Trading Psychology and Performance

• Trading JournalBeginner6 min read

  A trading journal is a record of every trade you take — the setup, the reasons, the result and what you felt — kept so you can learn from patterns in your own behaviour.

• Win RateBeginner5 min read

  Win rate is the percentage of trades that end in profit; on its own it says little, because a 30% win rate can be profitable and a 90% one can lose money.

• BacktestingIntermediate6 min read

  Backtesting is applying a strategy's rules to historical data to see how it would have performed — useful, but easy to fool yourself with if the test is not honest.

• ExpectancyIntermediate5 min read

  Expectancy is the average amount a strategy makes or loses per trade: (win rate × average win) − (loss rate × average loss).

• Profit FactorIntermediate4 min read

  Profit factor is gross profit divided by gross loss; above 1 means the strategy made more on winners than it lost on losers.

• Sharpe RatioAdvanced4 min read

  The Sharpe ratio measures return per unit of risk: excess return over a risk-free rate divided by the volatility of returns.

• Sortino RatioAdvanced4 min read

  The Sortino ratio is like the Sharpe ratio but counts only downside volatility, so large gains are not penalised as risk.

• TiltBeginner3 min read

  Tilt is an emotional state, usually after losses, in which you stop following your rules and start taking impulsive, oversized trades.

• Loss AversionIntermediate4 min read

  Loss aversion is the tendency to feel losses more strongly than equal gains, which leads traders to hold losing positions too long and close winners too early.

• Fear and GreedBeginner4 min read

  Fear and greed are the two emotions most often blamed for trading mistakes: fear makes people exit too early or freeze, greed makes them over-size or hold too long.

• Trading DisciplineBeginner4 min read

  Discipline is following your trading plan consistently — waiting patiently for valid setups and respecting your exits — even when emotions push the other way.

• Average Win and Average LossIntermediate4 min read

  Average win and average loss are the mean profit of winning trades and the mean loss of losing trades; combined with win rate they determine expectancy.

• Pre-Trade and Post-Trade ChecklistsBeginner4 min read

  A pre-trade checklist lists the conditions a trade must meet before you enter — setup, trend, risk, news. A post-trade checklist reviews what happened afterwards: whether you followed the plan, what went well and what to change.

• Trading PsychologyBeginner5 min read

  Trading psychology covers the emotions, biases and habits that affect your decisions — often the difference between a good plan and good results.

• Confirmation BiasIntermediate3 min read

  Confirmation bias is the tendency to favour information that supports a trade you already hold and dismiss information that contradicts it.

• Fear of Missing OutBeginner4 min read

  FOMO is the urge to jump into a trade because a price is moving fast and others seem to be profiting, often without a plan.

• Gross and Net ReturnBeginner3 min read

  Gross return is the result before costs; net return is what remains after fees, spreads, financing and slippage — the only figure that ends up in your account.

• Process vs. OutcomeBeginner4 min read

  Judging a trade by its process rather than its result: a good trade follows the plan with controlled risk, whatever the outcome. Process goals (follow the checklist, respect the stop) are under your control; outcome goals (make $1,000 this week) are not.

• OverfittingAdvanced3 min read

  Overfitting is tuning a strategy so closely to past data that it captures noise rather than a real pattern, so it fails on new data.

• OvertradingBeginner3 min read

  Overtrading is trading too often or too large, usually out of boredom or emotion, which raises costs and the number of mistakes.

• Paper TradingBeginner3 min read

  Paper trading is practising with simulated money, often in a broker's demo account, before risking real money in live trading.

• Revenge TradingBeginner3 min read

  Revenge trading is taking impulsive, often larger trades straight after a loss in an attempt to win the money back quickly.

• Trade ReviewBeginner3 min read

  A trade review is a structured look back at closed trades to check whether you followed your plan and what to change, judged on process rather than outcome alone.

• Anchoring BiasBeginner4 min read

  Anchoring is relying too heavily on the first number you saw — such as your entry price or a stock’s old high — when judging what something is worth now.

• Availability BiasIntermediate3 min read

  Availability bias is judging how likely something is by how easily examples come to mind. A recent, vivid crash makes another crash feel more likely than the evidence suggests.

• Calmar RatioAdvanced3 min read

  The Calmar ratio divides annualised return by maximum drawdown. A strategy returning 15% a year with a worst drawdown of 30% has a Calmar ratio of 0.5. It rewards returns earned without deep losses.

• Concept DriftAdvanced3 min read

  Concept drift is when the relationship a model learned changes over time, so a model that worked in the past stops working. In markets it can follow changes in regulation, participants or market regimes.

• Data SnoopingAdvanced3 min read

  Data snooping is testing so many ideas on the same data that some look profitable purely by chance. The more variations you try, the more likely the best one is luck rather than a real edge.

• Decision Fatigue and Analysis ParalysisBeginner3 min read

  Decision fatigue is the decline in decision quality after making many decisions. Analysis paralysis is overthinking until you cannot act at all. Rules, checklists and fewer trades reduce both.

• Forward TestingIntermediate3 min read

  Forward testing is running a strategy on new, live market data — with paper money or small size — to check that backtest results hold up.

• Gambler’s Fallacy and Hot-Hand FallacyBeginner4 min read

  The gambler’s fallacy is believing that a random outcome is “due” after a streak — for example, that five losing trades in a row make a win more likely. The hot-hand fallacy is the opposite mistake: believing a winning streak will continue without evidence.

• Good Losses and Bad WinsBeginner3 min read

  A good loss follows the plan and stays within the planned risk — sometimes it is simply an unlucky trade. A bad win makes money while breaking the rules — a lucky trade. Rewarding bad wins teaches habits that eventually cost money.

• Hindsight BiasBeginner3 min read

  Hindsight bias is the feeling, after the fact, that an outcome was obvious all along. It makes traders overestimate how predictable markets are and blame themselves unfairly for missed moves.

• Information Ratio and Tracking ErrorAdvanced3 min read

  Tracking error is the volatility of the difference between a portfolio’s returns and its benchmark’s. The information ratio divides the average excess return by the tracking error, showing how consistently a manager beats the benchmark.

• Journal Tags and Trade AnnotationsBeginner3 min read

  Journal tags are labels added to each trade — the setup used, the mistake made, your emotional state, the market condition — so that results can later be filtered and compared. Annotations are notes drawn or written on the chart itself.

• Look-Ahead BiasAdvanced3 min read

  Look-ahead bias is using information in a backtest that was not available at the time — for example, trading at a day’s close using a signal calculated from that same close, or using revised economic data. It makes results look better than reality.

• Loss ChasingBeginner3 min read

  Loss chasing is raising risk to win back losses quickly — larger positions, lower-quality setups or extra trades. It is closely related to revenge trading and often turns a bad day into a disastrous one.

• Maximum Adverse and Favourable ExcursionAdvanced3 min read

  Maximum adverse excursion (MAE) is the largest open loss a trade showed before it closed; maximum favourable excursion (MFE) is the largest open profit. Comparing them across many trades helps judge whether stops are too tight or targets too close.

• Mental AccountingIntermediate3 min read

  Mental accounting is treating money differently depending on where it came from — for example, taking bigger risks with “house money” from recent profits. Every dollar in the account is worth the same.

• Missed TradeBeginner3 min read

  A missed trade is a valid setup under your plan that you did not take. Recording missed trades shows whether hesitation is costing you, but chasing them after the fact is a common mistake.

• Narrative BiasIntermediate3 min read

  Narrative bias is preferring a convincing story over the quality of the evidence. A compelling explanation for why a stock must rise can make it easy to ignore data that says otherwise.

• No-Trade ConditionsBeginner3 min read

  No-trade conditions are rules that tell you not to trade — such as major news in the next hour, a hit loss limit, poor sleep or a market that does not fit your strategy. A no-trade day is a day you sit out deliberately.

• Overconfidence BiasBeginner3 min read

  Overconfidence is believing your knowledge or skill is greater than it is. In trading it shows up as oversized positions, excessive trading and ignoring risk after a run of wins.

• Pre-Commitment and Cooling-Off PeriodsBeginner3 min read

  Pre-commitment is deciding your rules — entries, stops, size, loss limits — before emotions are involved. A cooling-off period is a planned break after a big loss or stressful event before you trade again.

• Recency BiasIntermediate3 min read

  Recency bias is giving too much weight to the most recent events, such as assuming a strategy is broken after three losses in a row.

• Rule Adherence and Rule ViolationsBeginner3 min read

  Rule adherence is how closely you follow your written trading plan; a rule violation is any trade or action that breaks it. Tracking adherence separately from profit shows whether results come from the method or from luck.

• Sample Size and Statistical SignificanceIntermediate3 min read

  Sample size is how many trades a result is based on; small samples produce misleading statistics, and statistical significance asks whether a result could be luck.

• Scratch TradeIntermediate3 min read

  A scratch trade is one closed at or near break-even, usually because the idea stopped looking right. After costs it is often a small loss.

• Setup Grades (A, B and C Setups)Intermediate3 min read

  Many traders grade setups by how well they match their criteria: an A setup meets every condition, a B setup most, a C setup only some. Grading helps decide position size, or whether to trade at all.

• Sunk Cost FallacyIntermediate3 min read

  The sunk cost fallacy is continuing with a losing idea because of what you have already put in, rather than judging it on what happens next.

• Survivorship BiasIntermediate3 min read

  Survivorship bias is drawing conclusions only from what survived — successful traders or companies still listed — while ignoring the failures that disappeared.

• Trade EfficiencyAdvanced3 min read

  Trade efficiency compares the profit you actually captured with the maximum favourable move during the trade (MFE capture). Taking $3 of a $5 move is 60% efficiency. Consistently low numbers suggest exits are too early or too late.

• Trade FrequencyBeginner3 min read

  Trade frequency is how often you trade. Higher frequency multiplies costs and decisions, so it only makes sense if each trade has an edge after those costs.

• Trading RoutineBeginner3 min read

  A trading routine is a repeatable daily process — preparing before the market opens, trading the plan and reviewing afterwards — that reduces impulsive decisions.

• Walk-Forward AnalysisAdvanced3 min read

  Walk-forward analysis tests a strategy by repeatedly optimising it on one period and then testing it on the following, unseen period, rolling forward through the data. It gives a more honest estimate than a single optimisation over all the data.

Each term is defined in one sentence. Terms marked “Article in preparation” will get a full step-by-step article.

• Behavioral Finance

  BeginnerArticle in preparation

  Behavioral finance studies how real people make money decisions — with biases, emotions and rules of thumb — instead of assuming everyone is perfectly rational. It explains patterns such as panic selling, herd buying and holding losers too long.

• Don't Fight the Fed

  BeginnerGlossary

  “Don't fight the Fed” is a market saying: when the central bank is cutting rates and adding liquidity, stay bullish; when it is tightening, be cautious. Its cousin, “don't fight the tape”, warns against betting against a strong trend.

• Greater Fool Theory

  BeginnerArticle in preparation

  The greater fool theory describes buying something overpriced in the belief that someone else will pay even more later. It works until the buyers run out — which is why bubbles that rest on it end abruptly.

• Home Bias

  BeginnerGlossary

  Home bias is investors' tendency to hold mostly assets from their own country, even when it is a small slice of the world market. It feels familiar and safe but concentrates risk in one economy and currency.

• Market Bubble

  BeginnerArticle in preparation

  A bubble is a run-up in which prices race far beyond any reasonable value because buyers expect to sell higher to someone else, not because of the asset's earnings or use. Famous examples include the dot-com stocks of 1999–2000 and US housing before 2008.

• Market Sentiment

  BeginnerArticle in preparation

  Market sentiment is the prevailing mood of investors — greedy, fearful or undecided — measured with surveys, positioning data, volatility indexes and options activity. Extremes are often read contrarily: when everyone is bullish, few buyers are left.

• Priced In

  BeginnerArticle in preparation

  News is “priced in” when markets already expected it, so prices barely move when it arrives. That is why a stock can fall on good earnings: investors had already bought in anticipation of results that were even better.

• Window Dressing

  IntermediateGlossary

  Window dressing is a fund manager buying recent winners and selling losers just before a reporting date, so the published holdings look smarter than the actual decisions were. It can add buying pressure to strong stocks at quarter-end.