| name | trader-hand-skill |
| version | 1.0.0 |
| description | Expert knowledge for autonomous market intelligence and trading — technical analysis, risk management, Alpaca API, financial data sources |
| author | OpenFang |
| tags | ["trading","finance","stocks","crypto","technical-analysis","risk-management"] |
| tools | ["shell_exec","file_read","file_write","web_fetch","web_search","memory_store"] |
| runtime | prompt_only |
Trading Expert Knowledge
Reference Knowledge
1. Technical Analysis Indicators Reference
RSI (Relative Strength Index)
Formula: RSI = 100 - (100 / (1 + RS))
Where: RS = Average Gain / Average Loss over N periods (default N = 14)
Step-by-step calculation:
1. For each period, compute change = Close(t) - Close(t-1)
2. Gains = max(change, 0), Losses = abs(min(change, 0))
3. First average: simple mean of first 14 gains/losses
4. Subsequent: AvgGain = (PrevAvgGain * 13 + CurrentGain) / 14 (Wilder smoothing)
5. RS = AvgGain / AvgLoss
6. RSI = 100 - (100 / (1 + RS))
Worked example (14-period):
Avg Gain over 14 periods = 1.02
Avg Loss over 14 periods = 0.68
RS = 1.02 / 0.68 = 1.50
RSI = 100 - (100 / (1 + 1.50)) = 100 - 40 = 60.0
Interpretation:
- RSI < 30: Oversold territory (potential buy signal)
- RSI > 70: Overbought territory (potential sell signal)
- RSI = 50: Neutral — price momentum balanced
Advanced RSI Signals:
| Signal | Description | Strength |
|---|
| Bearish divergence | Price makes new high, RSI makes lower high | Strong reversal warning |
| Bullish divergence | Price makes new low, RSI makes higher low | Strong reversal warning |
| Bullish failure swing | RSI drops below 30, bounces, pulls back above 30, breaks prior RSI high | Very strong buy |
| Bearish failure swing | RSI rises above 70, drops, bounces below 70, breaks prior RSI low | Very strong sell |
| Range shift | RSI oscillates 40-80 in uptrend, 20-60 in downtrend | Trend confirmation |
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.
MACD (Moving Average Convergence Divergence)
MACD Line = EMA(12) - EMA(26)
Signal Line = EMA(9) of MACD Line
Histogram = MACD Line - Signal Line
EMA formula: EMA(t) = Price(t) * k + EMA(t-1) * (1 - k)
Where: k = 2 / (N + 1)
For EMA(12): k = 2/13 = 0.1538
For EMA(26): k = 2/27 = 0.0741
Worked example:
EMA(12) = 155.20
EMA(26) = 152.80
MACD Line = 155.20 - 152.80 = 2.40
Previous Signal Line = 1.80
Signal Line = 2.40 * (2/10) + 1.80 * (8/10) = 0.48 + 1.44 = 1.92
Histogram = 2.40 - 1.92 = 0.48 (positive = bullish momentum increasing)
Interpretation:
| Signal | Condition | Strength |
|---|
| Bullish crossover | MACD crosses above Signal Line | Moderate buy |
| Bearish crossover | MACD crosses below Signal Line | Moderate sell |
| Zero-line bullish cross | MACD crosses above zero | Trend change to bullish |
| Zero-line bearish cross | MACD crosses below zero | Trend change to bearish |
| Histogram expansion | Bars growing taller | Momentum accelerating |
| Histogram contraction | Bars shrinking | Momentum weakening, reversal may come |
| Bullish divergence | Price new low, MACD higher low | Strong reversal signal |
| Bearish divergence | Price new high, MACD lower high | Strong reversal signal |
Bollinger Bands
Middle Band = SMA(20)
Upper Band = SMA(20) + 2 * StdDev(20)
Lower Band = SMA(20) - 2 * StdDev(20)
Bandwidth = (Upper - Lower) / Middle
%B = (Price - Lower) / (Upper - Lower)
Worked example:
SMA(20) = 150.00
StdDev(20) = 3.50
Upper = 150.00 + 2 * 3.50 = 157.00
Lower = 150.00 - 2 * 3.50 = 143.00
Bandwidth = (157.00 - 143.00) / 150.00 = 0.0933 (9.33%)
Current price = 155.00
%B = (155.00 - 143.00) / (157.00 - 143.00) = 12/14 = 0.857
Interpretation: Price is 85.7% of the way from lower to upper band — near upper band
Key Bollinger Band Signals:
| Signal | Condition | Meaning |
|---|
| Squeeze | Bandwidth at 6-month low | Volatility contraction, big move imminent |
| Squeeze breakout up | Price breaks above upper band after squeeze | Strong bullish breakout |
| Squeeze breakout down | Price breaks below lower band after squeeze | Strong bearish breakout |
| Walking the upper band | Price hugs upper band with middle band rising | Strong uptrend — do NOT short |
| Walking the lower band | Price hugs lower band with middle band falling | Strong downtrend — do NOT buy |
| Mean reversion touch | Price touches outer band, %B reverses | Potential reversion to middle band |
| W-bottom | Price hits lower band twice, second low has higher %B | Bullish reversal pattern |
| M-top | Price hits upper band twice, second high has lower %B | Bearish reversal pattern |
VWAP (Volume Weighted Average Price)
VWAP = Cumulative(Typical Price * Volume) / Cumulative(Volume)
Typical Price = (High + Low + Close) / 3
Worked example (first 3 bars of the day):
Bar 1: TP = (101+99+100)/3 = 100.00, Vol = 10,000 -> cumTP*V = 1,000,000
Bar 2: TP = (102+100+101)/3 = 101.00, Vol = 15,000 -> cumTP*V = 2,515,000
Bar 3: TP = (103+101+102)/3 = 102.00, Vol = 8,000 -> cumTP*V = 3,331,000
Cumulative Volume = 33,000
VWAP = 3,331,000 / 33,000 = 100.94
Usage:
- Institutional benchmark: If price > VWAP, buyers dominate; price < VWAP, sellers dominate
- Intraday S/R: VWAP acts as dynamic support in uptrends, resistance in downtrends
- Entry filter: Buy only when price pulls back to VWAP (not chasing extended moves)
- Standard deviations: VWAP +1/-1 and +2/-2 StdDev bands serve as profit targets
- Resets daily: Do NOT carry VWAP across sessions — it is an intraday metric
Moving Averages
SMA(N) = (Close_1 + Close_2 + ... + Close_N) / N
EMA(N) = Close * (2/(N+1)) + PrevEMA * (1 - 2/(N+1))
Key Moving Averages:
EMA(9) — very short-term trend (scalping, day trading)
EMA(20) — short-term trend
EMA(50) — medium-term trend
SMA(100) — intermediate trend
SMA(200) — long-term trend (institutional benchmark)
Critical Cross Signals:
| Cross | Name | Meaning | Reliability |
|---|
| 50 MA > 200 MA | Golden Cross | Bullish trend reversal | High (lag ~2 weeks) |
| 50 MA < 200 MA | Death Cross | Bearish trend reversal | High (lag ~2 weeks) |
| 9 EMA > 21 EMA | Fast bullish cross | Short-term momentum shift | Moderate |
| Price > 200 SMA | Above long-term trend | Bullish regime | Very High |
| Price < 200 SMA | Below long-term trend | Bearish regime | Very High |
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.
ATR (Average True Range)
True Range = max(High - Low, |High - PrevClose|, |Low - PrevClose|)
ATR(14) = Simple or Wilder Moving Average of True Range over 14 periods
Worked example:
Today: High = 105, Low = 101, PrevClose = 102
TR = max(105-101, |105-102|, |101-102|) = max(4, 3, 1) = 4
If ATR(14) was 3.50 yesterday:
ATR(14) = (3.50 * 13 + 4) / 14 = (45.50 + 4) / 14 = 3.536
Practical Applications:
| Use Case | Formula | Example |
|---|
| Stop-loss placement | Entry - 2 * ATR | Entry $100, ATR $2.50 -> Stop at $95.00 |
| Take-profit target | Entry + 3 * ATR | Entry $100, ATR $2.50 -> Target $107.50 |
| Position sizing | Risk$ / ATR | $200 risk / $2.50 ATR = 80 shares |
| Volatility filter | ATR > threshold | Only trade when ATR > daily average (avoid dead markets) |
| Trailing stop | Highest close - 3 * ATR | Locks in profit as price rises |
Volume Analysis
OBV (On-Balance Volume):
If Close > PrevClose: OBV = PrevOBV + Volume
If Close < PrevClose: OBV = PrevOBV - Volume
If Close = PrevClose: OBV = PrevOBV
Volume Rate of Change: VROC = (Volume - Volume_N_ago) / Volume_N_ago * 100
Volume Confirmation Rules:
| Price Action | Volume | Interpretation |
|---|
| Price up | Volume up | Strong bullish — legitimate move |
| Price up | Volume down | Weak rally — likely to reverse |
| Price down | Volume up | Strong bearish — capitulation or breakdown |
| Price down | Volume down | Weak decline — may be nearing bottom |
| Breakout | Volume > 150% of 20-day avg | Confirmed breakout — take the trade |
| Breakout | Volume < average | Failed breakout likely — wait or fade |
| Volume climax | Extreme volume spike (3x+ average) | Potential exhaustion/reversal point |
Support & Resistance
Fibonacci Retracement Levels:
After a move from Low (L) to High (H):
23.6% level = H - (H - L) * 0.236
38.2% level = H - (H - L) * 0.382
50.0% level = H - (H - L) * 0.500
61.8% level = H - (H - L) * 0.618 (Golden Ratio — strongest level)
78.6% level = H - (H - L) * 0.786
Worked example (move from $80 to $120):
Range = $40
23.6% = 120 - 40 * 0.236 = 120 - 9.44 = $110.56
38.2% = 120 - 40 * 0.382 = 120 - 15.28 = $104.72
50.0% = 120 - 40 * 0.500 = 120 - 20.00 = $100.00
61.8% = 120 - 40 * 0.618 = 120 - 24.72 = $95.28 (most likely bounce)
78.6% = 120 - 40 * 0.786 = 120 - 31.44 = $88.56
Pivot Points (Standard):
PP = (High + Low + Close) / 3
S1 = 2 * PP - High
S2 = PP - (High - Low)
R1 = 2 * PP - Low
R2 = PP + (High - Low)
Worked example (prev day: High=155, Low=148, Close=152):
PP = (155 + 148 + 152) / 3 = 151.67
S1 = 2 * 151.67 - 155 = 148.33
S2 = 151.67 - (155 - 148) = 144.67
R1 = 2 * 151.67 - 148 = 155.33
R2 = 151.67 + (155 - 148) = 158.67
2. Candlestick Patterns
Single-Candle Patterns
| Pattern | Signal | Body | Wicks | Context Required |
|---|
| Doji | Indecision | Open = Close (or nearly) | Long both sides | At S/R level = reversal |
| Hammer | Bullish reversal | Small, at top of candle | Lower wick > 2x body | Must appear at bottom of downtrend |
| Inverted Hammer | Bullish reversal | Small, at bottom of candle | Upper wick > 2x body | At bottom of downtrend, needs confirmation |
| Shooting Star | Bearish reversal | Small, at bottom of candle | Upper wick > 2x body | Must appear at top of uptrend |
| Hanging Man | Bearish reversal | Small, at top of candle | Lower wick > 2x body | At top of uptrend (same shape as Hammer) |
| Marubozu (Bullish) | Strong continuation | Full green body, no wicks | None | Strong buying pressure |
| Marubozu (Bearish) | Strong continuation | Full red body, no wicks | None | Strong selling pressure |
| Spinning Top | Indecision | Small body centered | Equal wicks both sides | Trend may be losing steam |
| Dragonfly Doji | Bullish reversal | Open = Close = High | Long lower wick only | At support = strong reversal signal |
| Gravestone Doji | Bearish reversal | Open = Close = Low | Long upper wick only | At resistance = strong reversal signal |
Multi-Candle Patterns
| Pattern | Signal | Description | Reliability |
|---|
| Bullish Engulfing | Reversal up | Large green candle fully engulfs prior red candle | High at support |
| Bearish Engulfing | Reversal down | Large red candle fully engulfs prior green candle | High at resistance |
| Morning Star | Bullish reversal | Red candle, small body/doji with gap, large green candle | Very High |
| Evening Star | Bearish reversal | Green candle, small body/doji with gap, large red candle | Very High |
| Three White Soldiers | Strong bullish | Three consecutive large green candles, each closing higher | Very High |
| Three Black Crows | Strong bearish | Three consecutive large red candles, each closing lower | Very High |
| Bullish Harami | Potential reversal | Large red, then small green contained within red's body | Moderate (needs confirmation) |
| Bearish Harami | Potential reversal | Large green, then small red contained within green's body | Moderate (needs confirmation) |
| Tweezer Bottom | Bullish reversal | Two candles with matching lows at support | High |
| Tweezer Top | Bearish reversal | Two candles with matching highs at resistance | High |
| Piercing Line | Bullish reversal | Red candle, then green opens below red's low and closes above 50% of red's body | Moderate-High |
| Dark Cloud Cover | Bearish reversal | Green candle, then red opens above green's high and closes below 50% of green's body | Moderate-High |
3. Risk Management Formulas
Position Sizing (Fixed Fractional)
Position Size (shares) = Account Risk Amount / (Entry Price - Stop Loss Price)
Account Risk Amount = Portfolio Value * Risk Per Trade %
RULE: Never risk more than 1-2% of portfolio on a single trade.
Worked example:
Portfolio Value = $10,000
Risk Per Trade = 2% ($200)
Entry Price = $100.00
Stop Loss = $95.00 (based on 2x ATR below entry)
Risk per share = $100.00 - $95.00 = $5.00
Position Size = $200 / $5.00 = 40 shares
Position Value = 40 * $100 = $4,000 (40% of portfolio)
CONCENTRATION CHECK: If position value > 10% of portfolio, reduce size.
Adjusted: max position = $1,000 / $100 = 10 shares
Adjusted risk = 10 * $5.00 = $50 (only 0.5% of portfolio — acceptable)
Kelly Criterion (Optimal Bet Size)
Kelly % = W - ((1 - W) / R)
Where:
W = win rate (decimal)
R = average win / average loss ratio (reward-to-risk)
Worked example:
Win rate: 60% (W = 0.60)
Average win: $300, Average loss: $200
R = 300 / 200 = 1.5
Kelly = 0.60 - (0.40 / 1.5) = 0.60 - 0.267 = 0.333 (33.3%)
Full Kelly is too aggressive for real trading. Use fractions:
Half-Kelly = 0.333 / 2 = 16.7% of portfolio per trade
Quarter-Kelly = 0.333 / 4 = 8.3% of portfolio per trade (recommended)
If Kelly is negative, the system has NEGATIVE expectancy — do not trade it.
Value at Risk (VaR)
Parametric VaR = Portfolio Value * Portfolio Volatility * Z-score * sqrt(Time Horizon)
Z-scores: 90% confidence = 1.282
95% confidence = 1.645
99% confidence = 2.326
Worked example (daily VaR, 95% confidence):
Portfolio = $10,000
Daily volatility (stddev of daily returns) = 2.0%
VaR = $10,000 * 0.02 * 1.645 * sqrt(1) = $329.00
Meaning: 95% confident daily loss will not exceed $329.
Weekly VaR = $329 * sqrt(5) = $329 * 2.236 = $735.65
Monthly VaR = $329 * sqrt(21) = $329 * 4.583 = $1,507.81
Sharpe Ratio
Sharpe = (Rp - Rf) / StdDev(Rp) * sqrt(252)
Where:
Rp = mean daily portfolio return
Rf = daily risk-free rate (Treasury yield / 252)
StdDev(Rp) = standard deviation of daily returns
252 = trading days per year (annualization factor)
Worked example:
Mean daily return = 0.10% (0.001)
Annual Treasury yield = 5.0% -> daily Rf = 0.05/252 = 0.000198
StdDev of daily returns = 0.80% (0.008)
Daily Sharpe = (0.001 - 0.000198) / 0.008 = 0.100
Annualized Sharpe = 0.100 * sqrt(252) = 0.100 * 15.875 = 1.59
Ratings:
< 0.5 = Poor (not compensated for risk)
0.5-1.0 = Acceptable
1.0-2.0 = Good
2.0-3.0 = Very Good
> 3.0 = Excellent (verify — may indicate overfitting)
Sortino Ratio (Downside-Only Risk)
Sortino = (Rp - Rf) / DownsideDeviation * sqrt(252)
DownsideDeviation = sqrt(mean(min(Ri - Rf, 0)^2))
Better than Sharpe because it only penalizes downside volatility, not upside.
Sortino > 2.0 is considered very good.
Maximum Drawdown
For each point t in equity curve:
Peak(t) = max(Equity[0..t])
Drawdown(t) = (Peak(t) - Equity(t)) / Peak(t) * 100%
MaxDrawdown = max(Drawdown(t)) for all t
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
BASE_URL="https://paper-api.alpaca.markets"
DATA_URL="https://data.alpaca.markets"
HEADERS="-H 'APCA-API-KEY-ID: $ALPACA_API_KEY' -H 'APCA-API-SECRET-KEY: $ALPACA_SECRET_KEY'"
Account Information
curl -s "$BASE_URL/v2/account" $HEADERS
Get Current Positions
curl -s "$BASE_URL/v2/positions" $HEADERS
curl -s "$BASE_URL/v2/positions/AAPL" $HEADERS
Place Orders
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
-H "Content-Type: application/json" \
-d '{"symbol":"AAPL","qty":"10","side":"buy","type":"market","time_in_force":"day"}'
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
-H "Content-Type: application/json" \
-d '{"symbol":"AAPL","qty":"10","side":"buy","type":"limit","time_in_force":"gtc","limit_price":"150.00"}'
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
-H "Content-Type: application/json" \
-d '{"symbol":"AAPL","qty":"10","side":"sell","type":"stop","time_in_force":"gtc","stop_price":"145.00"}'
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
-H "Content-Type: application/json" \
-d '{"symbol":"AAPL","qty":"10","side":"sell","type":"stop_limit","time_in_force":"gtc","stop_price":"145.00","limit_price":"144.50"}'
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
-H "Content-Type: application/json" \
-d '{"symbol":"AAPL","qty":"10","side":"sell","type":"trailing_stop","time_in_force":"gtc","trail_percent":"5"}'
curl -s -X POST "$BASE_URL/v2/orders" $HEADERS \
-H "Content-Type: application/json" \
-d '{
"symbol": "AAPL",
"qty": "10",
"side": "buy",
"type": "limit",
"time_in_force": "day",
"limit_price": "150.00",
"order_class": "bracket",
"stop_loss": {"stop_price": "145.00"},
"take_profit": {"limit_price": "165.00"}
}'
curl -s -X POST \
-H \
-d
Order parameters reference:
| Parameter | Values | Notes |
|---|
side | buy, sell | |
type | market, limit, stop, stop_limit, trailing_stop | |
time_in_force | day, gtc, ioc, fok | day = cancel at close, gtc = good til canceled |
order_class | simple, bracket, oco, oto | bracket = entry + stop + target |
qty | String number | Whole shares for stocks |
notional | String dollar amount | Alternative to qty (fractional shares) |
Manage Orders
curl -s "$BASE_URL/v2/orders?status=open" $HEADERS
curl -s "$BASE_URL/v2/orders/{order_id}" $HEADERS
curl -s -X DELETE "$BASE_URL/v2/orders/{order_id}" $HEADERS
curl -s -X DELETE "$BASE_URL/v2/orders" $HEADERS
Close Positions
curl -s -X DELETE "$BASE_URL/v2/positions/AAPL" $HEADERS
curl -s -X DELETE "$BASE_URL/v2/positions/AAPL?qty=5" $HEADERS
curl -s -X DELETE "$BASE_URL/v2/positions" $HEADERS
Market Data (free with Alpaca account)
curl -s "$DATA_URL/v2/stocks/AAPL/quotes/latest" $HEADERS
curl -s "$DATA_URL/v2/stocks/AAPL/trades/latest" $HEADERS
curl -s "$DATA_URL/v2/stocks/AAPL/bars?timeframe=1Day&start=2024-01-01&limit=100" $HEADERS
curl -s "$DATA_URL/v2/stocks/AAPL/bars?timeframe=5Min&start=$(date -d 'today' +%Y-%m-%d)&limit=78" $HEADERS
curl -s "$DATA_URL/v2/stocks/snapshots?symbols=AAPL,MSFT,GOOGL" $HEADERS
curl -s "$DATA_URL/v1beta3/crypto/us/bars?symbols=BTC/USD&timeframe=1Day&limit=30" $HEADERS
curl -s "$DATA_URL/v1beta3/crypto/us/latest/quotes?symbols=BTC/USD,ETH/USD" $HEADERS
Market Clock & Calendar
curl -s "$BASE_URL/v2/clock" $HEADERS
curl -s "$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 $100 worth
Account Activity & History
curl -s "$BASE_URL/v2/account/activities/FILL?after=2024-01-01" $HEADERS
curl -s "$BASE_URL/v2/account/portfolio/history?period=1M&timeframe=1D" $HEADERS
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:
- Are your 60% predictions right ~60% of the time?
- If your 60% predictions are right 80% of the time, you are underconfident — adjust up
- If your 80% predictions are right 55% of the time, you are overconfident — adjust down
- 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
- Every trade has a written plan BEFORE entry: entry price, stop loss, target, position size, thesis
- Write down your reasoning BEFORE entering — if you cannot articulate the edge, do not trade
- Set stop-losses at order entry time, not "in your head"
- Review your journal weekly — look for patterns in wins AND losses
- Take breaks after big wins (overconfidence risk) AND big losses (emotional risk)
- Never average down on a losing position unless the original thesis explicitly planned for it
- Never move a stop-loss further away from your entry (only tighten, never widen)
- 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)
python -c "import json; ..."
curl -s "$BASE_URL/v2/clock" -H "APCA-API-KEY-ID: $ALPACA_API_KEY" \
-H "APCA-API-SECRET-KEY: $ALPACA_SECRET_KEY" | python -c "
import sys, json
d = json.load(sys.stdin)
print('OPEN' if d['is_open'] else 'CLOSED', '| Next:', d.get('next_open','') or d.get('next_close',''))
"
macOS / Linux
python3 -c "import json; ..."
curl -s URL | jq '.equity'
JSON Processing Without jq
python3 -c "import sys,json; print(json.dumps(json.load(sys.stdin),indent=2))" < file.json
curl -s URL | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['equity'])"
curl -s "$BASE_URL/v2/positions" $HEADERS | python3 -c "
import sys, json
positions = json.load(sys.stdin)
fmt = '{:<8} {:>6} {:>10} {:>10} {:>12} {:>8}'
print(fmt.format('Symbol','Qty','Entry','Current','P/L','P/L pct'))
print('-' * 60)
for p in positions:
print(fmt.format(p['symbol'], p['qty'], float(p['avg_entry_price']),
float(p['current_price']), float(p['unrealized_pl']),
round(float(p['unrealized_plpc'])*100,2)))
"
curl -s "$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
{
"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)",
Store trade journals using memory_store for tracking and calibration review.
