TRADING IQ
Raise Your Trading IQ.
Learn what works. See what doesn't. Backtesting methodology, risk management, and lessons from 230 coins and 88 parameter variations.
We Ran 52 Strategies for 1 Year. Here's the Data.
1-year backtest results across 52 crypto trading strategies on 572 coins. Raw numbers: win rates, profit factors, drawdowns, and which strategies actually survived.
Strategy Autopsy: Momentum Long
Why Momentum Long lost money — data-driven analysis on 50 coins over 2+ years.
How MACD Cross Strategy Works in Crypto
A practical guide to MACD crossover signals: what they measure, when they generate entries, and how to read them inside the PRUVIQ simulator.
Understanding Profit Factor in Backtesting
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.
Why Backtesting Alone Isn't Enough
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.
Order Types & Execution Strategies for Crypto Traders: Minimize Slippage and Improve Fills
Practical guide to order types (market, limit, IOC/FOK, stop orders) and execution strategies (laddering, TWAP/VWAP, post-only) with examples and backtest-friendly simulations to reduce slippage and costs.
Funding Rate Arbitrage: A Practical Guide for Perpetual Futures Traders
Understand how funding rates work, step-by-step funding-rate capture strategies, an illustrated arbitrage example with fees and risks, and an execution checklist.
How to Use PRUVIQ's Strategy Builder: A Step-by-Step Guide
Design, backtest, and iterate no-code crypto trading strategies using PRUVIQ's Strategy Builder. Practical workflow, examples, and robustness checks to move from idea to conviction.
ATR (Average True Range): Measuring Volatility That Matters
How ATR works, why it's essential for position sizing and stop-loss placement, and how to use it in crypto trading strategies.
Candlestick Patterns: Which Ones Actually Work in Crypto?
A data-driven look at candlestick patterns. Classic patterns like doji, hammer, and engulfing — do they predict crypto price moves?
Fibonacci Retracement: Math, Myth, and Market Reality
How Fibonacci levels work in crypto trading, why traders believe in them, and what backtesting actually shows about their effectiveness.
Ichimoku Cloud: The Complete Indicator (and Its Limits in Crypto)
How the Ichimoku Cloud works, what each line means, and why this all-in-one indicator struggles in fast-moving crypto markets.
Support and Resistance: The Foundation of Every Trading Strategy
How support and resistance actually work, methods to identify them, and why most traders draw them wrong. Practical guide for crypto.
VWAP: The Institutional Benchmark That Crypto Traders Overlook
What VWAP is, how institutions use it, and why it matters even in decentralized crypto markets. Practical guide with backtest context.
EMA Crossover Strategy: Why It Often Fails in Crypto
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.
MACD Explained: Crossovers, Divergence, and What Actually Works
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.
RSI: How to Use Oversold and Overbought Signals in Crypto
Practical guide to RSI (Relative Strength Index) in crypto futures. When it works, when it lies, and how to backtest it on 230+ coins.
SL/TP Optimization: Finding the Right Stop-Loss Ratio
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.
Stochastic + ADX: Measuring Momentum and Trend Strength
How to use Stochastic Oscillator and ADX together in crypto trading. Two indicators that answer different questions — and when to use each.
Volume Analysis: The One Indicator Most Traders Ignore
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.