Blog
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
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.
Read →
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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
concept
One idea per post — an indicator, a metric, or a piece of theory, unpacked clearly.
- 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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
- concept·6 min read
Bid-ask spread: the cost everyone pays and most traders ignore
Every trade has a hidden tax that gets paid the moment you cross the spread. On low-volume strategies it's negligible; on anything frequent, it's the single largest cost — and most retail backtests pretend it doesn't exist.
Read →
- concept·8 min read
Market regimes: why your strategy works until it doesn't
Most strategies don't break — the market changes underneath them. Trending and ranging regimes reward opposite rules, and knowing which you're in is half the battle.
Read →
deep dive
Long-form, opinionated pieces on what really kills retail strategies and how to survive.
- 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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
- deep dive·9 min read
How to read your Sharpe ratio (and when it lies)
Sharpe is the most-quoted risk-adjusted metric in trading — and one of the most misread. Here's what it actually measures, what counts as good, and how it fools people.
Read →
- deep dive·8 min read
Look-ahead bias: the silent backtest killer (with examples)
Look-ahead bias doesn't look like a bug — it just makes your backtest better. That's what makes it so dangerous. Here are the ways it sneaks in and how to catch it.
Read →
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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
- 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.
Read →
Ready to put the theory to work?
Spin up a backtest, build a strategy in the designer, or read the docs. The free tier doesn't expire.