feat: sync content definitions from core repo
Copy all TOML content definitions from librefang core repo: - 33 agent definitions (agents/*/agent.toml) - 14 hand definitions with docs (hands/*/HAND.toml + SKILL.md) - 25 integration templates (integrations/*.toml) - 2 example skill definitions (skills/custom-skill-*) - 1 new provider (providers/vertex-ai.toml) Part of the framework-vs-content registry split (RFC v0.7).
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---
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name: trader-hand-skill
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version: "1.0.0"
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description: "Expert knowledge for autonomous market intelligence and trading — technical analysis, risk management, Alpaca API, financial data sources"
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author: LibreFang
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tags: [trading, finance, stocks, crypto, technical-analysis, risk-management]
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tools: [shell_exec, file_read, file_write, web_fetch, web_search, memory_store]
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runtime: prompt_only
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---
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# Trading Expert Knowledge
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## Reference Knowledge
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## 1. Technical Analysis Indicators Reference
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### RSI (Relative Strength Index)
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```
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Formula: RSI = 100 - (100 / (1 + RS))
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Where: RS = Average Gain / Average Loss over N periods (default N = 14)
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Step-by-step calculation:
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1. For each period, compute change = Close(t) - Close(t-1)
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2. Gains = max(change, 0), Losses = abs(min(change, 0))
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3. First average: simple mean of first 14 gains/losses
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4. Subsequent: AvgGain = (PrevAvgGain * 13 + CurrentGain) / 14 (Wilder smoothing)
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5. RS = AvgGain / AvgLoss
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6. RSI = 100 - (100 / (1 + RS))
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Worked example (14-period):
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Avg Gain over 14 periods = 1.02
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Avg Loss over 14 periods = 0.68
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RS = 1.02 / 0.68 = 1.50
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RSI = 100 - (100 / (1 + 1.50)) = 100 - 40 = 60.0
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```
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**Interpretation:**
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- RSI < 30: Oversold territory (potential buy signal)
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- RSI > 70: Overbought territory (potential sell signal)
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- RSI = 50: Neutral — price momentum balanced
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**Advanced RSI Signals:**
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| Signal | Description | Strength |
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|--------|-------------|----------|
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| Bearish divergence | Price makes new high, RSI makes lower high | Strong reversal warning |
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| Bullish divergence | Price makes new low, RSI makes higher low | Strong reversal warning |
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| Bullish failure swing | RSI drops below 30, bounces, pulls back above 30, breaks prior RSI high | Very strong buy |
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| Bearish failure swing | RSI rises above 70, drops, bounces below 70, breaks prior RSI low | Very strong sell |
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| Range shift | RSI oscillates 40-80 in uptrend, 20-60 in downtrend | Trend confirmation |
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**Best practices:** Never use RSI as a sole signal. Combine with trend direction (moving averages) and volume. In strong trends, RSI can stay overbought/oversold for extended periods.
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---
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### MACD (Moving Average Convergence Divergence)
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```
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MACD Line = EMA(12) - EMA(26)
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Signal Line = EMA(9) of MACD Line
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Histogram = MACD Line - Signal Line
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EMA formula: EMA(t) = Price(t) * k + EMA(t-1) * (1 - k)
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Where: k = 2 / (N + 1)
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For EMA(12): k = 2/13 = 0.1538
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For EMA(26): k = 2/27 = 0.0741
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Worked example:
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EMA(12) = 155.20
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EMA(26) = 152.80
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MACD Line = 155.20 - 152.80 = 2.40
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Previous Signal Line = 1.80
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Signal Line = 2.40 * (2/10) + 1.80 * (8/10) = 0.48 + 1.44 = 1.92
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Histogram = 2.40 - 1.92 = 0.48 (positive = bullish momentum increasing)
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```
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**Interpretation:**
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| Signal | Condition | Strength |
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|--------|-----------|----------|
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| Bullish crossover | MACD crosses above Signal Line | Moderate buy |
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| Bearish crossover | MACD crosses below Signal Line | Moderate sell |
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| Zero-line bullish cross | MACD crosses above zero | Trend change to bullish |
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| Zero-line bearish cross | MACD crosses below zero | Trend change to bearish |
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| Histogram expansion | Bars growing taller | Momentum accelerating |
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| Histogram contraction | Bars shrinking | Momentum weakening, reversal may come |
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| Bullish divergence | Price new low, MACD higher low | Strong reversal signal |
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| Bearish divergence | Price new high, MACD lower high | Strong reversal signal |
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---
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### Bollinger Bands
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```
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Middle Band = SMA(20)
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Upper Band = SMA(20) + 2 * StdDev(20)
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Lower Band = SMA(20) - 2 * StdDev(20)
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Bandwidth = (Upper - Lower) / Middle
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%B = (Price - Lower) / (Upper - Lower)
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Worked example:
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SMA(20) = 150.00
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StdDev(20) = 3.50
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Upper = 150.00 + 2 * 3.50 = 157.00
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Lower = 150.00 - 2 * 3.50 = 143.00
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Bandwidth = (157.00 - 143.00) / 150.00 = 0.0933 (9.33%)
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Current price = 155.00
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%B = (155.00 - 143.00) / (157.00 - 143.00) = 12/14 = 0.857
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Interpretation: Price is 85.7% of the way from lower to upper band — near upper band
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```
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**Key Bollinger Band Signals:**
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| Signal | Condition | Meaning |
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|--------|-----------|---------|
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| Squeeze | Bandwidth at 6-month low | Volatility contraction, big move imminent |
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| Squeeze breakout up | Price breaks above upper band after squeeze | Strong bullish breakout |
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| Squeeze breakout down | Price breaks below lower band after squeeze | Strong bearish breakout |
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| Walking the upper band | Price hugs upper band with middle band rising | Strong uptrend — do NOT short |
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| Walking the lower band | Price hugs lower band with middle band falling | Strong downtrend — do NOT buy |
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| Mean reversion touch | Price touches outer band, %B reverses | Potential reversion to middle band |
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| W-bottom | Price hits lower band twice, second low has higher %B | Bullish reversal pattern |
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| M-top | Price hits upper band twice, second high has lower %B | Bearish reversal pattern |
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---
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### VWAP (Volume Weighted Average Price)
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```
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VWAP = Cumulative(Typical Price * Volume) / Cumulative(Volume)
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Typical Price = (High + Low + Close) / 3
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Worked example (first 3 bars of the day):
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Bar 1: TP = (101+99+100)/3 = 100.00, Vol = 10,000 -> cumTP*V = 1,000,000
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Bar 2: TP = (102+100+101)/3 = 101.00, Vol = 15,000 -> cumTP*V = 2,515,000
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Bar 3: TP = (103+101+102)/3 = 102.00, Vol = 8,000 -> cumTP*V = 3,331,000
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Cumulative Volume = 33,000
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VWAP = 3,331,000 / 33,000 = 100.94
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```
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**Usage:**
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- **Institutional benchmark**: If price > VWAP, buyers dominate; price < VWAP, sellers dominate
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- **Intraday S/R**: VWAP acts as dynamic support in uptrends, resistance in downtrends
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- **Entry filter**: Buy only when price pulls back to VWAP (not chasing extended moves)
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- **Standard deviations**: VWAP +1/-1 and +2/-2 StdDev bands serve as profit targets
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- **Resets daily**: Do NOT carry VWAP across sessions — it is an intraday metric
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---
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### Moving Averages
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```
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SMA(N) = (Close_1 + Close_2 + ... + Close_N) / N
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EMA(N) = Close * (2/(N+1)) + PrevEMA * (1 - 2/(N+1))
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Key Moving Averages:
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EMA(9) — very short-term trend (scalping, day trading)
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EMA(20) — short-term trend
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EMA(50) — medium-term trend
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SMA(100) — intermediate trend
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SMA(200) — long-term trend (institutional benchmark)
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```
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**Critical Cross Signals:**
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| Cross | Name | Meaning | Reliability |
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|-------|------|---------|-------------|
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| 50 MA > 200 MA | Golden Cross | Bullish trend reversal | High (lag ~2 weeks) |
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| 50 MA < 200 MA | Death Cross | Bearish trend reversal | High (lag ~2 weeks) |
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| 9 EMA > 21 EMA | Fast bullish cross | Short-term momentum shift | Moderate |
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| Price > 200 SMA | Above long-term trend | Bullish regime | Very High |
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| Price < 200 SMA | Below long-term trend | Bearish regime | Very High |
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**Moving Average Ribbon** (20/50/100/200 MAs all fanning out): Indicates a very strong trend. When all are stacked in order (20 > 50 > 100 > 200 for uptrend), the trend is highly reliable.
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---
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### ATR (Average True Range)
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```
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True Range = max(High - Low, |High - PrevClose|, |Low - PrevClose|)
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ATR(14) = Simple or Wilder Moving Average of True Range over 14 periods
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Worked example:
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Today: High = 105, Low = 101, PrevClose = 102
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TR = max(105-101, |105-102|, |101-102|) = max(4, 3, 1) = 4
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If ATR(14) was 3.50 yesterday:
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ATR(14) = (3.50 * 13 + 4) / 14 = (45.50 + 4) / 14 = 3.536
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```
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**Practical Applications:**
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| Use Case | Formula | Example |
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|----------|---------|---------|
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| Stop-loss placement | Entry - 2 * ATR | Entry $100, ATR $2.50 -> Stop at $95.00 |
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| Take-profit target | Entry + 3 * ATR | Entry $100, ATR $2.50 -> Target $107.50 |
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| Position sizing | Risk$ / ATR | $200 risk / $2.50 ATR = 80 shares |
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| Volatility filter | ATR > threshold | Only trade when ATR > daily average (avoid dead markets) |
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| Trailing stop | Highest close - 3 * ATR | Locks in profit as price rises |
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---
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### Volume Analysis
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```
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OBV (On-Balance Volume):
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If Close > PrevClose: OBV = PrevOBV + Volume
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If Close < PrevClose: OBV = PrevOBV - Volume
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If Close = PrevClose: OBV = PrevOBV
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Volume Rate of Change: VROC = (Volume - Volume_N_ago) / Volume_N_ago * 100
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```
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**Volume Confirmation Rules:**
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| Price Action | Volume | Interpretation |
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|-------------|--------|----------------|
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| Price up | Volume up | Strong bullish — legitimate move |
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| Price up | Volume down | Weak rally — likely to reverse |
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| Price down | Volume up | Strong bearish — capitulation or breakdown |
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| Price down | Volume down | Weak decline — may be nearing bottom |
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| Breakout | Volume > 150% of 20-day avg | Confirmed breakout — take the trade |
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| Breakout | Volume < average | Failed breakout likely — wait or fade |
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| Volume climax | Extreme volume spike (3x+ average) | Potential exhaustion/reversal point |
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---
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### Support & Resistance
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**Fibonacci Retracement Levels:**
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```
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After a move from Low (L) to High (H):
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23.6% level = H - (H - L) * 0.236
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38.2% level = H - (H - L) * 0.382
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50.0% level = H - (H - L) * 0.500
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61.8% level = H - (H - L) * 0.618 (Golden Ratio — strongest level)
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78.6% level = H - (H - L) * 0.786
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Worked example (move from $80 to $120):
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Range = $40
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23.6% = 120 - 40 * 0.236 = 120 - 9.44 = $110.56
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38.2% = 120 - 40 * 0.382 = 120 - 15.28 = $104.72
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50.0% = 120 - 40 * 0.500 = 120 - 20.00 = $100.00
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61.8% = 120 - 40 * 0.618 = 120 - 24.72 = $95.28 (most likely bounce)
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78.6% = 120 - 40 * 0.786 = 120 - 31.44 = $88.56
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```
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**Pivot Points (Standard):**
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```
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PP = (High + Low + Close) / 3
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S1 = 2 * PP - High
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S2 = PP - (High - Low)
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R1 = 2 * PP - Low
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R2 = PP + (High - Low)
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Worked example (prev day: High=155, Low=148, Close=152):
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PP = (155 + 148 + 152) / 3 = 151.67
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S1 = 2 * 151.67 - 155 = 148.33
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S2 = 151.67 - (155 - 148) = 144.67
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R1 = 2 * 151.67 - 148 = 155.33
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R2 = 151.67 + (155 - 148) = 158.67
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```
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---
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## 2. Candlestick Patterns
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### Single-Candle Patterns
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| Pattern | Signal | Body | Wicks | Context Required |
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|---------|--------|------|-------|------------------|
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| Doji | Indecision | Open = Close (or nearly) | Long both sides | At S/R level = reversal |
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| Hammer | Bullish reversal | Small, at top of candle | Lower wick > 2x body | Must appear at bottom of downtrend |
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| Inverted Hammer | Bullish reversal | Small, at bottom of candle | Upper wick > 2x body | At bottom of downtrend, needs confirmation |
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| Shooting Star | Bearish reversal | Small, at bottom of candle | Upper wick > 2x body | Must appear at top of uptrend |
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| Hanging Man | Bearish reversal | Small, at top of candle | Lower wick > 2x body | At top of uptrend (same shape as Hammer) |
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| Marubozu (Bullish) | Strong continuation | Full green body, no wicks | None | Strong buying pressure |
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| Marubozu (Bearish) | Strong continuation | Full red body, no wicks | None | Strong selling pressure |
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| Spinning Top | Indecision | Small body centered | Equal wicks both sides | Trend may be losing steam |
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| Dragonfly Doji | Bullish reversal | Open = Close = High | Long lower wick only | At support = strong reversal signal |
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| Gravestone Doji | Bearish reversal | Open = Close = Low | Long upper wick only | At resistance = strong reversal signal |
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### Multi-Candle Patterns
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| Pattern | Signal | Description | Reliability |
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|---------|--------|-------------|-------------|
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| Bullish Engulfing | Reversal up | Large green candle fully engulfs prior red candle | High at support |
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| Bearish Engulfing | Reversal down | Large red candle fully engulfs prior green candle | High at resistance |
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| Morning Star | Bullish reversal | Red candle, small body/doji with gap, large green candle | Very High |
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| Evening Star | Bearish reversal | Green candle, small body/doji with gap, large red candle | Very High |
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| Three White Soldiers | Strong bullish | Three consecutive large green candles, each closing higher | Very High |
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| Three Black Crows | Strong bearish | Three consecutive large red candles, each closing lower | Very High |
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| Bullish Harami | Potential reversal | Large red, then small green contained within red's body | Moderate (needs confirmation) |
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| Bearish Harami | Potential reversal | Large green, then small red contained within green's body | Moderate (needs confirmation) |
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| Tweezer Bottom | Bullish reversal | Two candles with matching lows at support | High |
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| Tweezer Top | Bearish reversal | Two candles with matching highs at resistance | High |
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| Piercing Line | Bullish reversal | Red candle, then green opens below red's low and closes above 50% of red's body | Moderate-High |
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| Dark Cloud Cover | Bearish reversal | Green candle, then red opens above green's high and closes below 50% of green's body | Moderate-High |
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---
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## 3. Risk Management Formulas
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### Position Sizing (Fixed Fractional)
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```
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Position Size (shares) = Account Risk Amount / (Entry Price - Stop Loss Price)
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Account Risk Amount = Portfolio Value * Risk Per Trade %
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RULE: Never risk more than 1-2% of portfolio on a single trade.
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Worked example:
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Portfolio Value = $10,000
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Risk Per Trade = 2% ($200)
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Entry Price = $100.00
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Stop Loss = $95.00 (based on 2x ATR below entry)
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Risk per share = $100.00 - $95.00 = $5.00
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Position Size = $200 / $5.00 = 40 shares
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Position Value = 40 * $100 = $4,000 (40% of portfolio)
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CONCENTRATION CHECK: If position value > 10% of portfolio, reduce size.
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Adjusted: max position = $1,000 / $100 = 10 shares
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Adjusted risk = 10 * $5.00 = $50 (only 0.5% of portfolio — acceptable)
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```
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### Kelly Criterion (Optimal Bet Size)
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```
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Kelly % = W - ((1 - W) / R)
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Where:
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W = win rate (decimal)
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R = average win / average loss ratio (reward-to-risk)
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Worked example:
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Win rate: 60% (W = 0.60)
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Average win: $300, Average loss: $200
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R = 300 / 200 = 1.5
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Kelly = 0.60 - (0.40 / 1.5) = 0.60 - 0.267 = 0.333 (33.3%)
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Full Kelly is too aggressive for real trading. Use fractions:
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Half-Kelly = 0.333 / 2 = 16.7% of portfolio per trade
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Quarter-Kelly = 0.333 / 4 = 8.3% of portfolio per trade (recommended)
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If Kelly is negative, the system has NEGATIVE expectancy — do not trade it.
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```
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### Value at Risk (VaR)
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```
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Parametric VaR = Portfolio Value * Portfolio Volatility * Z-score * sqrt(Time Horizon)
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Z-scores: 90% confidence = 1.282
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95% confidence = 1.645
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99% confidence = 2.326
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Worked example (daily VaR, 95% confidence):
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Portfolio = $10,000
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Daily volatility (stddev of daily returns) = 2.0%
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VaR = $10,000 * 0.02 * 1.645 * sqrt(1) = $329.00
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Meaning: 95% confident daily loss will not exceed $329.
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Weekly VaR = $329 * sqrt(5) = $329 * 2.236 = $735.65
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Monthly VaR = $329 * sqrt(21) = $329 * 4.583 = $1,507.81
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```
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### Sharpe Ratio
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```
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Sharpe = (Rp - Rf) / StdDev(Rp) * sqrt(252)
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Where:
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Rp = mean daily portfolio return
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Rf = daily risk-free rate (Treasury yield / 252)
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StdDev(Rp) = standard deviation of daily returns
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252 = trading days per year (annualization factor)
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Worked example:
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Mean daily return = 0.10% (0.001)
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Annual Treasury yield = 5.0% -> daily Rf = 0.05/252 = 0.000198
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StdDev of daily returns = 0.80% (0.008)
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Daily Sharpe = (0.001 - 0.000198) / 0.008 = 0.100
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Annualized Sharpe = 0.100 * sqrt(252) = 0.100 * 15.875 = 1.59
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Ratings:
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< 0.5 = Poor (not compensated for risk)
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0.5-1.0 = Acceptable
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1.0-2.0 = Good
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2.0-3.0 = Very Good
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> 3.0 = Excellent (verify — may indicate overfitting)
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```
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### Sortino Ratio (Downside-Only Risk)
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```
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Sortino = (Rp - Rf) / DownsideDeviation * sqrt(252)
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DownsideDeviation = sqrt(mean(min(Ri - Rf, 0)^2))
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Better than Sharpe because it only penalizes downside volatility, not upside.
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Sortino > 2.0 is considered very good.
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```
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### Maximum Drawdown
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```
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For each point t in equity curve:
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Peak(t) = max(Equity[0..t])
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Drawdown(t) = (Peak(t) - Equity(t)) / Peak(t) * 100%
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MaxDrawdown = max(Drawdown(t)) for all t
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Worked example:
|
||||
Equity curve: $10,000 -> $12,000 -> $9,600 -> $11,500
|
||||
Peak at $12,000
|
||||
Drawdown at $9,600 = (12,000 - 9,600) / 12,000 = 20.0%
|
||||
Max Drawdown = 20.0%
|
||||
|
||||
Recovery Factor = Total Net Profit / Max Drawdown
|
||||
If total profit = $3,000, MaxDD = $2,400 -> RF = 3,000/2,400 = 1.25
|
||||
|
||||
Calmar Ratio = Annual Return / Max Drawdown
|
||||
If annual return = 25%, MaxDD = 20% -> Calmar = 1.25 (target > 1.0)
|
||||
```
|
||||
|
||||
### Profit Factor
|
||||
```
|
||||
Profit Factor = Gross Winning Trades / Gross Losing Trades
|
||||
|
||||
Worked example:
|
||||
10 winning trades totaling $5,000
|
||||
8 losing trades totaling $3,200
|
||||
Profit Factor = 5,000 / 3,200 = 1.5625
|
||||
|
||||
Ratings: < 1.0 = losing system, 1.0-1.5 = marginal, 1.5-2.0 = good,
|
||||
2.0-3.0 = very good, > 3.0 = excellent (verify with enough trades)
|
||||
```
|
||||
|
||||
### Expectancy Per Trade
|
||||
```
|
||||
Expectancy = (Win% * AvgWin) - (Loss% * AvgLoss)
|
||||
|
||||
Worked example:
|
||||
Win rate: 55%, Average win: $150, Average loss: $100
|
||||
Expectancy = (0.55 * 150) - (0.45 * 100) = 82.50 - 45.00 = $37.50/trade
|
||||
Over 100 trades: expected profit = $3,750
|
||||
|
||||
Minimum for a viable system: Expectancy > 0 with at least 30 sample trades.
|
||||
```
|
||||
|
||||
### Risk/Reward Ratio
|
||||
```
|
||||
R:R = (Target Price - Entry Price) / (Entry Price - Stop Loss Price)
|
||||
|
||||
Worked example:
|
||||
Entry = $100, Stop = $95, Target = $112
|
||||
R:R = (112 - 100) / (100 - 95) = 12 / 5 = 2.4:1
|
||||
|
||||
Minimum acceptable R:R = 1.5:1
|
||||
With 40% win rate and 2:1 R:R: Expectancy = 0.40*2 - 0.60*1 = +0.20 (profitable!)
|
||||
With 40% win rate and 1:1 R:R: Expectancy = 0.40*1 - 0.60*1 = -0.20 (losing!)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 4. Alpaca Trading API Reference
|
||||
|
||||
### Authentication
|
||||
```bash
|
||||
# Paper trading (ALWAYS start here)
|
||||
BASE_URL="https://paper-api.alpaca.markets"
|
||||
|
||||
# Live trading (only after paper validation)
|
||||
# BASE_URL="https://api.alpaca.markets"
|
||||
|
||||
# Data API (same for both paper and live)
|
||||
DATA_URL="https://data.alpaca.markets"
|
||||
|
||||
# Auth headers (required on every request)
|
||||
HEADERS="-H 'APCA-API-KEY-ID: $ALPACA_API_KEY' -H 'APCA-API-SECRET-KEY: $ALPACA_SECRET_KEY'"
|
||||
```
|
||||
|
||||
### Account Information
|
||||
```bash
|
||||
# Get account details
|
||||
curl -s "$BASE_URL/v2/account" $HEADERS
|
||||
# Key fields: id, status, equity, cash, buying_power, portfolio_value,
|
||||
# pattern_day_trader (bool), daytrade_count, last_equity
|
||||
```
|
||||
|
||||
### Get Current Positions
|
||||
```bash
|
||||
# All positions
|
||||
curl -s "$BASE_URL/v2/positions" $HEADERS
|
||||
# Returns array: symbol, qty, side, avg_entry_price, current_price,
|
||||
# unrealized_pl, unrealized_plpc, market_value, cost_basis
|
||||
|
||||
# Single position
|
||||
curl -s "$BASE_URL/v2/positions/AAPL" $HEADERS
|
||||
```
|
||||
|
||||
### Place Orders
|
||||
```bash
|
||||
# Market order (fills immediately at best available price)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"symbol":"AAPL","qty":"10","side":"buy","type":"market","time_in_force":"day"}'
|
||||
|
||||
# Limit order (fills only at your price or better)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"symbol":"AAPL","qty":"10","side":"buy","type":"limit","time_in_force":"gtc","limit_price":"150.00"}'
|
||||
|
||||
# Stop order (triggers market order when stop price hit)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"symbol":"AAPL","qty":"10","side":"sell","type":"stop","time_in_force":"gtc","stop_price":"145.00"}'
|
||||
|
||||
# Stop-limit order (triggers limit order when stop price hit)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"symbol":"AAPL","qty":"10","side":"sell","type":"stop_limit","time_in_force":"gtc","stop_price":"145.00","limit_price":"144.50"}'
|
||||
|
||||
# Trailing stop (dynamic stop that trails price by dollar or percent amount)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"symbol":"AAPL","qty":"10","side":"sell","type":"trailing_stop","time_in_force":"gtc","trail_percent":"5"}'
|
||||
|
||||
# Bracket order (entry + stop loss + take profit as one atomic order)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"symbol": "AAPL",
|
||||
"qty": "10",
|
||||
"side": "buy",
|
||||
"type": "limit",
|
||||
"time_in_force": "day",
|
||||
"limit_price": "150.00",
|
||||
"order_class": "bracket",
|
||||
"stop_loss": {"stop_price": "145.00"},
|
||||
"take_profit": {"limit_price": "165.00"}
|
||||
}'
|
||||
|
||||
# OCO order (one-cancels-other: stop loss OR take profit, whichever hits first)
|
||||
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"symbol": "AAPL",
|
||||
"qty": "10",
|
||||
"side": "sell",
|
||||
"type": "limit",
|
||||
"time_in_force": "gtc",
|
||||
"limit_price": "165.00",
|
||||
"order_class": "oco",
|
||||
"stop_loss": {"stop_price": "145.00"}
|
||||
}'
|
||||
```
|
||||
|
||||
**Order parameters reference:**
|
||||
| Parameter | Values | Notes |
|
||||
|-----------|--------|-------|
|
||||
| `side` | `buy`, `sell` | |
|
||||
| `type` | `market`, `limit`, `stop`, `stop_limit`, `trailing_stop` | |
|
||||
| `time_in_force` | `day`, `gtc`, `ioc`, `fok` | day = cancel at close, gtc = good til canceled |
|
||||
| `order_class` | `simple`, `bracket`, `oco`, `oto` | bracket = entry + stop + target |
|
||||
| `qty` | String number | Whole shares for stocks |
|
||||
| `notional` | String dollar amount | Alternative to qty (fractional shares) |
|
||||
|
||||
### Manage Orders
|
||||
```bash
|
||||
# List open orders
|
||||
curl -s "$BASE_URL/v2/orders?status=open" $HEADERS
|
||||
|
||||
# Get specific order
|
||||
curl -s "$BASE_URL/v2/orders/{order_id}" $HEADERS
|
||||
|
||||
# Cancel specific order
|
||||
curl -s -X DELETE "$BASE_URL/v2/orders/{order_id}" $HEADERS
|
||||
|
||||
# Cancel ALL open orders
|
||||
curl -s -X DELETE "$BASE_URL/v2/orders" $HEADERS
|
||||
```
|
||||
|
||||
### Close Positions
|
||||
```bash
|
||||
# Close entire position in a symbol
|
||||
curl -s -X DELETE "$BASE_URL/v2/positions/AAPL" $HEADERS
|
||||
|
||||
# Partially close (sell 5 of 10 shares)
|
||||
curl -s -X DELETE "$BASE_URL/v2/positions/AAPL?qty=5" $HEADERS
|
||||
|
||||
# EMERGENCY: Close ALL positions
|
||||
curl -s -X DELETE "$BASE_URL/v2/positions" $HEADERS
|
||||
```
|
||||
|
||||
### Market Data (free with Alpaca account)
|
||||
```bash
|
||||
# Latest quote (bid/ask)
|
||||
curl -s "$DATA_URL/v2/stocks/AAPL/quotes/latest" $HEADERS
|
||||
|
||||
# Latest trade (last fill)
|
||||
curl -s "$DATA_URL/v2/stocks/AAPL/trades/latest" $HEADERS
|
||||
|
||||
# Historical bars (OHLCV) — daily
|
||||
curl -s "$DATA_URL/v2/stocks/AAPL/bars?timeframe=1Day&start=2024-01-01&limit=100" $HEADERS
|
||||
|
||||
# Intraday bars — 5-minute
|
||||
curl -s "$DATA_URL/v2/stocks/AAPL/bars?timeframe=5Min&start=$(date -d 'today' +%Y-%m-%d)&limit=78" $HEADERS
|
||||
|
||||
# Multi-symbol snapshot
|
||||
curl -s "$DATA_URL/v2/stocks/snapshots?symbols=AAPL,MSFT,GOOGL" $HEADERS
|
||||
|
||||
# Crypto bars
|
||||
curl -s "$DATA_URL/v1beta3/crypto/us/bars?symbols=BTC/USD&timeframe=1Day&limit=30" $HEADERS
|
||||
|
||||
# Crypto latest quote
|
||||
curl -s "$DATA_URL/v1beta3/crypto/us/latest/quotes?symbols=BTC/USD,ETH/USD" $HEADERS
|
||||
```
|
||||
|
||||
### Market Clock & Calendar
|
||||
```bash
|
||||
# Is market open right now?
|
||||
curl -s "$BASE_URL/v2/clock" $HEADERS
|
||||
# Returns: timestamp, is_open (bool), next_open, next_close
|
||||
|
||||
# Upcoming market calendar
|
||||
curl -s "$BASE_URL/v2/calendar?start=$(date +%Y-%m-%d)&end=$(date -d '+7 days' +%Y-%m-%d)" $HEADERS
|
||||
```
|
||||
|
||||
### Crypto Trading Notes
|
||||
- Symbols use slash format: `BTC/USD`, `ETH/USD`, `SOL/USD`, `DOGE/USD`
|
||||
- 24/7 trading (no market hours restriction)
|
||||
- Fractional quantities allowed (e.g., `"qty": "0.001"` for BTC)
|
||||
- Paper trading works identically to live
|
||||
- Use `notional` for dollar-based crypto orders: `"notional": "100.00"` buys $100 worth
|
||||
|
||||
### Account Activity & History
|
||||
```bash
|
||||
# Trade history
|
||||
curl -s "$BASE_URL/v2/account/activities/FILL?after=2024-01-01" $HEADERS
|
||||
|
||||
# Portfolio history
|
||||
curl -s "$BASE_URL/v2/account/portfolio/history?period=1M&timeframe=1D" $HEADERS
|
||||
# Returns: timestamp[], equity[], profit_loss[], profit_loss_pct[]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 5. Free Financial Data Sources
|
||||
|
||||
### Price Data (via web_search + web_fetch)
|
||||
| Source | URL Pattern | Data Available |
|
||||
|--------|-------------|----------------|
|
||||
| Yahoo Finance | `finance.yahoo.com/quote/AAPL` | Realtime quotes, charts, financials, analyst ratings |
|
||||
| Google Finance | `google.com/finance/quote/AAPL:NASDAQ` | Quotes, news, related stocks, earnings |
|
||||
| CoinGecko | `coingecko.com/en/coins/bitcoin` | Crypto prices, market cap, volume, 24h change |
|
||||
| CoinMarketCap | `coinmarketcap.com/currencies/bitcoin/` | Crypto prices, rankings, dominance, supply |
|
||||
| MarketWatch | `marketwatch.com/investing/stock/AAPL` | Quotes, news, analysis, options data |
|
||||
| Finviz | `finviz.com/quote.ashx?t=AAPL` | Technical + fundamental screener, charts |
|
||||
| TradingView | `tradingview.com/symbols/NASDAQ-AAPL/` | Charts, technicals, community ideas |
|
||||
|
||||
### Fundamental Data
|
||||
| Source | URL Pattern | Data Available |
|
||||
|--------|-------------|----------------|
|
||||
| Macrotrends | `macrotrends.net/stocks/charts/AAPL/apple/pe-ratio` | P/E, revenue, margins, historical |
|
||||
| Simply Wall St | Web search: `"AAPL simply wall st"` | Visual fundamental analysis, fair value |
|
||||
| SEC EDGAR | `sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=AAPL&type=10-K` | Official 10-K, 10-Q, 8-K filings |
|
||||
| Earnings Whispers | `earningswhispers.com/stocks/AAPL` | Earnings estimates, surprise history, calendar |
|
||||
| Stock Analysis | `stockanalysis.com/stocks/AAPL/financials/` | Clean financial statements, ratios |
|
||||
| Wisesheets | Web search: `"AAPL income statement"` | Financial data in spreadsheet format |
|
||||
|
||||
### Sentiment & Alternative Data
|
||||
| Source | URL | Data Available |
|
||||
|--------|-----|----------------|
|
||||
| CNN Fear & Greed | `money.cnn.com/data/fear-and-greed/` | Market sentiment index 0-100 (Extreme Fear to Extreme Greed) |
|
||||
| CBOE VIX | Web search: `"VIX index today"` | Volatility index (>30 = fear, <15 = complacency) |
|
||||
| Finviz Map | `finviz.com/map.ashx` | Market heatmap by sector/size |
|
||||
| StockTwits | `stocktwits.com/symbol/AAPL` | Social sentiment (bullish/bearish ratio) |
|
||||
| Put/Call Ratio | Web search: `"CBOE put call ratio today"` | Options sentiment (>1.0 = bearish, <0.7 = bullish) |
|
||||
| Short Interest | `finviz.com/quote.ashx?t=AAPL` -> Short Float | Percent of float sold short |
|
||||
| Insider Trading | `openinsider.com/screener` | CEO/CFO buy/sell patterns |
|
||||
|
||||
### Macro Economic Data
|
||||
| Source | URL | Data Available |
|
||||
|--------|-----|----------------|
|
||||
| FRED | `fred.stlouisfed.org` | Interest rates, CPI, employment, GDP, M2, yield curve |
|
||||
| Treasury.gov | `treasury.gov/resource-center/data-chart-center/interest-rates/` | Daily Treasury yield curve |
|
||||
| CME FedWatch | Web search: `"CME FedWatch tool"` | Federal funds rate probabilities |
|
||||
| BLS | `bls.gov/news.release/` | Employment situation, CPI, PPI |
|
||||
| ISM | Web search: `"ISM manufacturing PMI"` | PMI (>50 = expansion, <50 = contraction) |
|
||||
| Conference Board | Web search: `"consumer confidence index"` | Consumer confidence, leading indicators |
|
||||
| Earnings Calendar | `earningswhispers.com/calendar` | Upcoming earnings dates |
|
||||
| Economic Calendar | Web search: `"economic calendar this week"` | Scheduled data releases |
|
||||
|
||||
### Crypto-Specific Sources
|
||||
| Source | URL | Data Available |
|
||||
|--------|-----|----------------|
|
||||
| CoinGecko | `coingecko.com` | Prices, market cap, volume, DeFi TVL |
|
||||
| DefiLlama | `defillama.com` | Total Value Locked across all chains |
|
||||
| Glassnode (free tier) | Web search: `"bitcoin on-chain metrics"` | On-chain analytics (NUPL, MVRV, exchange flows) |
|
||||
| Bitcoin Fear & Greed | `alternative.me/crypto/fear-and-greed-index/` | Crypto-specific sentiment 0-100 |
|
||||
| Ultrasound Money | `ultrasound.money` | ETH supply/burn metrics |
|
||||
|
||||
---
|
||||
|
||||
## 6. Confidence Calibration Guide (Superforecasting)
|
||||
|
||||
### Calibration Principles (Philip Tetlock)
|
||||
- A "70% confident" prediction should be right about 70% of the time
|
||||
- Most people are overconfident: their "90%" predictions are right only ~70%
|
||||
- Track your predictions systematically and compare predicted vs actual frequency
|
||||
- Update incrementally (2-5% per new piece of evidence), not dramatically
|
||||
|
||||
### Confidence Level Guide
|
||||
| Level | Meaning | Evidence Required | Trading Action |
|
||||
|-------|---------|-------------------|----------------|
|
||||
| 20-30% | Slight lean | Single weak signal, limited data | No trade — insufficient edge |
|
||||
| 40-50% | Toss-up with slight edge | Conflicting signals, moderate evidence | No trade — coin flip |
|
||||
| 55-65% | Moderate conviction | Multiple aligned signals, historical precedent | Small position, wide stops |
|
||||
| 70-80% | Strong conviction | Strong multi-factor alignment, catalyst identified | Standard position size |
|
||||
| 85-95% | Very high conviction | Overwhelming evidence — be suspicious of yourself | Full position, but NEVER all-in |
|
||||
|
||||
### Brier Score for Trade Predictions
|
||||
```
|
||||
Brier Score = mean((predicted_probability - actual_outcome)^2)
|
||||
actual_outcome: 1 if prediction was correct, 0 if wrong
|
||||
|
||||
Worked example (5 predictions):
|
||||
Pred 1: 80% confident -> correct (1) -> (0.80 - 1)^2 = 0.04
|
||||
Pred 2: 60% confident -> wrong (0) -> (0.60 - 0)^2 = 0.36
|
||||
Pred 3: 70% confident -> correct (1) -> (0.70 - 1)^2 = 0.09
|
||||
Pred 4: 90% confident -> correct (1) -> (0.90 - 1)^2 = 0.01
|
||||
Pred 5: 55% confident -> wrong (0) -> (0.55 - 0)^2 = 0.30
|
||||
Brier Score = (0.04 + 0.36 + 0.09 + 0.01 + 0.30) / 5 = 0.16
|
||||
|
||||
Ratings: 0.00 = perfect, < 0.15 = excellent, 0.15-0.25 = good,
|
||||
0.25 = coin flip, > 0.25 = worse than random
|
||||
```
|
||||
|
||||
### Calibration Self-Check Protocol
|
||||
After accumulating 20+ trade predictions, group by confidence bucket:
|
||||
1. Are your 60% predictions right ~60% of the time?
|
||||
2. If your 60% predictions are right 80% of the time, you are underconfident — adjust up
|
||||
3. If your 80% predictions are right 55% of the time, you are overconfident — adjust down
|
||||
4. Recalibrate your confidence scale after every 50 resolved predictions
|
||||
|
||||
---
|
||||
|
||||
## 7. Trading Psychology & Cognitive Biases
|
||||
|
||||
### Biases to Watch For
|
||||
| Bias | Description | Mitigation |
|
||||
|------|-------------|------------|
|
||||
| **Confirmation Bias** | Seeking info that confirms your thesis | Always build the opposing case first (adversarial debate) |
|
||||
| **Anchoring** | Over-weighting the first number you see (entry price, analyst target) | Start analysis from base rates and current data, not old prices |
|
||||
| **Recency Bias** | Over-weighting recent events (last week's crash, last month's rally) | Look at longer timeframes — 6-month and 1-year charts minimum |
|
||||
| **Loss Aversion** | Holding losers too long ("it'll come back"), cutting winners too fast | Use mechanical stop-losses and take-profit targets, set BEFORE entry |
|
||||
| **Overconfidence** | Believing you are more right than you are | Track Brier scores, use Kelly fractions, never bet > 2% per trade |
|
||||
| **Narrative Bias** | Compelling story = good trade (often false) | Focus on quantitative data, not stories. "Good company" != "good trade" |
|
||||
| **FOMO** | Fear of missing out, chasing entries | Only enter at planned levels. The market is open 252 days a year |
|
||||
| **Sunk Cost** | "I've lost so much, I can't sell now" | Each moment is a new decision. Ask: "Would I enter this trade NOW at current price?" |
|
||||
| **Hindsight Bias** | "I knew that would happen" | Journal BEFORE trades with specific predictions, not after |
|
||||
| **Disposition Effect** | Selling winners early to "lock in profits" but holding losers | Let winners run (trail stops), cut losers at planned stops |
|
||||
| **Gambler's Fallacy** | "It's dropped 5 days in a row, it HAS to bounce" | Each day is independent. Trends persist more often than they reverse |
|
||||
| **Endowment Effect** | Overvaluing positions you already own | Evaluate positions as if you were building from scratch today |
|
||||
|
||||
### Discipline Rules
|
||||
1. Every trade has a written plan BEFORE entry: entry price, stop loss, target, position size, thesis
|
||||
2. Write down your reasoning BEFORE entering — if you cannot articulate the edge, do not trade
|
||||
3. Set stop-losses at order entry time, not "in your head"
|
||||
4. Review your journal weekly — look for patterns in wins AND losses
|
||||
5. Take breaks after big wins (overconfidence risk) AND big losses (emotional risk)
|
||||
6. Never average down on a losing position unless the original thesis explicitly planned for it
|
||||
7. Never move a stop-loss further away from your entry (only tighten, never widen)
|
||||
8. The market will be there tomorrow — missing a trade is not a loss, but a blown account is
|
||||
|
||||
---
|
||||
|
||||
## 8. Portfolio Construction
|
||||
|
||||
### Asset Allocation Guidelines
|
||||
| Style | Equities | Crypto | Fixed Income / Cash | Max Single Position |
|
||||
|-------|----------|--------|---------------------|---------------------|
|
||||
| Conservative | 50-60% | 0-5% | 35-50% | 5% |
|
||||
| Moderate | 60-75% | 5-15% | 10-35% | 8% |
|
||||
| Aggressive | 70-85% | 10-25% | 5-20% | 10% |
|
||||
| Speculative | 50-70% | 20-40% | 5-10% | 15% (with strict stops) |
|
||||
|
||||
### Sector Diversification
|
||||
Maximum 30% in any single sector:
|
||||
- Technology, Healthcare, Financials, Consumer Discretionary, Consumer Staples
|
||||
- Energy, Industrials, Utilities, Real Estate, Materials, Communication Services
|
||||
|
||||
### Correlation Awareness
|
||||
Highly correlated positions amplify risk. Check correlations before adding:
|
||||
| Pair | Typical Correlation | Risk |
|
||||
|------|---------------------|------|
|
||||
| AAPL + MSFT + GOOGL | 0.7-0.9 | Concentrated large-cap tech |
|
||||
| BTC + ETH + SOL | 0.8-0.95 | Concentrated crypto (moves together) |
|
||||
| SPY + QQQ | 0.9+ | Nearly identical exposure |
|
||||
| Stocks + Bonds | -0.2 to 0.3 | Genuinely diversifying |
|
||||
| Gold + Stocks | -0.1 to 0.2 | Hedge in crisis |
|
||||
| VIX + SPY | -0.8 | Inverse — VIX as hedge |
|
||||
|
||||
### Rebalancing Rules
|
||||
- **Calendar**: Rebalance quarterly (first trading day of quarter)
|
||||
- **Threshold**: Rebalance when any allocation drifts > 5% from target
|
||||
- **Tax-aware**: Prefer rebalancing via new contributions rather than selling (taxable accounts)
|
||||
|
||||
---
|
||||
|
||||
## 9. Cross-Platform Commands
|
||||
|
||||
### Windows (PowerShell / Git Bash)
|
||||
```bash
|
||||
# Python might be `python` not `python3` on Windows
|
||||
python -c "import json; ..."
|
||||
|
||||
# Use forward slashes in file paths or escape backslashes
|
||||
# curl is available via Git Bash, PowerShell, or WSL
|
||||
|
||||
# Check if market is open (Windows Git Bash)
|
||||
curl -s "$BASE_URL/v2/clock" -H "APCA-API-KEY-ID: $ALPACA_API_KEY" \
|
||||
-H "APCA-API-SECRET-KEY: $ALPACA_SECRET_KEY" | python -c "
|
||||
import sys, json
|
||||
d = json.load(sys.stdin)
|
||||
print('OPEN' if d['is_open'] else 'CLOSED', '| Next:', d.get('next_open','') or d.get('next_close',''))
|
||||
"
|
||||
```
|
||||
|
||||
### macOS / Linux
|
||||
```bash
|
||||
python3 -c "import json; ..."
|
||||
# curl, jq typically available by default
|
||||
# Use jq for JSON processing:
|
||||
curl -s URL | jq '.equity'
|
||||
```
|
||||
|
||||
### JSON Processing Without jq
|
||||
```bash
|
||||
# Pretty-print JSON
|
||||
python3 -c "import sys,json; print(json.dumps(json.load(sys.stdin),indent=2))" < file.json
|
||||
|
||||
# Extract specific field
|
||||
curl -s URL | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['equity'])"
|
||||
|
||||
# Parse Alpaca positions into readable table
|
||||
curl -s "$BASE_URL/v2/positions" $HEADERS | python3 -c "
|
||||
import sys, json
|
||||
positions = json.load(sys.stdin)
|
||||
fmt = '{:<8} {:>6} {:>10} {:>10} {:>12} {:>8}'
|
||||
print(fmt.format('Symbol','Qty','Entry','Current','P/L','P/L pct'))
|
||||
print('-' * 60)
|
||||
for p in positions:
|
||||
print(fmt.format(p['symbol'], p['qty'], float(p['avg_entry_price']),
|
||||
float(p['current_price']), float(p['unrealized_pl']),
|
||||
round(float(p['unrealized_plpc'])*100,2)))
|
||||
"
|
||||
|
||||
# Calculate RSI from historical bars
|
||||
curl -s "$DATA_URL/v2/stocks/AAPL/bars?timeframe=1Day&limit=30" $HEADERS | python3 -c "
|
||||
import sys, json
|
||||
data = json.load(sys.stdin)
|
||||
closes = [float(b['c']) for b in data['bars']]
|
||||
changes = [closes[i]-closes[i-1] for i in range(1, len(closes))]
|
||||
gains = [max(c,0) for c in changes[-14:]]
|
||||
losses = [abs(min(c,0)) for c in changes[-14:]]
|
||||
avg_gain = sum(gains)/14
|
||||
avg_loss = sum(losses)/14
|
||||
rs = avg_gain/avg_loss if avg_loss > 0 else 999
|
||||
rsi = 100 - (100/(1+rs))
|
||||
print(f'RSI(14) = {rsi:.1f}')
|
||||
"
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 10. Pre-Trade Checklist
|
||||
|
||||
Before every trade, verify ALL of the following:
|
||||
|
||||
```
|
||||
PRE-TRADE CHECKLIST
|
||||
====================
|
||||
[ ] 1. TREND: What is the higher-timeframe trend? (Daily chart 200 SMA)
|
||||
- Trading WITH the trend? (preferred)
|
||||
- Counter-trend? (requires stronger signal + tighter stops)
|
||||
|
||||
[ ] 2. SIGNAL: What specific setup triggered this trade?
|
||||
- Indicator signal (RSI, MACD, etc.)
|
||||
- Pattern (candlestick, chart pattern)
|
||||
- Catalyst (earnings, news, sector rotation)
|
||||
|
||||
[ ] 3. ENTRY: Exact entry price or condition
|
||||
- Limit order at specific level? Market order on breakout?
|
||||
|
||||
[ ] 4. STOP LOSS: Exact stop price
|
||||
- Based on ATR (2-3x ATR from entry)
|
||||
- Below key support (long) or above key resistance (short)
|
||||
- NEVER wider than 2% of portfolio
|
||||
|
||||
[ ] 5. TARGET: Exact take-profit price
|
||||
- Risk/Reward at least 1.5:1 (preferably 2:1+)
|
||||
- At logical resistance (long) or support (short)
|
||||
|
||||
[ ] 6. POSITION SIZE: Calculated from risk management rules
|
||||
- Risk amount = Portfolio * 1-2%
|
||||
- Shares = Risk amount / (Entry - Stop)
|
||||
- Total position < 10% of portfolio
|
||||
|
||||
[ ] 7. CORRELATION CHECK: Does this overlap with existing positions?
|
||||
- Not adding to concentrated sector exposure
|
||||
- Total portfolio heat (sum of open risk) < 6%
|
||||
|
||||
[ ] 8. CATALYST CHECK: Any upcoming events that could gap through stops?
|
||||
- Earnings date? Fed meeting? CPI release?
|
||||
- If yes: reduce size or wait until after event
|
||||
|
||||
[ ] 9. MARKET CONTEXT: Is the overall market favorable?
|
||||
- Fear & Greed index level
|
||||
- VIX level (>30 = caution, <15 = complacency risk)
|
||||
- Market trend (SPY vs 200 SMA)
|
||||
|
||||
[ ] 10. CONFIDENCE: Rate 1-10 honestly
|
||||
- Below 6? Skip the trade
|
||||
- Record confidence for calibration tracking
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 11. Trade Journal Template
|
||||
|
||||
```json
|
||||
{
|
||||
"trade_id": "T001",
|
||||
"date_opened": "2025-01-15",
|
||||
"date_closed": null,
|
||||
"symbol": "AAPL",
|
||||
"side": "long",
|
||||
"entry_price": 150.00,
|
||||
"stop_loss": 145.00,
|
||||
"target": 162.00,
|
||||
"position_size": 40,
|
||||
"risk_amount": 200.00,
|
||||
"risk_reward": 2.4,
|
||||
"setup": "Bullish engulfing at 50 EMA + RSI divergence",
|
||||
"confidence": 7,
|
||||
"market_context": "SPY above 200 SMA, VIX at 18, F&G neutral (52)",
|
||||
"pre_trade_thesis": "AAPL pulled back to 50 EMA support, RSI showing bullish divergence, earnings in 3 weeks should provide catalyst. Sector (tech) is leading.",
|
||||
"result": {
|
||||
"exit_price": null,
|
||||
"exit_reason": null,
|
||||
"pnl": null,
|
||||
"pnl_percent": null,
|
||||
"held_days": null,
|
||||
"lessons": null
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Store trade journals using `memory_store` for tracking and calibration review.
|
||||
Reference in new issue
Block a user