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Plain-English explainers, deep dives, and backtest results on the SMA200 and adjacent trend-following topics. Everything written by a builder, not a guru.
Sector ETFs and the SMA200: which sectors give the cleanest signal
All sector ETFs are not created equal when it comes to the 200-day SMA filter. Technology (XLK) is the cleanest signal, with 179 cross events over 28 years; staples (XLP) and healthcare (XLV) are the whippiest, with 309 and 313 events respectively. The data behind why, and how to think about sector-rotation strategies using SMA200 as the gate.
Read article →How often does SPY actually cross its 200-day SMA? Thirty-three years of data
SPY has had 223 daily-close cross events against its 200-day SMA since January 1993. That's an average of 6.7 per year, but the rate varies wildly across decades. Most of those crosses are noise; only a handful per decade are real regime changes. The data, the methodology gotcha most retail traders skip, and which decades produced the cleanest signal.
Read article →What is the 200-day moving average? A 5-minute explainer
The 200-day moving average is the most-watched long-term trend indicator in equity markets. It's also the most-misunderstood, especially by readers new to technical concepts. The math in one sentence, what it signals, why institutional and retail traders both use it, and what it cannot do.
Read article →50-day vs 200-day moving average: which one is the actual trend filter
Both moving averages get traded as if they answer the same question. They don't. The 50-day captures short-term momentum and whipsaws often; the 200-day captures long-term regime and rarely false-signals. The framework you'd pick depends on which question you're actually asking, and most retail traders don't ask carefully enough.
Read article →Death cross vs golden cross: what they actually signal (and what they don't)
Both crosses get more airtime than they deserve. They're lagging regime labels, not predictions, and they're often confused with the much more frequent event of price simply crossing its own 200-day SMA. Forty years of SPY data, the famous false signals (2015, 2022), and what the framework actually says you should care about.
Read article →I open-sourced the synthetic-LETF return engine. It includes the borrow-cost fix.
If you have ever run a synthetic TQQQ backtest using the standard L * daily_return formula, your numbers are roughly 60% too high. sma200-bt is the corrected version, MIT-licensed, calibrated to within 5% of real TQQQ over 2015 to 2024. Install with pip, use it for any leverage and any underlying.
Read article →TLT has been below its 200-day SMA for 85 days. The 5-year analog set.
Long bonds tripped the SMA200 trend filter back in March and have not recovered. 85 calendar days below is the fifth-longest streak of the last five years; the longest was 648 days through the 2022 bond bear. Here is what the framework actually says to do, what the recent analogs look like, and why TLT trips this filter more often than equity ETFs do.
Read article →For Leveraged ETFs, the Underlying Matters More Than the Leverage
The conventional wisdom is 'use less leverage to reduce drawdown.' That's correct in isolation but wrong as a cross-product comparison. 27 years of synthetic-LETF backtests show 3x SPY (UPRO) with the SMA200 filter beats 2x QQQ (QLD) on both CAGR AND max drawdown. The underlying's tail-bear profile dominates the leverage level. Practical implication: pick underlying first, then size leverage.
Read article →The Semi Collapse Scenario: What the SMA200 Actually Does to TQQQ and SOXL if Semis Have Their Own Dotcom
Most TQQQ and SOXL holders are quietly comforting themselves with 'I'll use the SMA200 to bail if it cracks.' 27 years of synthetic backtests including the actual dotcom collapse show that escape plan works for UPRO (-67% max drawdown) but doesn't save TQQQ (-95%) or SOXL (-99%). The underlying's vol matters more than the filter when leverage is high.
Read article →The Third Defensive Bucket: Managed Futures as an Alternative to Cash and Gold
When the SMA200 trend filter says 'go flat' on your leveraged equity sleeve, the conventional defensive options are cash (boring), gold (good), or long bonds (broke in 2022). There's a third option most retail strategies don't consider: managed futures via DBMF. The 7-year data shows it adds +0.076 Sharpe over cash and delivers the best single-asset drawdown protection of any defensive bucket tested.
Read article →The Hidden Cost Every Leveraged-ETF Backtest Ignores
Most synthetic LETF backtests overstate returns by ~60% over 10 years. The bug is one missing term in the daily-return formula. This piece shows the calibration proof against real TQQQ, the corrected long-window numbers, and what the SMA200 trend filter actually does once leveraged ETFs are modeled honestly.
Read article →Why One Indicator Isn't Enough (and Why Three Tuned Indicators Aren't Better)
The SMA200 gives you a binary read on long-term trend. Useful, but incomplete. Most traders try to fix this by stacking RSI, MACD, and Bollinger bands until the chart is unreadable. There's a better way, and a walk-forward test reveals why most "tuned" confluence strategies are statistical noise dressed up as edge.
Read article →Does the 200-day Moving Average Actually Beat Buy-and-Hold?
A look at 16 years of data on QQQ, TQQQ, SOXL, UPRO comparing the simplest trend-filter rule against passive buy-and-hold. The answer is more interesting than either side wants to admit.
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