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
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
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)
# 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: $ALPACA_SECRET_KEY'"
# All positions
curl -s "$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"$HEADERS
Place Orders
# Market order (fills immediately at best available price)
curl -s -X POST "$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"$HEADERS\
-H "Content-Type: application/json"\
-d '{
"symbol": "AAPL",
"qty": "10",
"side": "sell",
"type": "limit",
"time_in_force": "gtc",
"limit_price": "165.00",
"order_class": "oco",
"stop_loss": {"stop_price": "145.00"}
}'
Order parameters reference:
Parameter
Values
Notes
side
buy, sell
type
market, limit, stop, stop_limit, trailing_stop
time_in_force
day, gtc, ioc, fok
day = cancel at close, gtc = good til canceled
order_class
simple, bracket, oco, oto
bracket = entry + stop + target
qty
String number
Whole shares for stocks
notional
String dollar amount
Alternative to qty (fractional shares)
Manage Orders
# List open orders
curl -s "$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"$HEADERS
Close Positions
# Close entire position in a symbol
curl -s -X DELETE "$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"$HEADERS
Energy, Industrials, Utilities, Real Estate, Materials, Communication Services
Correlation Awareness
Highly correlated positions amplify risk. Check correlations before adding:
Pair
Typical Correlation
Risk
AAPL + MSFT + GOOGL
0.7-0.9
Concentrated large-cap tech
BTC + ETH + SOL
0.8-0.95
Concentrated crypto (moves together)
SPY + QQQ
0.9+
Nearly identical exposure
Stocks + Bonds
-0.2 to 0.3
Genuinely diversifying
Gold + Stocks
-0.1 to 0.2
Hedge in crisis
VIX + SPY
-0.8
Inverse — VIX as hedge
Rebalancing Rules
Calendar: Rebalance quarterly (first trading day of quarter)
Threshold: Rebalance when any allocation drifts > 5% from target
Tax-aware: Prefer rebalancing via new contributions rather than selling (taxable accounts)
9. Cross-Platform Commands
Windows (PowerShell / Git Bash)
# Python might be `python` not `python3` on Windows
python -c "import json; ..."# Use forward slashes in file paths or escape backslashes# curl is available via Git Bash, PowerShell, or WSL# Check if market is open (Windows Git Bash)
curl -s "$BASE_URL/v2/clock" -H "APCA-API-KEY-ID: $ALPACA_API_KEY"\
-H "APCA-API-SECRET-KEY: $ALPACA_SECRET_KEY"| python -c "
import sys, json
d = json.load(sys.stdin)
print('OPEN' if d['is_open'] else 'CLOSED', '| Next:', d.get('next_open','') or d.get('next_close',''))
"
macOS / Linux
python3 -c "import json; ..."# curl, jq typically available by default# Use jq for JSON processing:
curl -s URL | jq '.equity'
JSON Processing Without jq
# Pretty-print JSON
python3 -c "import sys,json; print(json.dumps(json.load(sys.stdin),indent=2))" < file.json
# Extract specific field
curl -s URL | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['equity'])"# Parse Alpaca positions into readable table
curl -s "$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
{"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.
Evan Hu
17d32ed4a7