Volatility แปลว่าอะไร

Volatility

Volatility ความผันผวน Historical Implied VIX Standard Deviation ATR Bollinger Bands Option Pricing Risk Management Position Size Trading Strategy

Volatility Calculation

# === Volatility Calculation in Python ===

import numpy as np
from dataclasses import dataclass

def historical_volatility(prices, window=20):
    log_returns = np.diff(np.log(prices))
    rolling_std = []
    for i in range(window, len(log_returns) + 1):
        std = np.std(log_returns[i-window:i], ddof=1)
        annualized = std * np.sqrt(252)
        rolling_std.append(annualized)
    return rolling_std

def atr(high, low, close, period=14):
    tr_list = []
    for i in range(1, len(high)):
        tr = max(
            high[i] - low[i],
            abs(high[i] - close[i-1]),
            abs(low[i] - close[i-1])
        )
        tr_list.append(tr)
    atr_values = []
    atr_val = np.mean(tr_list[:period])
    atr_values.append(atr_val)
    for i in range(period, len(tr_list)):
        atr_val = (atr_val * (period - 1) + tr_list[i]) / period
        atr_values.append(atr_val)
    return atr_values

# Example calculation
np.random.seed(42)
prices = 100 + np.cumsum(np.random.randn(100) * 1.5)
hv = historical_volatility(prices, 20)

print("=== Historical Volatility ===")
print(f"  Latest HV (20-day): {hv[-1]:.2%}")
print(f"  Average HV: {np.mean(hv):.2%}")
print(f"  Max HV: {np.max(hv):.2%}")
print(f"  Min HV: {np.min(hv):.2%}")

@dataclass
class VolRegime:
    regime: str
    hv_range: str
    vix_range: str
    market_behavior: str
    strategy: str

regimes = [
    VolRegime("Low", "< 15%", "< 15", "ตลาดสงบ Trend ชัด", "Trend Following, Sell Premium"),
    VolRegime("Normal", "15-25%", "15-20", "ตลาดปกติ มี Swing", "Swing Trading, Covered Call"),
    VolRegime("High", "25-40%", "20-30", "ตลาดผันผวน ข่าวสำคัญ", "Reduce Size, Widen Stops"),
    VolRegime("Extreme", "> 40%", "> 30", "ตลาดตกใจ Crisis", "Hedge, Buy Premium, Cash"),
]

print(f"\nVolatility Regimes:")
for v in regimes:
    print(f"  [{v.regime}] HV: {v.hv_range} | VIX: {v.vix_range}")
    print(f"    Market: {v.market_behavior}")
    print(f"    Strategy: {v.strategy}")

Trading Applications

# === Volatility-based Trading ===

# Position Sizing with ATR
# risk_per_trade = account * 0.01  # 1% risk
# stop_loss_distance = atr * 2     # 2x ATR
# position_size = risk_per_trade / stop_loss_distance

# Bollinger Bands
# middle = SMA(close, 20)
# upper = middle + 2 * StdDev(close, 20)
# lower = middle - 2 * StdDev(close, 20)
# bandwidth = (upper - lower) / middle

# Bollinger Squeeze Detection
# if bandwidth < threshold:  # Squeeze — low volatility
#     prepare_for_breakout()
# if bandwidth > high_threshold:  # Expansion — high volatility
#     consider_mean_reversion()

@dataclass
class TradingSetup:
    setup: str
    volatility_condition: str
    entry: str
    stop_loss: str
    target: str
    risk_reward: str

setups = [
    TradingSetup("Breakout", "Bollinger Squeeze → Expansion", "Break above Upper Band", "Below Middle Band", "2x ATR from entry", "1:2"),
    TradingSetup("Mean Reversion", "Bollinger > 2 StdDev", "Touch Lower Band + RSI < 30", "Below recent low", "Middle Band", "1:1.5"),
    TradingSetup("Trend Follow", "ATR rising + ADX > 25", "Pullback to 20 EMA", "1.5x ATR", "3x ATR", "1:2"),
    TradingSetup("Range Trade", "ATR falling + ADX < 20", "Support/Resistance bounce", "Outside range", "Opposite boundary", "1:1"),
    TradingSetup("Vol Expansion", "VIX spike > 25%", "After spike settles", "Above VIX high", "VIX mean revert", "1:2"),
]

print("\n=== Volatility Trading Setups ===")
for s in setups:
    print(f"  [{s.setup}] Vol: {s.volatility_condition}")
    print(f"    Entry: {s.entry}")
    print(f"    SL: {s.stop_loss} | TP: {s.target} | R:R: {s.risk_reward}")

Risk Management

# === Risk Management with Volatility ===

@dataclass
class RiskRule:
    rule: str
    low_vol: str
    normal_vol: str
    high_vol: str
    extreme_vol: str

rules = [
    RiskRule("Position Size", "Full (1-2% risk)", "Normal (1% risk)", "Half (0.5% risk)", "Quarter (0.25% risk)"),
    RiskRule("Stop Loss", "1.5x ATR", "2x ATR", "2.5x ATR", "3x ATR or no trade"),
    RiskRule("Max Open Trades", "5-8", "3-5", "2-3", "0-1"),
    RiskRule("Leverage", "Normal", "Reduce 25%", "Reduce 50%", "No leverage"),
    RiskRule("Hedge", "ไม่จำเป็น", "Optional", "Recommended", "Required"),
    RiskRule("Cash Allocation", "10-20%", "20-30%", "30-50%", "50-80%"),
]

print("Risk Management by Volatility:")
for r in rules:
    print(f"  [{r.rule}]")
    print(f"    Low: {r.low_vol}")
    print(f"    Normal: {r.normal_vol}")
    print(f"    High: {r.high_vol}")
    print(f"    Extreme: {r.extreme_vol}")

# Kelly Criterion adjusted for volatility
# f = (W * R - L) / R
# f_adjusted = f * (base_vol / current_vol)
# Where lower vol = larger position, higher vol = smaller position

vol_tools = {
    "ATR Indicator": "TradingView: ATR(14) overlay on chart",
    "Bollinger Bands": "TradingView: BB(20,2) squeeze detection",
    "VIX Chart": "TradingView: CBOE:VIX daily chart",
    "IV Rank": "Option platform: current IV vs 52-week range",
    "HV Calculator": "Python script above or Excel",
    "Vol Surface": "Option platform: IV by strike and expiry",
}

print(f"\n\nVolatility Tools:")
for k, v in vol_tools.items():
    print(f"  [{k}]: {v}")

เคล็ดลับ

• ATR: ใช้ ATR ตั้ง Stop Loss ให้เหมาะกับ Volatility ปัจจุบัน
• Size: ลด Position Size เมื่อ Volatility สูง
• Squeeze: สังเกต Bollinger Squeeze เตรียม Breakout Trade
• VIX: ดู VIX เป็น Sentiment Indicator ก่อนเทรด
• Regime: ปรับ Strategy ตาม Volatility Regime

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สรุป

Volatility ความผันผวน Historical Implied VIX ATR Bollinger Bands Position Size Risk Management Regime Trading Strategy Option Pricing Production