Adaptive - works for mean reversion and trend following
| Strategy Type | Volatility-Based Support/Resistance and Trend Analysis |
| Market Outlook | Adaptive - works for mean reversion and trend following |
| Risk Profile | Medium (dynamic levels adjust to volatility) |
| Reward Profile | 1.5:1 to 3:1 depending on strategy variation |
| Time Horizon | Swing trading (3-20 days typical) |
| Iv Environment | Self-adjusting to volatility; works across environments |
| Breakeven | Win rate >45% with 2:1 R:R achieves profitability |
| Primary Instruments | TSX 60 constituents, XIU ETF, sector ETFs, liquid Canadian stocks |
| Iiroc Compliance | Fully compliant; standard equity trading |
| Contract Size | Standard 100-share board lots |
| Trading Hours | 9:30 AM - 4:00 PM ET |
| Expiry Options | N/A - equity positions with no expiration |
| Settlement | T+1 for equities (effective May 2024) |
| Options Exchange | Montreal Exchange (MX) for options overlay |
| Capital Gains Tax | 50% inclusion rate; swing trading generates capital gains |
| Tfsa Eligibility | Fully eligible for Canadian equities and ETFs |
| Rrsp Eligibility | Fully permitted; swing trading acceptable |
Start with the standard settings: 20-period SMA with 2 standard deviations. These are the most widely used and tested settings. Only adjust after gaining experience.
No. A band touch alone is not a signal. You need confirmation: RSI oversold (<30), a reversal candle (hammer, bullish engulfing), and ideally a ranging (not trending down) market. Without confirmation, many band touches will fail.
Bollinger Bands use standard deviation (changes with volatility), so they expand and contract. Keltner Channels use ATR (average true range), which changes more slowly. Comparing them helps identify squeezes.
Visually, bands become very narrow - the tightest they've been in weeks/months. Quantitatively, bandwidth hits multi-week lows. The TTM Squeeze indicator (if available) plots when BB is inside KC.
Yes, especially in strong trends. Price can 'walk' along a band for extended periods. This is why confirmation is crucial - a band touch in a strong trend is often NOT a reversal signal.
Require multiple confirmations: RSI at extreme, reversal candle pattern, higher timeframe support, and avoid trading band touches during 'walking bands' (strong trends). Quality > quantity.
Wait for breakout. Trading during the squeeze has no edge - you don't know the direction. Wait for price to close outside a band with bandwidth expanding, then enter in the breakout direction.
In uptrends, buy pullbacks to the middle band (which acts as support). In downtrends, sell rallies to the middle band (resistance). Use band touches in trend direction for trend continuation, not reversal.
%B quantifies where price is relative to bands on a scale. It's easier to set exact rules (buy when %B < 0.05) and backtest. It also clearly shows when price is outside bands (%B > 1 or < 0).
Consider shorter periods (10) for day trading or very active swing trading. Consider longer periods (50) for position trading. Keep 2 standard deviations unless you have specific reason to change. Test any changes before live trading.
Define exact rules: entry (e.g., close below lower band + RSI < 30), exit (close above middle band or stop at 2x ATR), and position sizing. Test on 5+ years of data. Compare parameters (18-22 period, 1.8-2.2 SD) for robustness. Walk-forward test.
Buy calls/puts at band extremes for directional exposure. Sell put spreads below lower band support. Buy straddles during squeezes. Compare band width (HV) to IV for relative value assessment. Avoid selling iron condors during squeezes.
Watch for BB inside KC (squeeze on). When squeeze releases (BB expands outside KC), note the momentum histogram direction. Enter in that direction. This combines volatility compression with momentum for high-probability breakouts.
Higher timeframes provide context: weekly squeeze = major move coming; weekly at band = significant level. Trade in direction of higher timeframe signals. Use lower timeframe for entry timing. Alignment across timeframes increases probability.
Yes, particularly squeeze breakout systems and mean reversion with quantitative filters. Key is objective rules: exact entry/exit criteria, risk management. Mean reversion works in ranging markets; breakouts work from squeezes. Segment by market condition.
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