Learn Trading.
No Hype. Real Data.

Everything you need to know about crypto perpetual futures. How leverage works, what funding rates are, and how to avoid getting liquidated.

A complete breakdown of crypto trading fees. Maker vs taker, funding rates, withdrawal fees, and how to cut your costs by 40% or more.

A practical guide to backtesting crypto trading strategies. Learn to avoid look-ahead bias, overfitting, and the common mistakes that make 90% of backtests worthless.

A practical guide to detecting volatility compression and expansion in crypto futures. No hype, just mechanics.

PRUVIQ was born from frustration with crypto's 'trust me bro' culture. The name is a challenge: Prove It. Here's how it started.

Position sizing, stop losses, and why managing risk matters more than finding the perfect entry. Practical guide for futures traders.

How Fibonacci levels work in crypto trading, why traders believe in them, and what backtesting actually shows about their effectiveness.

A data-driven look at candlestick patterns. Classic patterns like doji, hammer, and engulfing — do they predict crypto price moves?

How ATR works, why it's essential for position sizing and stop-loss placement, and how to use it in crypto trading strategies.

How the Ichimoku Cloud works, what each line means, and why this all-in-one indicator struggles in fast-moving crypto markets.

How support and resistance actually work, methods to identify them, and why most traders draw them wrong. Practical guide for crypto.

What VWAP is, how institutions use it, and why it matters even in decentralized crypto markets. Practical guide with backtest context.

Everything you need to know about EMA crossovers in crypto. Why everyone uses them, why most lose money with them, and how to actually make them work.

A no-nonsense guide to MACD in crypto futures. How it works, when to trust it, and how to combine it with other indicators in backtesting.

Practical guide to RSI (Relative Strength Index) in crypto futures. When it works, when it lies, and how to backtest it on 535+ coins.

The data-driven process behind choosing SL 10% and TP 8%. Why most traders set their stops wrong, and how backtesting 2,898 trades revealed the optimal ratio.

How to use Stochastic Oscillator and ADX together in crypto trading. Two indicators that answer different questions — and when to use each.

Why volume matters more than price in crypto futures. How to use volume ratio, volume SMA, and volume z-score to filter real moves from fakeouts.

A step-by-step guide to reducing your Binance Futures trading fees by 20%. Lower fees compound into real money over time.

We ran the same strategies in both directions across 50 coins for 365 days. SHORT dominated, but the last 30 days tell a different story. Here's the data.

BB Squeeze SHORT strategy backtested with 3% and 10% stop loss across 50 coins over 2+ years. The tighter stop lost more trades but the wider stop made more money.

1-year backtest results across 52 crypto trading strategies on 572 coins. Raw numbers: win rates, profit factors, drawdowns, and which strategies actually survived.

Profit Factor is the single most useful number in a backtest report. Learn what PF means, what counts as strong vs marginal, and how to use it in PRUVIQ rankings.

Look-ahead bias, overfitting, and out-of-sample testing explained. Why great backtest numbers frequently fail in live markets — and how PRUVIQ addresses each problem.

BTC dropped 48% from ATH. 311K traders got liquidated in one day. Our SHORT-only system ran through it all. Here's what actually happened.

A practical guide to backtesting crypto trading strategies. Learn to avoid look-ahead bias, overfitting, and the common mistakes that make 90% of backtests worthless.

How to calculate optimal position size using Kelly Criterion. Practical guide with real trading examples and the math behind bankroll management.

10 expert agents analyzed our TP change. 7 said GO, 1 said WAIT, 2 had invalid methodology. Here's exactly how we made the call — with all the data.

Look-ahead bias, overfitting, and the gap between backtested +2000% and live -30%. How to spot fake results.