Bitcoin won on raw return — with an -83% drawdown and a -74% year. But an equal-weight mix of all five beat every single one on risk-adjusted return. Why chasing the winner is the wrong lesson.</description>
    </item>
    <item>
      <title>Does the 200-day moving average work? Tested on five assets</title>
      <link>https://edgelabtrading.com/blog/200-day-moving-average/</link>
      <guid>https://edgelabtrading.com/blog/200-day-moving-average/</guid>
      <pubDate>Wed, 08 Jul 2026 09:00:00 +0000</pubDate>
      <description>The most-watched line in trading, run as a hold-or-cash filter on stocks, gold, bonds and bitcoin. It roughly halves stock drawdowns and lifts risk-adjusted return — but turns bonds' +3.1% into -0.2%. A drawdown tool, not a return booster, and only where it fits.</description>
    </item>
    <item>
      <title>Does "sell in May and go away" work? 33 years of SPY, tested</title>
      <link>https://edgelabtrading.com/blog/sell-in-may/</link>
      <guid>https://edgelabtrading.com/blog/sell-in-may/</guid>
      <pubDate>Wed, 08 Jul 2026 09:00:00 +0000</pubDate>
      <description>The summer slump is real — over 33 years, winter beat summer in 5 of 6 five-year blocks. But going to cash each May still returned 6.7% a year versus 10.8% for buy-and-hold, with a worse Sharpe. A real pattern that isn't a tradable edge — and the least-bad version.</description>
    </item>
    <item>
      <title>When is a strategy dead? Three statistical tripwires we use</title>
      <link>https://edgelabtrading.com/blog/strategy-dead-tripwires/</link>
      <guid>https://edgelabtrading.com/blog/strategy-dead-tripwires/</guid>
      <pubDate>Mon, 06 Jul 2026 09:00:00 +0000</pubDate>
      <description>Telling a normal bad patch from a genuinely broken edge — before it drains the account. Three tripwires you pre-commit and check live: a sustained rolling-Sharpe breach, a drawdown past its Monte Carlo envelope, and a shift in the trade distribution. Worked on a real 23-year record.</description>
    </item>
    <item>
      <title>Prop firm math: why the daily loss limit matters more than the profit target</title>
      <link>https://edgelabtrading.com/blog/prop-firm-daily-loss-limit/</link>
      <guid>https://edgelabtrading.com/blog/prop-firm-daily-loss-limit/</guid>
      <pubDate>Mon, 06 Jul 2026 09:00:00 +0000</pubDate>
      <description>Three strategy types, 23 years, one prop-rule simulator. The profit target is the number everyone watches — the daily loss limit is the one that decides. And the killer isn't even the same across strategies: dip-buyers die fast to the daily rule, trend dies slow to the total rule.</description>
    </item>
    <item>
      <title>The Strategy Graveyard: we stress-tested 150+ trading strategies — most didn't survive</title>
      <link>https://edgelabtrading.com/blog/strategy-graveyard/</link>
      <guid>https://edgelabtrading.com/blog/strategy-graveyard/</guid>
      <pubDate>Mon, 06 Jul 2026 09:00:00 +0000</pubDate>
      <description>One identical out-of-sample, walk-forward, real-cost bar. Few strategies cleared it — but most didn't die, they were edges we already owned or that need institutional scale. The honest breakdown, and why a stack of OK uncorrelated strategies beats the hunt for a perfect one.</description>
    </item>
    <item>
      <title>Your worst drawdown is still ahead of you: 10,000 Monte Carlo reshuffles</title>
      <link>https://edgelabtrading.com/blog/monte-carlo-drawdown/</link>
      <guid>https://edgelabtrading.com/blog/monte-carlo-drawdown/</guid>
      <pubDate>Mon, 06 Jul 2026 09:00:00 +0000</pubDate>
      <description>We shuffled 410 real trades 10,000 times. Same trades, same profit — but history's -11.3% max drawdown turns out to be the lucky draw: 95% of reorderings go deeper, and a new all-time-worst within ten years is more likely than not.</description>
    </item>
    <item>
      <title>Toby Crabel's NR7 breakout, tested on stocks, gold and bitcoin — 1,850 trades</title>
      <link>https://edgelabtrading.com/blog/nr7-breakout/</link>
      <guid>https://edgelabtrading.com/blog/nr7-breakout/</guid>
      <pubDate>Sat, 04 Jul 2026 09:00:00 +0000</pubDate>
      <description>A 36-year-old pattern run with identical rules on four assets, net of costs. On stocks alone it loses to buy-and-hold — across three uncorrelated markets it becomes a Sharpe-1.45 book with a -12.4% worst drawdown.</description>
    </item>
    <item>
      <title>The RSI 30/40 strategy: buy the Nasdaq at 30, sell at 40 — every trade from 23 years</title>
      <link>https://edgelabtrading.com/blog/rsi-strategy-nasdaq/</link>
      <guid>https://edgelabtrading.com/blog/rsi-strategy-nasdaq/</guid>
      <pubDate>Fri, 03 Jul 2026 09:00:00 +0000</pubDate>
      <description>The strategy from the video, tested honestly: 32 signals since 2003, 28 winners, every trade listed one by one — plus the faster RSI(2) variant and the honest math of what each earns.</description>
    </item>
    <item>
      <title>Buying the dip in QQQ: 23 years of evidence, net of costs</title>
      <link>https://edgelabtrading.com/blog/qqq-dip-buying/</link>
      <guid>https://edgelabtrading.com/blog/qqq-dip-buying/</guid>
      <pubDate>Fri, 12 Jun 2026 09:00:00 +0000</pubDate>
      <description>Twenty rule combinations, no cherry-picking: the dip-buying edge is real, robust across settings, and persistent across two decades. It still doesn't do what the meme says it does.</description>
    </item>
    <item>
      <title>How many trading strategies do you need? The portfolio math</title>
      <link>https://edgelabtrading.com/blog/how-many-strategies/</link>
      <guid>https://edgelabtrading.com/blog/how-many-strategies/</guid>
      <pubDate>Fri, 12 Jun 2026 09:00:00 +0000</pubDate>
      <description>One formula decides it, and correlation is the variable that matters. Theory said our two-strategy combo should land at Sharpe 1.04 — the market paid 1.02. The full math, plus the trap that ruins most multi-strategy portfolios.</description>
    </item>
    <item>
      <title>Can a mechanical strategy pass an FTMO challenge? We ran 5,600 of them</title>
      <link>https://edgelabtrading.com/blog/ftmo-challenge-systematic-strategy/</link>
      <guid>https://edgelabtrading.com/blog/ftmo-challenge-systematic-strategy/</guid>
      <pubDate>Fri, 12 Jun 2026 09:00:00 +0000</pubDate>
      <description>62% pass at honest size — but the median pass took 357 trading days, and sizing up feeds the daily-loss rule. The simulation prop firm content never runs.</description>
    </item>
    <item>
      <title>Darwinex Zero for systematic traders: the platform that pays for Sharpe</title>
      <link>https://edgelabtrading.com/blog/darwinex-zero-systematic/</link>
      <guid>https://edgelabtrading.com/blog/darwinex-zero-systematic/</guid>
      <pubDate>Fri, 12 Jun 2026 09:00:00 +0000</pubDate>
      <description>Not another affiliate review — I trade there. How the VaR engine turns risk-adjusted return into the only metric, the honest breakeven on €45/month, and who should pick a prop firm instead.</description>
    </item>
    <item>
      <title>Are paid trading strategies worth it? A buyer's checklist from someone who sells them</title>
      <link>https://edgelabtrading.com/blog/are-paid-trading-strategies-worth-it/</link>
      <guid>https://edgelabtrading.com/blog/are-paid-trading-strategies-worth-it/</guid>
      <pubDate>Fri, 12 Jun 2026 09:00:00 +0000</pubDate>
      <description>Most aren't. A minority are — and the difference is checkable before you pay. Five questions, the red flags that end the conversation, and the chart that explains most bad purchases.</description>
    </item>
    <item>
      <title>ETF momentum rotation: rules, 21 years of data — and an honest verdict</title>
      <link>https://edgelabtrading.com/blog/etf-momentum-rotation/</link>
      <guid>https://edgelabtrading.com/blog/etf-momentum-rotation/</guid>
      <pubDate>Thu, 11 Jun 2026 09:00:00 +0000</pubDate>
      <description>One decision a month across stocks, bonds and gold. 10.9% CAGR out-of-sample — but the boring benchmark beat it risk-adjusted, and every "improvement" we tested just snuck the portfolio back toward buy-and-hold.</description>
    </item>
    <item>
      <title>The Friday gold effect: a real pattern you probably can't trade</title>
      <link>https://edgelabtrading.com/blog/friday-gold-strategy/</link>
      <guid>https://edgelabtrading.com/blog/friday-gold-strategy/</guid>
      <pubDate>Thu, 11 Jun 2026 09:00:00 +0000</pubDate>
      <description>Friday is 12x better than Monday in gold — half of all daily gains on one weekday. Costs eat the naive version. One VIX-filtered variant survives as a satellite trade — I run it myself, and the exact rules are in the article.</description>
    </item>
    <item>
      <title>The Turnaround Tuesday strategy — rules and 23 years of backtest data</title>
      <link>https://edgelabtrading.com/blog/turnaround-tuesday/</link>
      <guid>https://edgelabtrading.com/blog/turnaround-tuesday/</guid>
      <pubDate>Tue, 10 Mar 2026 09:00:00 +0000</pubDate>
      <description>Two rules, no indicators. 81% win rate out-of-sample and under 20% time in the market. Full rules, equity curves, SPY validation — and the honest caveats.</description>
    </item>
    <item>
      <title>Why your backtest passes — and your live account doesn't</title>
      <link>https://edgelabtrading.com/blog/why-backtests-fail/</link>
      <guid>https://edgelabtrading.com/blog/why-backtests-fail/</guid>
      <pubDate>Tue, 10 Mar 2026 09:00:00 +0000</pubDate>
      <description>We optimized 2,160 parameter combinations to build the perfect backtest, then watched it fall apart on data it had never seen. Out-of-sample testing is the filter that catches it.</description>
    </item>
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