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Every earlier chapter taught you to "read the market"; this one teaches you to "manage yourself". Technical analysis ans
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01 · Trading Plan
Next lesson · 07 · Trading Systems
Every earlier chapter taught you to "read the market"; this one teaches you to "manage yourself". Technical analysis answers what to buy and when to buy; a trading system answers how much to buy, when to cut the loss, what to do after a loss, and whether you will give the profits back. Trading without a system is gambling; trading with a system is a business.
Placing orders without a plan is gambling: entering on a "feeling it will go up", holding losers to the bitter end, taking profits at the first tick — this is the daily routine of 90% of retail traders. This article lays out the eight elements of a trading plan (market / timeframe / entry / exit / stop-loss / position sizing / review / psychology) plus a complete template you can copy and fill in, and shows you how to translate "I feel it will go up" into conditions that are executable, verifiable, and reviewable. Finally, the expectancy formula EV = win rate × average win − loss rate × average loss shows you: why a strategy with a 30% win rate can still make money, and a strategy with a 50% win rate can still lose it.
Decide how much you can lose before thinking about how much you can make — this is the one order of priorities in trading that admits no compromise. This article covers the three essentials of position sizing (fixed-fraction 1%-2% risk per trade, how to use the Kelly criterion and its limits, equal-risk sizing), four stop-loss methods (fixed amount / ATR / structure / time), and trailing take-profits that let profits run. The math is walked through in tables: a 50% drawdown needs a 100% gain to break even, and how far a 5x/10x/20x/50x leveraged position can move against you before liquidation — by the end you will understand that "controlling drawdown" is not a matter of style, it is a matter of survival.
Why do retail traders always buy at the top and sell at the bottom? Why can't you press the button even when you know you should stop out? Why is a blow-up most likely right after three consecutive losses? Starting from the neural mechanisms (how FOMO and panic hijack your brain), this article dissects the five major cognitive biases (loss aversion / anchoring / confirmation bias / gambler's fallacy / disposition effect), each with a definition, a trading-scenario example, and countermeasures. It ends by answering the ultimate question — why knowing doesn't mean doing — and how to turn discipline into habit with rules, cooling-off periods, and automation.
The first three articles answer "how to do it"; this one answers "how well you did it". The equity curve is a trader's health report: steady uptrends, spike drawdowns, and long flat stretches each carry their own meaning and countermeasures. This article gives every key performance metric a common-sense passing line, walks through the math of drawdown recovery in tables (a 20% drawdown needs a 25% gain to break even; a 50% drawdown needs a double), and teaches you to use performance attribution to split P&L across strategy / instrument / session / direction — find where the money was made and where it was lost — before landing on actionable templates for daily logging and monthly reviews.
A review is not a diary of what happened; it is data-driven trade review: a three-layer framework from single-trade review, through daily/weekly review, to the monthly system review. It turns "should have stopped out but didn't" and "itched to trade while supposed to be flat" into a countable execution deviation rate, uses emotion logs to locate your personal minefields, and uses "market-system fit" to judge whether losses come from strategy decay or environment mismatch. This article provides Excel/Notion/Feishu template designs and thoughts on automated review (linking to the Quant Practice chapter), plus a complete fictional weekly review report you can model after.
A "daily three-part journal (pre-market / intraday / post-market) + weekly checklist + monthly system review" grounds the daily operation of a trading system: the journal records "what happened", the checklist ensures "everything that should be done was done". This article provides copy-ready templates, check metrics such as the execution deviation rate, and tool choices, complementing the "data-driven review" of the Advanced Trade Review article. Core stance: record the facts first, check discipline second, pass judgment last — reverse the order and the review becomes self-consolation.
① Trading plan (set the rules first: when to trade and how)
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② Risk management (then set the hard limits: how much you can lose at most, how to survive)
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③ Trading psychology (finally fix yourself: why you keep violating ① and ②)
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④ Trading journal & checklists (so ①②③ get checked and iterated daily/weekly/monthly)
⚠️ Risk Warning
Everything in this chapter is for study and research only and does not constitute investment advice. Leveraged trading can wipe out your principal and even leave you in debt (negative balance). Participate only with money you can afford to lose, and fully understand margin and liquidation mechanics before trading for real (see the Futures chapter).
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Trading plans — turning entries, exits, stop-losses and adds from feelings into rules, behavioral comparisons of planned vs unplanned traders, and how to write your own plan
Trading risk management — the accelerating cost of recovering losses, per-trade risk fractions, position calculation, maximum drawdown control, and the logic of always having a next hand to play
Trading psychology — the neural mechanics of FOMO and panic, System 1 vs System 2, and the cognitive biases behind loss aversion, sunk costs, and failing to follow your own plan
Equity curve and performance attribution — how to read the equity curve, maximum drawdown, Sharpe ratio, and deciding whether profits come from a good system or a good market
Advanced trade review — upgrading from a diary to data-driven review across five layers: single trade, periodic, system, emotion, and market environment
Trading journal and checklists — daily, weekly, and monthly logging and review templates; using checklists to enforce discipline and close the trading-system loop
The path from paper trading to live trading — what simulation can and cannot teach, what to practice and the three traps, graduation criteria, switching to live with minimum size, and the first-30-days slow-down rules
Price alerts and off-screen discipline — the attention cost of watching charts, outsourcing the "condition→action" trigger to the system, binding alerts to trading-plan key levels, alert overload, and what to do after an alert fires
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08 · Pitfalls
This is the last stop of the knowledge base — and the least romantic one: it does not teach you how to make money, it te