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Crypto trading strategy guides
Long-form guides on backtesting, walk-forward optimization, smart-order ladders, position sizing, and the rest of the quant toolbox — written for retail traders who want the boring truth instead of the marketing pitch.
Editor's pick
Read the complete guide to crypto trading strategies
The HalfTrend indicator, explained — and what its latch is actually worth, in numbers
HalfTrend's whole idea is refusing to flip until price proves it. We explain the latch mechanic, then measure what it buys you against Parabolic SAR and SuperTrend on 50 coins of real history — including the part none of them were fitted to.
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guide
Practical how-tos — sizing, exits, picking timeframes, building strategies end-to-end.
- guide·9 min read
Volatility targeting: how professional desks keep risk constant
Fixed dollar size ignores the obvious: a $10,000 position in BTC has 5× the dollar volatility of a $10,000 position in gold. Vol-targeting scales the position so the dollar risk stays constant — and it's how every serious systematic shop sizes trades.
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- guide·8 min read
How to backtest a strategy on Binance (fees, data, and pairs)
Backtesting for Binance means testing against Binance's real fees, real pairs, and real data — not a generic simulation. Here's how to make the test match the venue.
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- guide·7 min read
Trendlines, drawn properly: two-touch rule, slope, and why most are wrong
A trendline is the simplest tool on the chart and the easiest to lie with. Here is how to draw one that means something — and the discipline that keeps it from becoming a Rorschach test.
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- guide·8 min read
What timeframe should you trade? The honest answer
There is no best timeframe — but there is a best timeframe for you. The choice is a trade-off between noise, costs, and how much of your life trading will consume.
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- guide·8 min read
Diversification for traders: running many strategies, not many coins
Holding ten crypto assets that all crash together is not diversification. For an algo trader, real diversification comes from uncorrelated strategies — here's why.
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- guide·10 min read
Algorithmic trading strategies: the main types, honestly assessed
A tour of the strategy families retail algo traders actually use — what each one bets on, the market it needs, and how hard it really is to make work.
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concept
One idea per post — an indicator, a metric, or a piece of theory, unpacked clearly.
- concept·7 min read
Does the best backtest predict the future? We measured it 200 times
When you optimize a strategy and ship the best-Sharpe settings, you're betting the in-sample ranking of your parameters holds up out-of-sample. Across 200 strategy-coin grids, that ranking correlated just 0.37 with reality — and a quarter of the time it was no better than random.
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- concept·8 min read
Buy-and-hold vs trading crypto: what the data actually says
HODL maximalists quote the returns. Traders quote the drawdowns. Both are cherry-picking halves of the same dataset — so let's put the whole thing on the table.
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- concept·7 min read
How many trades does a backtest need before you can trust it?
Fifteen trades tell you almost nothing, no matter how many years they span. Here is the honest arithmetic of backtest sample sizes — and why trade count beats calendar length every time.
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- concept·7 min read
R-multiples: the only way to compare trades that actually scales
Was that +$80 trade good? You cannot tell from dollars alone. Expressed as R-multiples — units of initial risk — every trade gets the same currency, and your strategy's quality becomes measurable.
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- concept·6 min read
Heikin-Ashi candles: smoother charts, with one critical catch
Heikin-Ashi candles smooth out chart noise so trends jump off the screen. They make trend-following intuitive — and silently mislead anyone who treats the price they show as real.
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- concept·7 min read
Donchian channels: the breakout indicator the Turtles got rich on
Two lines — the N-bar high and the N-bar low — and a rule to enter on breakouts. That's a Donchian channel. The system trained the most famous prop-trading class in history. Here is how it works and where it breaks.
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deep dive
Long-form, opinionated pieces on what really kills retail strategies and how to survive.
- deep dive·6 min read
Parabolic SAR vs SuperTrend: 50 coins, five and a half years, one honest scoreboard
Both flip between long and short with a trailing line — but one of them trades four times as often. We ran both through the same engine on identical data, with fees, and scored the part of history neither was fitted to.
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- deep dive·8 min read
Which crypto strategy families survive out-of-sample? All 10, ranked
We tuned ten classic strategy families on twenty coins, then ran each tuned winner once on data it had never seen. Only two families kept a positive median edge. Here is the full ranking — including the three that were negative before fees even bit.
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- deep dive·6 min read
SuperTrend vs EMA crossover: we tested both on 50 coins so you don't have to argue about it
Two of the most popular trend-following systems, identical conditions, fifty crypto pairs, an out-of-sample honesty check — and a scoreboard that isn't close this month.
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- deep dive·10 min read
We ran 11,440 backtests. The average 'winning' strategy lost half its edge on data it had never seen
Ten classic strategy families, 5,720 parameter configurations, twenty crypto pairs, one honest rule: tune only on the past, then test once on data the strategy never saw. Here is exactly how much of 'backtested profitability' survived.
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- deep dive·11 min read
CPCV: the cross-validation method that catches overfitting walk-forward misses
Walk-forward optimisation gives you one out-of-sample equity curve. Combinatorial purged cross-validation gives you hundreds — and shows you the distribution of your strategy's true performance, not the lucky-path artefact.
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- deep dive·8 min read
Backtest data quality: the bad candles that fake an edge
Your backtest is only as honest as the candles you feed it. Bad ticks, gaps, and survivorship bias quietly fabricate edges — or hide real ones. Here's how to spot them.
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walkthrough
Step-by-step tours of the platform — features, screens, and the workflows behind them.
- walkthrough·8 min read
How to backtest an ATR strategy on crypto (stops and sizing that adapt)
ATR isn't an entry signal — it's a volatility measure. The right way to backtest it is as the engine behind your stops and position sizing. Here's how, step by step.
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- walkthrough·8 min read
How to backtest a Donchian breakout strategy on crypto
The channel breakout that powered the original Turtle traders is simple to state and easy to overfit. Here's how to backtest it honestly, from rules to walk-forward.
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- walkthrough·8 min read
How to backtest a VWAP strategy on crypto (filter, not trigger)
VWAP is a fair-value benchmark, so the strategies worth backtesting use it as a filter or a reversion reference — not a crossover signal. Here's how to test one honestly.
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- walkthrough·8 min read
Momentum trading strategy: how to backtest one on crypto
Momentum is the simplest edge in markets — buy what's going up — and one of the easiest to ruin by buying the exact top. Here's how to backtest it honestly.
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- walkthrough·8 min read
How to backtest an ADX trend-strength strategy on crypto
ADX measures how strong a trend is, not its direction. Learn to turn that into testable rules, run it on real crypto history, and validate the edge with walk-forward.
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- walkthrough·8 min read
How to backtest a Bollinger Bands strategy on crypto
Turn a Bollinger Bands idea — mean-reversion fade or volatility breakout — into testable rules, run it on real crypto history, and tell whether the edge holds up.
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