| Market | Stocks (can be adapted for ETFs, Forex, Crypto) |
| Timeframe | Daily (suitable for weekly rebalancing or monthly holding) |
| Indicators | 30-day rolling volatility (standard deviation), SMA(50) |
| Style | Factor investing, Rotational/Relative Strength with Low Volatility tilt |
| Skill level | Beginner |
| Typical holding time | Swing (multi-week to multi-month) |
| Risk per trade | 1% core portfolio per position |
How It Works
- Select a universe of stocks/ETFs.
- Rank assets by lowest historical volatility (30-day standard deviation percentage).
- Pick the top N (e.g., 10) lowest-volatility assets each rebalance period.
- Hold equally weighted positions; rebalance at set frequency (monthly or quarterly typical).
- Exclude assets below a simple moving average (SMA) to avoid downward trends.
The potential edge persists as “boring” stocks historically deliver better risk-adjusted returns—perhaps because investors tend to chase exciting, volatile assets, underpricing the slow-and-steady corner of the market. Optimal in calm trending markets or weak bear markets—less ideal when all sectors experience sudden high volatility spikes.
Strategy Rules (Step-by-step)
Setup:
- Each month (or desired rebalance frequency): Generate your universe (e.g., S&P 500, top 500 crypto/forex pairs, or chosen ETF list).
- Calculate 30-day rolling volatility for each asset using daily closing returns (standard deviation of daily % returns).
- Optional: Filter out any asset whose closing price is below its 50-day simple moving average.
Entry:
- On rebalance day, buy the N (e.g., 10) assets with the lowest 30-day volatility and meeting SMA(50) filter. Allocate equal percentage to each.
Stop-loss:
- Hard stop: Remove any position if it falls below its 50-day SMA intra-period.
- Optional: Use ATR(14) to set a volatility-based stop.
Take profit:
- No fixed take profit. Positions are swapped out at next rebalance or stop-loss.
Trade management:
- On rebalance date, sell any asset falling out of the top N or that failed the SMA(50) filter, and replace it with new qualifying assets.
- No mid-cycle adjustments unless stop-loss is triggered.
Settings and Parameters
- Volatility period: 30 trading days (approx. 1.5 months)
- SMA(50): Used as basic trend filter and stop
- Rebalance period: Monthly (can test weekly/quarterly)
- Assets tested: US stocks (S&P 500), global equity ETFs, major cryptos
- Session/Hours: End-of-day closing prices
When It Works vs. When It Fails
Works best:
- Steady bull markets or sideways uptrends with low to moderate overall risk appetite
- Markets prioritizing quality, defensive, or income-oriented stocks (e.g., utilities/consumer staples sectors)
Struggles:
- Sustained periods of speculative mania (all stocks rise on high volatility)
- Market crashes where “safe” stocks also fall sharply or lose their volatility edge
Filters to avoid bad conditions:
- Skip rebalancing near major earnings releases or macroeconomic events
- Apply a minimum liquidity screen (e.g., average daily volume >1M shares)
- Optional: Exclude stocks with recent abnormal volume/price swings (ATR filter)
Risk Management (Beginner-safe)
- Risk a max of 1% of total portfolio per individual holding.
- Maximum total strategy exposure: 10% in any one sector or 15% in one stock (if universe is small).
- Cease new trades for that month if overall strategy equity drawdown exceeds 5% intra-month.
- Remember to factor in slippage and commissions, especially on illiquid names!
Example Trade (Walkthrough)
- Pair/Asset: Procter & Gamble (PG)
- Timeframe: Daily, monthly rebalance
- Setup snapshot: On last month’s rebalance date, PG shows one of the lowest 30-day volatilities in S&P 500 and is trading above its 50-day SMA.
- Entry: Buy at market close, $150/share (e.g., allocate 10% of $10,000 = $1,000, so 6 shares).
- Stop-loss: Price falls below 50-day SMA ($144), triggering exit at next close below this level.
- Take profit: Hold until next rebalance or stop-loss is triggered.
- Outcome: Price rises to $162 by next rebalance (8% gain; 0.8R). No stop-loss hit; lesson learned: The edge was visible as volatility remained low while price drifted up steadily.
Pros and Cons
Pros:
- Simple, rules-based method with clear portfolio diversification
- Historically robust risk-adjusted returns, especially in calm or defensive markets
- Reduces emotional whipsawing compared to momentum or speculative factor strategies
Cons:
- Periods of underperformance, especially in explosive risk-on markets
- Not immune to severe market corrections (drawdown risk remains)
- False “safety” signals if volatility regimes suddenly shift
Common Mistakes
- Chasing past winners or selecting names before validating volatility filter
- Over-leveraging under the illusion of “safety”
- Ignoring correlation risks (e.g., picking ten utility stocks)
- Trading through volatile earnings or major economic reports
Tips and Variations
- Add minimum momentum filter so only rising low-volatility names are picked
- Use ATR for more precise volatility stops instead of just SMA
- Consider sector/industry diversification cap (max 2 per sector)
- Trigger email/phone alerts for rebalance
Tools You Can Use
- Charting: TradingView, StockCharts, ThinkorSwim, Yahoo Finance
- Screeners/Alerts: Finviz, MarketWatch, Portfolio123
- Journaling: Edgewonk, Tradervue, Excel/Google Sheets
- Backtesting: Portfolio Visualizer, QuantConnect, Amibroker, Excel VBA
FAQs
- Does it work on crypto? Yes, if liquidity is high and chosen universe is diversified—use daily timeframes for best results.
- What timeframe is best? Daily with monthly rebalance to avoid over-trading and to capture the “factor” return.
- What win rate to expect? Varies by year and market regime; many years the win rate on trades can be 55–65% with low-moderate drawdown.
- Can I automate it? Easily—use broker APIs or scripting tools and automate rebalance scans plus order placement.
Glossary (Beginner terms)
- EMA: Exponential Moving Average, a price-smoothing indicator
- ATR: Average True Range, measures volatility of price movement
- R-multiple: Profit/loss measured in multiples of initial risk (e.g., 1R = amount risked per trade)
- Drawdown: Peak-to-trough decline during a strategy’s run