BasicsIntroductory
The trader's equation: win rate, risk, and reward
The expected-value equation behind every trade and why nearly every strategy decision is downstream of it.
8 min readRead article
Edgecraft Learning Hub
Understand your strategy. Not just the results.
Explore practical explanations, guides and reference material for building, testing and evaluating crypto trading strategies under real market conditions.
Browse by category
Basics
Essential concepts for building and testing rule-based trading strategies.
6 articlesExplore Basics
Foundations
Core principles behind realistic testing, validation, risk and robust performance.
12 articlesExplore Foundations
Guides
Practical, step-by-step guidance for building, testing and improving strategies.
0 articlesExplore Guides
Reference
Clear explanations of the metrics, methods and terminology used in strategy analysis.
0 articlesExplore Reference
Start here
Build a stronger understanding of how strategies are designed, tested and evaluated.
BasicsIntroductory
Realistic expectations: what systematic trading can and cannot do
Calibrating what a real edge looks like, and why expectations — not signals — end most accounts.
8 min readRead article
FoundationsIntroductory
Building a strategy: what to decide before you write a single rule
The four parts of a complete strategy — entry, exit, regime and sizing — and the traps that catch most retail builds.
8 min readRead article
FoundationsIntroductory
Realistic backtesting: the costs that kill paper edges
Why the curve in a standard backtester is fiction: fees, funding, slippage, partial fills and latency, and how to model them honestly.
9 min readRead article
Browse all topics
Filter by category, or search below to jump straight to the concept, metric or workflow you need.
18 articles available
Basics
Essential concepts for building and testing rule-based trading strategies.
BasicsIntroductory
How crypto markets work: order books, spreads, and order types
How the order-book auction works: bids, asks, the spread as a real cost, and the order types every systematic trader needs to know.
8 min readRead article
BasicsIntroductory
Spot vs. perpetual futures: funding, margin, and liquidation
What a perpetual future actually is and how funding, margin and liquidation work in practice.
9 min readRead article
BasicsIntroductory
Trading styles: scalping, day trading, swing, position, and market-making
How holding time decides costs, required win rate, and whether a style is viable for a retail systematic trader.
9 min readRead article
BasicsIntroductory
The trader's equation: win rate, risk, and reward
The expected-value equation behind every trade and why nearly every strategy decision is downstream of it.
8 min readRead article
BasicsIntroductory
Realistic expectations: what systematic trading can and cannot do
Calibrating what a real edge looks like, and why expectations — not signals — end most accounts.
8 min readRead article
BasicsIntroductory
The psychology of running a system
Automation removes some bad habits and creates new ones. The discipline needed to keep a system running.
8 min readRead article
Foundations
Core principles behind realistic testing, validation, risk and robust performance.
FoundationsIntroductory
Building a strategy: what to decide before you write a single rule
The four parts of a complete strategy — entry, exit, regime and sizing — and the traps that catch most retail builds.
8 min readRead article
FoundationsIntroductory
Risk: what actually ends trading accounts
Risk is not volatility. Drawdown, ruin, correlated risk, leverage and tail risk — the things that actually end accounts.
9 min readRead article
FoundationsIntroductory
Realistic backtesting: the costs that kill paper edges
Why the curve in a standard backtester is fiction: fees, funding, slippage, partial fills and latency, and how to model them honestly.
9 min readRead article
FoundationsIntroductory
Overfitting: how good-looking numbers lie
The most common reason backtests succeed and live trading fails — how to detect overfitting and defend against it.
9 min readRead article
FoundationsIntermediate
Out-of-sample testing: protecting yourself from luck
Splitting train and test, walk-forward, and why crypto needs longer windows than equities to mean anything.
9 min readRead article
FoundationsIntermediate
Optimization: what it is worth and when it hurts
What optimization can and cannot do, and how to avoid the data-mining trap that turns a fine strategy into a fragile one.
8 min readRead article
FoundationsIntermediate
Statistical tools: what each metric tells you and what each hides
Sharpe, Sortino, Calmar, profit factor, win rate, expectancy, max drawdown — what each measures and what each conceals.
10 min readRead article
FoundationsIntermediate
Market regimes: why one strategy cannot fit all markets
Trending, ranging, high-volatility and low-volatility regimes pay different strategies. How to read a backtest with regime eyes.
8 min readRead article
FoundationsIntermediate
Strategy decay: every edge dies, and how to notice early
Why edges erode — crowding, regime change, structural shifts — and how to tell decay from normal noise before it eats an account.
9 min readRead article
FoundationsIntermediate
Multi-objective optimization and Pareto frontiers
Why optimizing one metric overfits, and how Pareto frontiers reveal the trade-offs between Sharpe, drawdown, trade count and robustness.
8 min readRead article
FoundationsIntroductory
The live headwind: how costs eat a paper edge, line by line
A line-by-line worked example of how fees, spread, slippage, funding, missed fills and a liquidation event reduce a strong paper return to a marginal live one.
9 min readRead article
FoundationsIntroductory
Why one pair is not proof: single-market backtests and selection bias
Why a single-pair backtest is just one sample, how pair-shopping manufactures fake edges, and what cross-asset validation actually tells you.
8 min readRead article
Guides
Practical, step-by-step guidance for building, testing and improving strategies.
Articles in this category are being written. Check back as the Learning Hub grows.
Reference
Clear explanations of the metrics, methods and terminology used in strategy analysis.
Articles in this category are being written. Check back as the Learning Hub grows.
Put the principles into practice
Edgecraft is being built to help traders create, test and investigate strategies using realistic market assumptions and evidence-led analysis.