Bollinger Bands

Overview

Bollinger Bands (volatility bands) — Plot a moving average with upper/lower bands at standard-deviation distances to gauge volatility and mean reversion.

When to use this skill

Use when the user asks to:

• Analyze or interpret Bollinger Bands on a chart or dataset
• Build buy/sell signals or alerts based on volatility bands
• Combine Bollinger Bands with other indicators for confirmation

How it works

Plot a moving average with upper/lower bands at standard-deviation distances to gauge volatility and mean reversion. Apply it on OHLCV data (open, high, low, close, volume) for any timeframe. Always confirm with price structure, trend context, and at least one independent indicator before acting.

Reading the signals

• Bullish bias: signal aligns with higher highs/higher lows and rising volume.
• Bearish bias: signal aligns with lower highs/lower lows and rising volume.
• No-trade: conflicting context or low volatility/volume.

Worked example (Python)

import pandas as pd
# df has columns: open, high, low, close, volume (datetime index)
# Compute the indicator, then generate signals
# (use pandas/numpy or ta libraries; validate on out-of-sample data)

Risk management

• Define stop-loss from structure or ATR before entry.
• Size positions by fixed-fractional risk (e.g. 0.5–1% per trade).
• Never rely on a single indicator; require confluence.

Common pitfalls

• Over-optimizing parameters to past data (curve fitting).
• Ignoring the higher-timeframe trend.
• Acting on signals during low liquidity.

Educational analysis only. Not financial advice.