04 · Trading Schools and Philosophy

The previous article covered "who made money and how"; this one answers "what should I believe, and how should I think". First a panoramic scan of the four mainstream schools (technical, fundamental, quantitative, event/macro), then five unavoidable philosophical questions (is the market efficient? predict or respond? probabilistic thinking? profit and loss from the same source? **circle of competence?), closing with a template for writing "your own trading philosophy". The first twelve articles of this knowledge base taught you "how to do it"; this one teaches you "why".

Disclaimer: Everything on this site is for learning and research only and does not constitute investment advice. Markets carry risk; invest with caution.

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I. The Four Mainstream Schools at a Glance

School	Core question	Tools	Timeframe	Representative figures	Main weakness
Technical analysis	Does price action repeat?	Candles, patterns, indicators, volume-price	Seconds-weeks	Livermore, Turtles	Subjective signals, many false breakouts
Fundamental analysis	What is the company worth?	Financials, valuation, moats	Quarters-years	Buffett, Lynch	Slow, long error-correction windows
Quantitative	Are statistical patterns stable?	Models, backtests, probability	Minutes-months	Thorp, Simons	Model decay, capacity limits
Event/macro	How do policy and sentiment drive prices?	Central banks, news, capital flows	Days-years	Soros, Dalio	Unfalsifiable, leverage risk

1.1 Technical Analysis: A Philosophical Positioning of Chart Reading

• Assumptions: market action discounts everything (price reflects all news); prices move in trends; history repeats (human nature doesn't change).
• Where it applies: short-to-medium-term trading in liquid markets (stocks, futures, crypto, forex); quantified stop-losses, level selection, risk-control execution.
• Philosophical positioning: technical analysis' real value isn't "prediction" but "providing a reproducible response framework" — turning "where should I make my decision" into a map you can practice against repeatedly.
• Limitations (see Chapter 06 - Technical Analysis): signal homogeneity causes "level stampedes"; false breakouts dominate in ranging markets; pattern judgment is subjective.
• In one line: technical analysis is not a crystal ball but a coordinate system for decisions — it doesn't tell you what happens tomorrow; it tells you "if A happens, do B."

1.2 Fundamentals: Value vs Growth, Left Side vs Right Side

Inside fundamental investing sit two classic divides:

Dimension	Value investing	Growth investing
Core question	What is it worth now (is it cheap?)	What will it be worth later (does it grow fast?)
Valuation tools	PE, PB, dividend yield, free cash flow	PEG, revenue growth, market runway
Holding period	3-10 years	1-3 years
Representatives	Buffett, Graham	Lynch, Fisher, Cathie Wood
Risk	Cheap turns into trap (value trap)	Growth misses expectations and valuation compresses

Dimension	Left-side trading	Right-side trading
Entry timing	Buy in batches during declines / near bottoms	Buy after trend confirmation (breakouts)
Psychological cost	High (the more you buy, the more you lose)	Low (may profit right after buying)
Judgment required	Must have a "value anchor"	Must have "trend rules"
Typical losses	Catching falling knives, bottom-fishing halfway down	False breakouts, chasing tops

• Philosophical point: fundamentalists believe "prices eventually revert to value", but the theory says nothing about timing — left-side buyers may endure 2-3 years in a "value trough", while right-side buyers accept "paying a bit more for more certainty".
• Common misconception: tying "fundamental analysis" to "long-term holding" is wrong — fundamentals answer "worth buying or not"; trends and position sizing answer "when to buy and how much". They are partners, not substitutes.

1.3 Quantitative: Rule-Based, Statistical, No Prediction Only Response

• Core: every decision comes from backtestable rules and data; subjective emotion is banned. The goal is not "being right" but "positive expectancy plus surviving drawdowns".
• Three keywords:
  • Rule-based: signals defined to the decimal (entries, stops, taking profits, sizing all written as if-then), no improvisation.
  • Statistical: every signal must answer "sample size? win rate and profit/loss ratio? stability (Sharpe)?" — replace gut feeling with historical distributions.
  • No prediction, only response: models output not "it rises tomorrow" but "if it rises/falls, what are my positions and actions?"
• The quant's price: models fail (market structure changes), capacity is finite (crowded strategies die), and backtests lie (overfitting).
• Philosophical point: quants are the school most thoroughly "admitting ignorance" — they abandon "seeing the future" in exchange for "controlling losses". Ordinary traders can borrow its spirit (rules, backtesting, discipline) without replicating its technical complexity.

1.4 Event/Macro: Gaming Central Banks and Policy

• Core: short-term market moves are driven less by fundamentals than by the game between money and expectations — rate decisions, fiscal stimulus, currency interventions, regulation, geopolitics all rewrite "expected futures".
• Representative tools: yield curves, central bank speeches, CPI and nonfarm payrolls, capital flows, positioning crowding.
• Representative scenarios: Fed hiking cycles compressing valuations; easing cycles lifting risk assets; a central bank abandoning its peg (the 2015 Swiss franc black swan, see 02 - Famous Crashes and Black Swans); policy crackdowns on asset classes (China tutoring in 2021, crypto in 2022).
• Philosophical point: macro judgments are unfalsifiable (you can't prove them wrong beforehand), so this school most needs "position management > forecasting skill" — even Soros's macro bets came with hard stops; ordinary traders' macro convictions must be discounted before deployment.
• Special note for A-shares: policy weighs heavier in China than in U.S. markets, and the rhythm of "policy bottom → market bottom → economic bottom" gets gamed repeatedly; macro traders in A-shares must confirm timing with technicals (see the Chinese-market addendum in 03 - Trading Masters).

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II. Five Philosophical Questions

2.1 Is the Market Efficient or Not?

• The Efficient Market Hypothesis (EMH): proposed by Eugene Fama — prices already reflect all public information; excess returns come only from luck — no one can consistently beat the market.
• Behavioral finance: Daniel Kahneman, Robert Shiller, and others demonstrated systematic investor irrationality (herding, loss aversion, overconfidence, anchoring), with prices deviating from value for long stretches — markets can be beaten in phases.
• Fun fact: the 2013 Nobel Prize in Economics went to Fama and Shiller simultaneously — two contradictory theories sharing one trophy, itself the best footnote to the market's complexity.
• The ordinary trader's stance: don't pick sides; divide labor by market and timeframe:
  • Long-term broad index funds: assume near-efficiency — buy indexes, don't time (passive).
  • Specific sectors/stocks: admit frequent mispricing, but operate only within your circle of competence (active).
  • Short term/perpetuals: assume zero informational edge over the market — survive on rules and discipline alone.
• In one line: markets are efficient most of the time and inefficient at extremes — you needn't beat the market, just avoid standing on the wrong side when it breaks.

2.2 Prediction vs Response

• The predictor's dilemma: right forecast + no position = wasted; wrong forecast + holding on = disaster. Forecast accuracy naturally sits below 60% (coin-flip territory), and prediction cannot answer "what if I'm wrong?"
• The responder's position: admit you can't predict; handle uncertainty with rules —
  • Don't predict direction; define "if A then X, if B then Y";
  • Don't predict magnitude; cap per-trade risk with ATR/position sizing;
  • Don't predict duration; let stops and trailing exits decide how long you hold.
• The two stances aren't opposed: prediction supplies directional hypotheses (scripts); response supplies execution (what if the script fails). Professionals differ from amateurs thus: amateurs prepare only for the script where they're right; professionals prepare for the script where they're wrong.
• In one line: prediction builds scenarios; response makes money.

🛑 Prediction Builds Scenarios; Response Makes Money

Prediction builds scenarios; response makes money. Forecast accuracy naturally runs below 60% and cannot answer "what if I'm wrong"; responders write decisions as if-then rules — define the loss first, discuss returns second.

2.3 Probabilistic Thinking: One Trade Proves Nothing

• Core: each trade is "one sample draw from a random variable"; single wins and losses prove nothing — a positive long-run expectancy is what validates a system.

• Math example (a system that stays correct after 5 straight losses):

  • System: win rate 40%, profit/loss ratio 3:1 (win 3R / lose 1R).
  • Per-trade expectancy = 0.4 × 3 − 0.6 × 1 = +0.6R (positive).
  • Probability of 5 straight losses = 0.6^5 ≈ 7.8% — hardly rare; any system trading 100 times will contain roughly 8 such streak samples.
  • After 5 straight losses the expectancy is still +0.6R per trade — the system hasn't degraded; your emotions have.

• Three corollaries of probabilistic thinking:

  1. Evaluate systems in blocks of 20-30 trades — single-trade, daily, and weekly P&L are all noise.
  2. Revenge-sizing after losses (doubling down to average) is the fastest road to ruin — that's gambler's fallacy ("my turn to win now"), not probability.
  3. Decide "my maximum tolerable losing streak" first, then size each trade: if 5 straight losses would break you psychologically, your size should be sized for surviving 15.

• In one line: you don't need to be right on every trade — you need wins bigger than losses when you're right.

2.4 Profit and Loss Share One Source: Returns Require Bearing Volatility

• Core: every positive-expectancy strategy must bear corresponding drawdowns and losses — volatility and returns are two faces of one coin; you cannot keep the return and refuse the volatility.
• Evidence:
  • Trend strategies earn from "big trends", paying with repeated stop-outs in chop (losing two-thirds of the time);
  • Value strategies earn from "reversion to value", paying with possible 2-3 years of going nowhere or down;
  • Arbitrage/market-making earns from "liquidity", paying with extreme events that erase months of profit in one hit (market makers' collective blowups in 2008 and March 2020).
• Corollary 1: risk-free arbitrage is scarce. When some "risk-free return" appears (20%-yield stablecoins, shadow-financing spreads), it either closes fast or hides unpriced risk (see LUNA in 01 - A History of Financial Bubbles).
• Corollary 2: the essence of a stop-loss is not "avoiding losses" but "controlling the ratio between losses and gains" — accepting small losses preserves the chance at big wins.
• In one line: decide first how much volatility you'll bear for a given return — then decide whether you want that return at all.

2.5 Circle of Competence and Focus: Trade Only What You Understand

• Circle of competence (Buffett/Munger): invest only in industries and assets you truly understand — understanding means being able to answer "how does it make money? will it still in ten years? am I calm when the price falls?"
• Three forms of focus:
  • Trade only 1-2 instruments (e.g., BTC only, no basket of altcoins);
  • Trade only 1-2 timeframes (e.g., daily swings only, no 1-minute charts);
  • Run only 1-2 strategies (e.g., trend breakouts only, no news-gambling).
• The circle's cost: you will miss plenty of "other people's opportunities" — that's the circle's normal fee; almost every historical "exception" outside the circle produced the biggest losses (late Livermore fighting trends, retail chasing fads).
• In one line: you can never earn all the market's money, but you can lose all of yours — guarding the circle is guarding principal.

2.6 Your Relationship with the Market: Reverence, Compliance, Confrontation

Stance	Meaning	Typical mindset	Outcome
Revere the market	Admit your smallness and the unknown	"I'm the weak one here; survive first"	Survive and slowly get rich
Comply with the market	Go with the trend, never argue	Ride while it lasts, leave when it ends	Capture the main wave
Fight the market	Bottom-fish against trends, top-pick, hold losers	"The market's wrong; I'm right"	Most positions die in defiance
Master the market (illusion)	Believe you can control prices	Pooling, manipulation, all-in bets	Manipulators end up in prison (see Xu Xiang)

• The correct order: revere first (risk control), comply second (follow the trend), and only then discuss "counter-trend within your circle" (left-side value buys).
• In one line: the market targets no one, yet spares no one — reverence isn't cowardice; it's clarity.

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III. How to Write Your Own Trading Philosophy

Trading philosophy = your worldview of the market (what it is) + your self-knowledge (what I can do) + the behavioral rules derived from both (what I do). Fill in this template, and you have your own "Dao":

[1. Worldview] What is the market to me?
  Example: short term it's a voting machine driven by emotion (easily pushed to extremes),
  long term it's a weighing machine (value dominates).
  Core propositions I accept/reject: ______

[2. Self-Knowledge] Who am I?
  Time I can invest: ___ hours per week
  Maximum drawdown I can bear: ___% (write a specific number; derive it from the questionnaire in 01 - Getting Started)
  Fields I understand (circle of competence): ①____ ②____ ③____
  My character weaknesses (cross-check with the trading psychology audit in Chapter 07 - Trading System): ______

[3. School Choice] Which school is primary, which secondary?
  Primary: □Technical □Fundamental □Quant rules □Event/Macro (pick 1)
  Secondary: ______ (0-1, used to confirm entry timing for the primary)

[4. Behavioral Rules] (every rule must be checkable)
  1. Instruments I trade: ______
  2. Timeframes I trade: ______
  3. My entry rule (written as if-then): ______
  4. My maximum risk per trade: ___% of account (recommend 1%-2%)
  5. My stop-loss rule: ______ (executed unconditionally)
  6. My profit-taking/exit rule: ______
  7. Three things I will absolutely never do: ①____ ②____ ③____

[5. One-Sentence Philosophy]
  Example: "I enter only within my circle of competence, only on confirmed trends,
       risking 1% to chase 3:1 payoff — admit losses fast, hold winners long,
       and let compounding work for me."

Acceptance criteria:

• Read it to a friend who knows nothing about trading — can they retell "when you buy and when you concede"? If not, your philosophy is still a slogan.
• Test it against the seven extreme events in 02 - Famous Crashes and Black Swans: what does your philosophy say happens in each case? If you can't answer, your risk control hasn't been integrated into it.
• Date it and reread in three months: if any rule got changed, record why — good trading philosophies are carved by subtraction, not stacked by addition.

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⚠️ Risk Warning

All schools and philosophical views here serve teaching and research purposes only and do not constitute investment advice. No school is absolutely superior — they differ only in fit with your time, cognition, and temperament; none guarantees profit, and no "philosophy" substitutes for position management and stop-loss discipline. Leveraged trading can wipe out principal and even leave you in debt (negative balance) — participate only with money you can afford to lose, and fully understand margin and forced-liquidation mechanics before trading live (see Chapter 03 - Futures).

Further Reading

• 05 · A Brief History of China's Stock Market
• 06 · Crypto History
• 03 · Trading Masters