Trading fundamentals

Trading Fundamentals

Skill: Trading Fundamentals | Domain: trading | Category: fundamentals | Level: beginner Tags: trading, fundamentals, psychology, development, dual-tf, risk

1. Market Structure

Market Types

Market Type	Description	Examples
Exchange-Traded	Centralized, regulated, standardized	NYSE, NASDAQ, CME, CBOE
OTC (Over-the-Counter)	Decentralized, bilateral, flexible	Forex spot, bonds, derivatives
Dark Pools	Private exchanges, minimal pre-trade transparency	Liquidnet, IEX
ECN/ATS	Electronic, direct order matching	ARCA, BATS, IEX

Market Participants

Participant	Role	Typical Behavior
Market Makers	Provide liquidity, quote bid/ask	Mean-reverting, earn spread
Institutional Investors	Large funds, pension funds	Slow accumulation, trend-following
Hedge Funds	Diverse strategies, leverage	Short-term tactical, event-driven
Retail Traders	Individual accounts	Often contrarian signal (sentiment)
High-Frequency Traders	Algorithms, co-location	Latency arbitrage, market making
Central Banks	Currency intervention	Large directional moves
Arbitrageurs	Exploit price discrepancies	Keep markets efficient

Market Microstructure

• Bid-Ask Spread: Cost of immediacy; tighter = more liquid
• Order Book Depth: Volume at each price level; thin books = slippage
• Price Discovery: Process of finding fair value through supply/demand
• Market Impact: Price moves against your order as size increases
• Slippage: Difference between expected and executed price
• Tick Size: Minimum price increment (e.g., $0.01 stocks, 0.25 pts ES futures)
• Lot Size: Standard trading unit (100 shares stocks, 100,000 units forex standard lot)

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2. Order Types

Basic Orders

Order Type	Description	When to Use	Risk
Market Order	Execute immediately at best price	Need instant fill	Slippage in thin markets
Limit Order	Execute only at specified price or better	Price-sensitive entry/exit	May not fill
Stop Order	Becomes market when price reached	Stop-loss, breakout entry	Slippage at trigger
Stop-Limit	Becomes limit when stop triggered	Breakout with price control	May not fill past gap
Trailing Stop	Stop adjusts with price movement	Lock in profits on trends	Whipsaws in volatile markets
MIT (Market if Touched)	Market order when price touched	Reversal entries	Slippage
GTC (Good Till Cancelled)	Order stays until filled or cancelled	Swing trade entries	Forgotten orders
FOK (Fill or Kill)	Fill entire order or cancel	Large block trades	Frequent cancellations
IOC (Immediate or Cancel)	Fill what's available, cancel rest	Partial fills acceptable	Partial execution

Advanced/Algorithmic Orders

Order Type	Description	Formula/Logic
TWAP	Time-Weighted Average Price	Executes equal portions each time interval
VWAP	Volume-Weighted Average Price	Executes proportional to volume distribution
Iceberg	Shows only portion of total size	Total size hidden; refreshes displayed qty
POV (% of Volume)	Participate at set % of market volume	Slices = Volume × Target%
Implementation Shortfall	Minimize cost vs. arrival price	Optimizes between urgency and market impact
Pegged Orders	Price pegs to bid/ask/midpoint	Dynamic pricing with spread

Iceberg Order Example

Total Order: 100,000 shares Display Quantity: 1,000 shares → Market sees only 1,000 at a time → After each fill, 1,000 more displayed → Used to hide large institutional interest

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## 3. Asset Classes

| Asset Class | Sub-Types | Key Characteristics | Typical Instruments |
|-------------|-----------|--------------------|--------------------|
| **Equities** | Stocks, ETFs, ADRs | Ownership stake, dividends, earnings driven | AAPL, SPY, QQQ |
| **Fixed Income** | Gov bonds, Corp bonds, Munis | Interest payments, duration risk | TLT, AGG, UST |
| **Commodities** | Energy, Metals, Agri | Inflation hedge, cyclical | Gold, Oil, Corn |
| **Forex** | Major, Minor, Exotic pairs | 24/5 market, leverage, macro driven | EUR/USD, USD/JPY |
| **Derivatives** | Options, Futures, Swaps | Leverage, hedging, expiration | SPX options, ES futures |
| **Cryptocurrencies** | Layer-1, DeFi, Stablecoins | 24/7, high volatility, on-chain data | BTC, ETH, SOL |
| **Real Assets** | REITs, Infrastructure | Tangible, inflation protection | VNQ, MLP |
| **Alternative** | Hedge funds, PE, Commodities | Low correlation, illiquid | SPACs, art, wine |

### Asset Class Correlations (Typical)

- **Stocks ↔ Bonds**: Negative correlation in risk-off; breaks down in stagflation
- **USD ↑ → Gold ↓**: Usually negative (priced in USD)
- **Oil ↑ → CAD ↑**: Canada major oil exporter
- **Risk-off**: Buy USD, JPY, Gold, Treasuries; Sell EM, commodities
- **Risk-on**: Buy stocks, commodities, EM; Sell USD, bonds

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## 4. Trading Timeframes

| Style | Holding Period | Chart TF | Trades/Day | Typical R:R | Capital Required |
|-------|---------------|----------|-----------|-------------|-----------------|
| **Scalping** | Seconds–minutes | 1s–5m | 20–100+ | 1:1–1.5:1 | High (commissions) |
| **Day Trading** | Minutes–hours | 5m–1h | 2–10 | 2:1–3:1 | $25k+ (PDT rule) |
| **Swing Trading** | Days–weeks | 4h–Daily | 3–15/month | 3:1–5:1 | $5k–$25k |
| **Position Trading** | Weeks–months | Daily–Weekly | 1–5/month | 5:1–10:1 | $10k+ |
| **Investing** | Months–years | Weekly–Monthly | Annual | N/A | Any amount |

### Multi-Timeframe Hierarchy

Higher TF → Determines Trend Direction (Primary Bias) Middle TF → Confirms Setup / Pattern Lower TF → Precise Entry/Exit Timing

Example (Day Trader): HTF: Daily chart → Uptrend (above 200 EMA) MTF: 1h chart → Pullback to key support LTF: 15m chart → Bullish reversal candle for entry

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## 5. Core Principles: Risk Management (10 Rules)

### Rule 1: Never Risk More Than 1-2% Per Trade

Account: $50,000 Max Risk/Trade: 1% = $500 If stop = 50 points at $10/point → Max 1 contract

### Rule 2: Define Risk BEFORE Entry

- Place stop loss before entering
- Know exact dollar risk before sizing position
- Never move stops to avoid a loss (move only to lock in profit)

### Rule 3: Use Position Sizing, Not Gut Feel

- Size = Risk Amount ÷ (Entry Price − Stop Price)
- Always calculate; never guess

### Rule 4: Maintain Positive Expected Value

EV = (Win Rate × Avg Win) − (Loss Rate × Avg Loss) EV must be > 0 for long-term profitability Example: 40% WR, $300 avg win, 60% LR, $150 avg loss EV = (0.40 × $300) − (0.60 × $150) = $120 − $90 = +$30 per trade ✓

### Rule 5: Risk-Reward Minimum 2:1

- Never take a trade with R:R < 1.5:1
- Optimal: 2:1 to 3:1 for most strategies
- Allows profitability at 40% win rate: (0.40 × 2) − (0.60 × 1) = +0.20R

### Rule 6: Correlation Risk Management

- Don't hold multiple correlated positions at full size
- If 3 long tech stocks: effective risk = 3× single position risk
- Limit correlated sector exposure to 5–6% of capital

### Rule 7: Drawdown Limits

- Daily loss limit: 3% of account → Stop trading for the day
- Weekly loss limit: 6% → Reduce size by 50% next week
- Monthly loss limit: 10% → Full review before continuing
- Account drawdown: >20% → Stop, assess, fix before continuing

### Rule 8: Scale In, Scale Out

- Enter in 2–3 tranches to average better price
- Exit in 2–3 tranches to lock profits while running winners
- Never add to a losing position ("averaging down" = dangerous)

### Rule 9: Keep a Trading Journal

- Record every trade with: entry/exit, rationale, emotion, result
- Review weekly for patterns and improvement areas

### Rule 10: Protect Capital First, Make Profits Second

- Goal #1: Survive to trade another day
- Goal #2: Consistent small gains compound to large gains

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## 6. Position Sizing Formulas

### Method 1: Fixed Percentage Risk (Most Common)

Position Size = (Account × Risk%) ÷ |Entry − Stop|

Example: Account = $100,000 Risk% = 1% → $1,000 risk Entry = $50.00, Stop = $48.00 → $2.00 risk/share Position Size = $1,000 ÷ $2.00 = 500 shares Position Value = 500 × $50 = $25,000 (25% of account)

### Method 2: Kelly Criterion

f* = (bp − q) ÷ b

Where: b = average win / average loss ratio p = probability of win (win rate) q = 1 − p (probability of loss)

Example: Win Rate = 55%, Avg Win = $300, Avg Loss = $150 b = 300/150 = 2.0 f* = (2.0 × 0.55 − 0.45) ÷ 2.0 = (1.10 − 0.45) ÷ 2.0 = 0.325 = 32.5%

⚠️ Full Kelly is too aggressive! Use Half-Kelly (16.25%) or Quarter-Kelly (8.1%)

### Method 3: ATR-Based Position Sizing

Position Size = (Account × Risk%) ÷ (ATR × Multiplier)

Example: Account = $100,000, Risk% = 1% ATR(14) = $3.50 on a $75 stock Multiplier = 2× ATR for stop distance Stop Distance = 2 × $3.50 = $7.00 Position Size = $1,000 ÷ $7.00 = 142 shares

### Method 4: Volatility-Adjusted (Equal Volatility)

Position Size = Target Volatility / (Price × Daily Vol %) Target each position to contribute equal volatility to portfolio Used in risk parity and institutional portfolios

### Risk-Reward Analysis Table

| Win Rate | Min R:R Required for Breakeven |
|----------|-------------------------------|
| 30% | 2.33:1 |
| 40% | 1.50:1 |
| 50% | 1.00:1 |
| 60% | 0.67:1 |
| 70% | 0.43:1 |

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## 7. Drawdown Management

### Drawdown Calculations

Max Drawdown = (Peak Value − Trough Value) ÷ Peak Value × 100

Recovery Required from Drawdown: 10% loss → Need 11.1% gain to recover 20% loss → Need 25.0% gain to recover 30% loss → Need 42.9% gain to recover 40% loss → Need 66.7% gain to recover 50% loss → Need 100.0% gain to recover

### Drawdown Response Protocol

| Drawdown Level | Action |
|---------------|--------|
| 5% | Review recent trades, check for pattern errors |
| 10% | Reduce position size by 25%, increase selectivity |
| 15% | Reduce size by 50%, review strategy validity |
| 20% | Stop trading, full strategy audit, paper trade |
| 25%+ | Complete reset: new strategy or long break |

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## 8. Trading Psychology: 12 Cognitive Biases

### Bias 1: Confirmation Bias

- **What**: Seek information that confirms existing view
- **Example**: Only reading bullish articles on a stock you own
- **Counter**: Actively seek bearish arguments; read the bear thesis

### Bias 2: Recency Bias

- **What**: Overweight recent events, underweight long-term data
- **Example**: After 3 winning trades, expect #4 to win too
- **Counter**: Review at least 100+ trade sample; use statistics

### Bias 3: Loss Aversion

- **What**: Pain of losing 2× stronger than joy of equal gain
- **Example**: Hold losers too long, cut winners too early
- **Counter**: Pre-define exits; use trailing stops; separate emotions from trades

### Bias 4: Overconfidence Bias

- **What**: Overestimate skill, underestimate luck
- **Example**: Attribute wins to skill, losses to bad luck
- **Counter**: Track edge-adjusted returns; keep win/loss attribution log

### Bias 5: Anchoring Bias

- **What**: Over-rely on first piece of information seen
- **Example**: "Stock was at $100, now $60, must be cheap"
- **Counter**: Value from fundamentals/technicals, not reference prices

### Bias 6: Gambler's Fallacy

- **What**: Believe past events affect independent future events
- **Example**: After 5 losses, feel "due for a win"
- **Counter**: Each trade is independent; law of large numbers applies, not sequences

### Bias 7: Herding Bias

- **What**: Follow the crowd, seek social validation
- **Example**: Buying because "everyone on Twitter is bullish"
- **Counter**: Trade your own plan; use contrary indicators for positioning

### Bias 8: Status Quo Bias

- **What**: Prefer current state, resist change
- **Example**: Hold losing position hoping it "comes back"
- **Counter**: Ask "would I enter this trade fresh today?" If no → exit

### Bias 9: Disposition Effect

- **What**: Sell winners too early, hold losers too long (tax + psychology)
- **Example**: Sell at 10% profit but hold 30% losers
- **Counter**: Use trailing stops; evaluate positions on forward-looking merit only

### Bias 10: Narrative Fallacy

- **What**: Create coherent stories for random events
- **Example**: "Oil rose because traders worried about Middle East"
- **Counter**: Focus on price action and data; be skeptical of explanations

### Bias 11: Sunk Cost Fallacy

- **What**: Continue because of past investment, not future value
- **Example**: "I'm already down $5,000, I'll hold to get back to even"
- **Counter**: Sunk costs are irrelevant; decide based on future expected value

### Bias 12: FOMO (Fear of Missing Out)

- **What**: Chase trades already in motion due to fear of missing profits
- **Example**: Buying breakout 5% above your planned entry
- **Counter**: There's always another trade; define entry rules strictly

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## 9. Emotional Management Framework

### The STOP Technique (In-Trade)

S → Stop: Pause before acting impulsively T → Think: What does my system say to do? O → Observe: Am I emotional or rational right now? P → Proceed: Only act according to pre-defined rules

### Pre-Trade Checklist (Mental State)

- [] Am I well-rested? (Sleep < 6h → reduce size or don't trade)
- [] Am I emotionally neutral? (Not angry, depressed, or euphoric)
- [] Did I review my plan? (Know entry, stop, target before touching keyboard)
- [] Am I trading my system? (Not revenge trading or FOMO)
- [] Is account within normal drawdown? (Not tilting)

### States That Degrade Performance

| State | Risk | Action |
|-------|------|--------|
| Euphoric (after big win) | Oversize next trade | Reduce size 50% |
| Angry (after loss) | Revenge trade | Stop for the day |
| Tired | Slow reactions, poor judgment | Don't trade |
| Anxious | Exit too early | Reduce position size |
| Bored | Force trades | Find another activity |

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## 10. Trading Journal Template

### Trade Entry Fields

```yaml
Trade #: [Sequential number]
Date/Time: [Entry timestamp]
Instrument: [Symbol/Asset]
Direction: [Long/Short]
Setup Name: [e.g., "Bullish Engulfing at Support"]
Timeframe: [Primary chart TF]

Entry Price: $___
Stop Loss: $___     Stop Distance: $___ (___%)
Target 1: $___      R:R to T1: ___:1
Target 2: $___      R:R to T2: ___:1
Position Size: ___ shares/contracts
Dollar Risk: $___   % Account Risk: ___%

Pre-Trade Reasoning:
  Trend: [Higher TF trend direction]
  Pattern: [Technical setup identified]
  Confluence: [Supporting factors]
  Trigger: [Exact entry trigger]
  
Emotional State (1-10): ___
Conviction Level (1-10): ___

Trade Exit Fields

Exit Price: $___
Exit Date/Time: [Exit timestamp]
Hold Duration: ___
P&L: $___  (___R)

Exit Reason: [Stop/Target/Manual/Time]
Exit Rating (1-10): ___

Post-Trade Review:
  What worked: ___
  What failed: ___
  Emotional grade: ___
  Would I take this trade again? [Yes/No]
  Lesson learned: ___

Weekly Review Template

Week of: ___
Total Trades: ___
Winners: ___ (___%)  Losers: ___ (___%)

Gross P&L: $___
Avg Win: $___   Avg Loss: $___
Profit Factor: ___  (Gross Wins ÷ Gross Losses; target > 1.5)
Max Win: $___   Max Loss: $___
Max Drawdown: $___

Best Trade: ___ (Why it worked)
Worst Trade: ___ (What to change)
Main Lesson: ___
Next Week Focus: ___

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11. Trader Development Framework — 5 Stages

Source: Umar Ashraf — $55M+ career earnings, TradeZella founder, 12 years experience

Pre-Journey Truths (Accept Before Starting)

1. Trading is not easy — accepting difficulty prevents surprise/frustration
2. Money is NOT the goal — chase process, money is byproduct
3. Control only what you can control — risk, trade selection, emotions, rules
4. No permanent "aha moment" — consistent process, forever adjusted
5. Psychology is overrated in early stages — if emotions are a problem at
   stage 1-2, your SIZE is too large, not your psychology
6. Trading is a marathon — rushing = boom-bust cycle

Stage 1: Novice (2-4 weeks)

Goal: Build foundation, establish process
- Pick ONE market, ONE session, ONE style (don't diversify yet)
- Paper trade first if new, then real money with minimal capital ($1-3K)
- Risk: <1% per account (0.5% better). Risk $10 on $1K account.
- Max 3 trades/day
- End trading by 11-12am ET max
- Be at desk 1 hour before market open

Process framework:
  1. Pre-market game plan (events, levels, bias, inflection points)
  2. Live trading notes (15-minute check-ins, write thoughts while trading)
  3. Post-market analysis (compare plan vs actual execution)

Education balance: Videos/books start high, screen time medium;
  over time video goes down, screen time goes up

Stage 2: Developing (2-3 months)

Goal: Build playbooks with conceptual WHY
- Build playbooks — understand WHY patterns work, not just shapes
- Example "Morning Top" playbook:
  → Gap down from previous close
  → First 5min to 1h window
  → Upside move with NO follow-through (low volume, weak tape)
  → Activity slows / selling pressure appears
  → Short at key level rejection

- Back-test extensively: 3 years, 50+ instances, document each
- Track everything in R-multiple (not dollars): Lost 1R, made 2R, etc.
- Track: stop effectiveness, drawdown speed, entry/exit timing,
  best/worst trade times, rule compliance rate
- Weekly reviews mandatory
- Goals are skill-based: "Improve R-multiple" not "make $X"

Stage 3: Intermediate / Optimization (2-6 months)

Goal: Identify and fix problems systematically
- By now: data proves your biggest problems
- Problem-solving cycle:
  Identify → Understand deeply → Create solution → Track → Fixed
- Common problems: bias blocking flexibility, cutting profits early,
  oversizing, rushing second trade after win
- Correlating factors matter: bad sleep → emotional decisions → oversizing
- Playbooks should be established and back-tested by now
- Still NOT focused on money — money starts appearing as byproduct

Stage 4: Advanced / Sizing Up (6 months - 2+ years)

Goal: Dynamic risk management, emotions at scale
THIS is where emotions actually matter (not stages 1-3)

Dynamic risk rules:
  → Size up 20-30% increments only (not 10x jumps)
  → 1-2 max increased-risk trades per MONTH (special card)
  → Stay at new risk level 2 months before next increase
  → If in drawdown: DO NOT size up
  → After a big win: size DOWN on second trade
  → Volatile/uncertain market = conservative sizing

Confidence trap:
  After wins → confidence rises → every trade looks good →
  take bad trades → lose. Reset: walk away, journal, take time off.

Stage 5: Pro / Expert

NOT permanent — oscillate between 4 and 5 while sizing up
- Max risk defined, average risk defined (e.g., max 10K, avg 5K)
- 3-5 proven setups mastered
- Repeatable process that survives market regime changes
- Key feeling: "I can do this again" — process confidence, not aha moment
- Even at stage 5, revisit stage 1 basics when market shifts
- Took Umar ~8 years to reach stage 5

R-Multiple Tracking System

All P&L tracked in R (risk units), not dollars:
  Won 2R = made 2x your risk | Lost 1R = lost your risk amount

Metrics to track:
  - Win rate per playbook
  - R-multiple distribution (are you losing > -1R?)
  - Stop loss effectiveness (hit stop then reverse?)
  - Entry timing (early/late/on time)
  - Exit timing (early/late/on target)
  - Drawdown speed and recovery speed
  - Best/worst trade hours
  - Rule compliance rate
  - Playbook-specific performance

Review cadence: Daily recaps + Weekly reviews + Monthly reviews

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12. Dual Time-Frame Auction Retest System

Source: Rajan Dhall — DND Capital founder, CFTE/STA qualified, taught at London School of Economics

Framework

Anchor chart: Daily (determines bias)
Execution chart: 5-minute (takes trades)
NO intermediate timeframes — intentionally skips everything between
  Daily and 5M to avoid conflicting signals and preserve gap info

Moving Average Alignment Rule

Daily: 50 MA (macro trend) or 21 MA (day trading)
5-minute: 21 MA (intraday)

ONLY trade when BOTH timeframes show price on same side of MA:
  Above both MAs = LONGS only
  Below both MAs = SHORTS only
Both charts must show similar 45° angle structure ("look like each other")

Auction Area Concept

Derived from Market Profile theory (price discovery / value areas)
Auction area = zone of congestion where price spent most time
Yesterday's candle body provides auction context for today
Gap levels and opening price create key S/R zones

Entry Rules

1. Wait for price to retest the auction area (congestion zone) from the right side
2. Look for 2-candle break pattern at the auction retest:
   - Down candle breaks low of up candle = short signal (and vice versa)
3. Minimum 2:1 risk-to-reward on every trade
4. SL: above/below the candle structure high/low at the auction area

Trade Management

- 1 trade per day (data shows 3+ per day underperforms)
- Trade duration: 4-9 minutes average
- First hour of session only (highest volatility + best execution)
- Static risk every day (not dynamic) — compound by increasing base
  after building 20 trades of "casino money" profit
- Moving SL to breakeven at 1.75:1 is viable for candle-breaker entries
  but NOT for gap trades during high-volatility environments

The "Marta Method" Variation

Same entry as above but drops to 1-minute chart for exit:
  - Holds until 1M reversal candle pattern appears
  - Achieves 5-6:1 R:R vs standard 2:1
  - Requires more composure / micromanagement skill

Market Selection Insight

Best: Individual stocks (TSLA, AAPL, GOOG, NVDA) — $3-10 daily ranges
Good: DAX futures (50c stop, €1 target)
Avoid: FX (too efficient, two-way flow = 4 variables vs 2, spread costs kill edge)
Key: Stocks have no negative economic consequence from going up (unlike currencies)

Fractal: Same logic applies on Monthly+Daily (swing) or Weekly+Daily instead of Daily+5M

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Related Skills

• Strategy Selection
• Risk And Portfolio
• Smc Beginner Pro Guide
• Market Microstructure