Traderizz guides
Backtesting & journal guides for better practice & review
Practical tutorials on free backtesting, P&L, R-multiples, expectancy, risk-reward, setup analytics, liquidity, and building a review habit.
36 guides
- Foundations
What Is R-Multiple Trading? A Practical Guide
R-multiples normalize every trade by risk so you can compare setups fairly and measure true edge.
- Analytics
How to Calculate Trading Expectancy (Step by Step)
Expectancy tells you the average R per trade — the number that predicts whether your system pays over time.
- Getting started
How to Start a Trading Journal (That You Will Actually Use)
A journal works when logging takes minutes and review answers one question: did I follow my edge?
- Process
Weekly Trade Review: A 30-Minute Routine for Traders
Thirty focused minutes beats hours of chart replay. Here is a repeatable weekly review checklist.
- Analytics
Win Rate vs Expectancy: What Actually Predicts Profit
A 40% win rate can outperform 75% if average wins in R are larger than average losses. Here is why.
- Broker import
How to Import Delta Exchange & Shark Exchange Trades into a Trading Journal
Stop rebuilding history by hand. Connect Delta or Shark, import fills into a journal, then review expectancy in R.
- Process
How to Journal Losing Trades (Without Repeating Them)
Losers teach more than winners — if you log them honestly. Here is how to review losses in R without spiraling.
- Trading diary
Trading Diary Calendar: How to Review Every Trading Session
A trade list shows what happened. A calendar shows when your behavior changes. Use daily R and session notes to find patterns hidden between individual trades.
- Analytics
Trade Tags & Setup Analytics: Find Which Trading Strategy Has an Edge
Your overall P&L can hide one strong setup and three expensive habits. Tag trades consistently, then compare count, expectancy, total R, and execution quality.
- Risk management
What Is Negative Risk-Reward Trading? Can a Low RR Strategy Work?
Risking more than the planned reward is not automatically a bad strategy. The real test is whether win rate, realized payoff, fees, and discipline produce positive expectancy.
- Analytics
High Win Rate vs High Risk-Reward: How Their Equity Curves Differ
One strategy climbs through frequent small wins and sudden drops. Another absorbs long flat periods before large jumps. Both can have the same expectancy—and feel completely different.
- Market structure
What Is Liquidity in Trading? A Practical Guide for Traders
Liquidity is the ability to trade near the expected price without moving the market too much. Here is how to recognize it, measure it, and journal its effect.
- Trading strategies
Liquidity Sweep Trading Strategy: Rules, Examples & Mistakes
A liquidity sweep is not simply a wick beyond a high or low. Turn the idea into objective rules, defined risk, and a sample you can test.
- Trading psychology
How to Stop Overtrading: Causes, Warning Signs & a Reset Plan
Overtrading is not defined by a universal trade count. It begins when activity exceeds your written edge. Diagnose the trigger, measure the cost, and install a rule that can be enforced.
- Trading psychology
How to Stop Revenge Trading After a Loss
Revenge trading begins when recovering a loss becomes more important than executing a valid setup. Use a pre-committed interruption plan before the next loss happens.
- Trading psychology
How to Stop FOMO Trading and Chasing Entries
FOMO turns a missed opportunity into a low-quality late entry. Diagnose the trigger, define when an entry is too late, and make skipping measurable.
- Risk management
Why Traders Move Stop Losses—and How to Stop
Moving a stop to avoid being wrong changes both the trade and the risk model. Separate valid trade management from emotional stop widening.
- Trading strategies
What Is a Trading Strategy Probability Tree?
Every trade is one branch in a larger distribution. A probability tree shows why changing strategy after each outcome destroys the sample you need to judge an edge.
- Trading analytics
How Many Trades Do You Need to Test a Trading Strategy?
There is no magic sample size. The number of trades you need depends on payoff variance, win rate, execution consistency, and the decision you want to make.
- Trading analytics
What Is Profit Factor in Trading? Formula, Examples, and Limits
Profit factor compares gross trading profits with gross trading losses. It is useful—but only when you also inspect sample size, costs, outliers, and drawdown.
- Risk management
Maximum Drawdown in Trading: Meaning, Formula, and Recovery
Maximum drawdown measures the largest peak-to-trough decline in an equity curve. It shows downside severity that profit, win rate, and expectancy can hide.
- Risk management
Risk-Reward Ratio in Trading: Formula, Examples, and Limits
Risk-reward ratio compares what a trade can lose with what it is planned to make. It is simple to calculate—and meaningless until you pair it with win rate, costs, and realized results.
- Trading analytics
Breakeven Win Rate: Formula, Examples, and What It Really Assumes
The breakeven win rate is the hit rate at which a strategy neither gains nor loses. It is simple to compute for fixed outcomes—and easy to misuse the moment your wins and losses vary in size.
- Risk management
Position Sizing in Trading: Formula, Examples, and Risk
Position sizing converts a predefined risk amount and stop distance into a trade quantity. The arithmetic is simple, but contract specifications, costs, gaps, and correlated exposure matter.
- Trading analytics
How to Backtest a Trading Strategy: A Step-by-Step Guide
A credible backtest applies rules consistently to historical data, includes realistic trading costs, protects unseen data, and records every decision for review.
- Process
Trading Plan Template: How to Write a Plan You Can Follow
A trading plan is a written decision set you create before the market opens, so execution becomes checking rules instead of forming opinions under pressure.
- Trading strategies
Smart Money Concepts (SMC) Trading: A Practical, Honest Guide
SMC is a popular discretionary price-action framework, not a proven view of institutional order flow. Here is what it claims, where it is weak, and how to convert it into rules you can actually test.
- Market structure
Market Structure, BOS and CHOCH: Objective Rules for Traders
BOS and CHOCH only mean something once swing points, breach rules, and timeframes are fixed in advance. Here is how to write structure rules two traders would apply identically.
- Trading strategies
Order Block Trading Strategy: Rules, Mitigation & Invalidation
Not every opposing candle is an order block. Learn how traders define the zone, where mitigation and invalidation sit, and how to test the setup honestly.
- Trading strategies
Fair Value Gap Trading: Imbalance Rules, Fills & Invalidation
A fair value gap is a three-candle imbalance, not a promise. Learn the exact rules, what fill and respect mean, and how to test the setup without hindsight.
- Smart money concepts
SMC Killzones: Asia, London & New York Trading Sessions
Killzones are community-defined session windows, not magic entry times. Use them as a testable context filter with explicit timezone rules, setup confirmation, and journal evidence.
- Trading analytics
MAE and MFE in Trading: Analyze Stops, Targets, and Exit Quality
MAE shows how far a trade moved against you while it was open; MFE shows how far it moved in your favor. Together they reveal path and exit quality that final P&L cannot.
- Trading analytics
Time-of-Day Trading Analytics: Measure Performance by Hour
Your best and worst trading hours should come from complete, timezone-correct data—not memory. Build a practical session analysis without overfitting tiny groups.
- Trading analytics
How to Forward Test a Trading Strategy
Forward testing is the stage after historical validation: execute frozen rules on new data, measure the gap between assumptions and reality, and make a predefined go, hold, or reject decision.
- Trading process
Rule Adherence in a Trading Journal: Score Process, Not P&L
A winning trade can violate the plan and a losing trade can follow it perfectly. Rule adherence separates decision quality from the outcome that happened next.
- Trading strategies
When Should You Retire a Trading Strategy?
A losing run is not proof that an edge disappeared. Use predefined safety limits, rolling evidence, regime and execution diagnostics, and a disciplined pause-to-retire decision process.
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