NATR (Normalized Average True Range)

Overview

The Normalized Average True Range (NATR) is a volatility indicator that expresses the Average True Range (ATR) as a percentage of the closing price. By normalizing ATR, NATR allows traders to compare volatility across different securities regardless of their price levels, making it ideal for portfolio analysis, cross-asset comparisons, and relative volatility assessments. A stock trading at $10 with an ATR of $0.50 has the same NATR as a stock at $100 with an ATR of $5.00 (both 5%).

Parameters

Parameter	Type	Default	Description
high	Array	Required	Array of high prices for each period
low	Array	Required	Array of low prices for each period
close	Array	Required	Array of closing prices for each period
period	Integer	14	Number of periods for ATR calculation

Parameter Details

Note: Array elements should be ordered from oldest to newest (chronological order)

high, low, close - Same requirements as ATR calculation - Must have same length - Need sufficient data (at least period + 1 values) - NATR first calculates ATR, then normalizes by close price

period - Default is 14 periods (Wilder's original ATR setting) - Represents lookback period for averaging true range - Shorter periods (7-10): More responsive to recent volatility changes - Longer periods (21-30): Smoother, better for long-term volatility assessment - Common settings: - Day trading: 7-10 periods - Swing trading: 14 periods (standard) - Position trading: 21-30 periods

Usage

Basic Usage

require 'sqa/tai'

high  = [48.70, 48.72, 48.90, 48.87, 48.82, 49.05, 49.20, 49.35,
         49.92, 50.19, 50.12, 50.10, 50.00, 49.75, 49.80]
low   = [47.79, 48.14, 48.39, 48.37, 48.24, 48.64, 48.94, 49.03,
         49.50, 49.87, 49.20, 49.00, 48.90, 49.00, 49.10]
close = [48.20, 48.61, 48.75, 48.63, 48.74, 49.03, 49.07, 49.32,
         49.91, 50.13, 49.53, 49.50, 49.25, 49.20, 49.45]

# Calculate NATR with default 14-period setting
natr = SQA::TAI.natr(high, low, close, period: 14)

puts "Current NATR: #{natr.last.round(2)}%"

With Custom Parameters

# Short-term volatility (7-period)
natr_short = SQA::TAI.natr(high, low, close, period: 7)

# Long-term volatility (21-period)
natr_long = SQA::TAI.natr(high, low, close, period: 21)

puts "7-day NATR: #{natr_short.last.round(2)}%"
puts "14-day NATR: #{natr.last.round(2)}%"
puts "21-day NATR: #{natr_long.last.round(2)}%"

Comparing Multiple Assets

# Compare volatility across different securities
symbols = ['AAPL', 'GOOGL', 'TSLA', 'SPY']

volatility_comparison = symbols.map do |symbol|
  high, low, close = load_ohlc_data(symbol)
  natr = SQA::TAI.natr(high, low, close, period: 14)

  {
    symbol: symbol,
    price: close.last.round(2),
    natr: natr.last.round(2)
  }
end

# Sort by volatility (highest to lowest)
volatility_comparison.sort_by { |v| -v[:natr] }.each do |data|
  puts "#{data[:symbol]}: #{data[:natr]}% (Price: $#{data[:price]})"
end

Understanding the Indicator

What It Measures

NATR measures volatility relative to price level:

• Relative Volatility: Percentage-based volatility that's comparable across assets
• Price-Adjusted Risk: How much an asset moves relative to its price
• Normalized Comparison: Enables direct comparison between $10 and $1000 stocks
• Portfolio Balancing: Helps identify which positions have similar risk profiles

NATR answers: "What percentage of its price does this security typically move per period?"

Calculation Method

NATR is calculated in two steps:

1. Calculate ATR: Standard Average True Range over the specified period
2. Normalize by Close: Divide ATR by current close price and multiply by 100

Formula:

NATR = (ATR / Close) × 100

Where:
- ATR = Average True Range over period
- Close = Current closing price
- Result expressed as percentage

Example Calculation:

Stock A: Price = $100, ATR = $3.00
NATR = (3.00 / 100) × 100 = 3.0%

Stock B: Price = $20, ATR = $0.60
NATR = (0.60 / 20) × 100 = 3.0%

Both stocks have same relative volatility despite different prices

Indicator Characteristics

• Range: Unbounded positive percentage (typically 0.5% to 10%+)
• Type: Volatility measure, normalized oscillator
• Lag: Moderate (inherits ATR's smoothing lag)
• Best Used: Cross-asset comparisons, portfolio construction, relative risk assessment
• Limitations: Doesn't indicate direction, requires multiple assets for context

Interpretation

Value Ranges

Understanding NATR percentages:

• Below 1%: Very low volatility, stable price action. Common for utility stocks, bonds, stable large-caps.
• 1-2%: Low to moderate volatility. Typical for established blue-chip stocks in normal conditions.
• 2-4%: Moderate to elevated volatility. Common for growth stocks, mid-caps, or markets with some uncertainty.
• 4-7%: High volatility. Seen in small-caps, growth stocks during earnings, or market stress periods.
• Above 7%: Very high volatility. Typical for speculative stocks, during major news, or market crashes.

Context Matters: Compare NATR to the asset's historical range and peer group averages.

Key Patterns

• Rising NATR: Volatility expanding, risk increasing, uncertainty growing
• Falling NATR: Volatility contracting, risk decreasing, price stabilizing
• Stable NATR: Consistent volatility environment
• NATR Spikes: Sudden volatility events (earnings, news, market shocks)
• Relative NATR: High NATR vs peers suggests higher risk/reward potential

Signal Interpretation

How to use NATR signals:

1. Portfolio Risk Management
2. High NATR assets: Reduce position size to maintain consistent portfolio risk
3. Low NATR assets: Can increase position size for balanced exposure

4. Target equal risk contribution across positions

5. Asset Selection

6. Compare NATR within sector to find outliers
7. High NATR = higher risk but potentially higher returns
8. Low NATR = lower risk but potentially lower returns

9. Match NATR to risk tolerance

10. Market Regime Identification

11. Rising NATR across market = increasing uncertainty
12. Falling NATR across market = stabilizing conditions
13. Divergent NATR = sector rotation or stock-specific issues

Trading Signals

Position Sizing Based on NATR

NATR is primarily used for risk management rather than entry/exit signals:

1. Equal Risk Position Sizing

   # Size positions inversely to NATR for equal risk
   account_risk = 10000  # Risk $10k on this trade
   natr = 3.5  # 3.5% NATR
   
   # Stop loss at 2x NATR
   stop_distance_pct = natr * 2  # 7%
   position_value = account_risk / (stop_distance_pct / 100)
   
   shares = (position_value / current_price).floor
   

2. Volatility Filtering

3. Only trade assets with NATR in acceptable range
4. Example: Only trade stocks with 2-5% NATR

5. Avoids extremely volatile (whipsaw) or dead (no movement) stocks

6. Dynamic Stop Losses

7. Use NATR to set percentage-based stops
8. High NATR = wider stops, Low NATR = tighter stops
9. Example: Stop = 2 × NATR percentage

Risk Adjustment Signals

High NATR Alert (Above 6%): - Reduce position size by 30-50% - Widen stop losses to avoid normal volatility - Consider options strategies instead of stock - Monitor more frequently for sudden moves

Low NATR Alert (Below 1%): - Can increase position size moderately - Tighten stop losses (less room needed) - Suitable for larger positions - Less frequent monitoring needed

NATR Spike (2x average): - Volatility event occurring - Avoid new entries until stabilization - Widen existing stops temporarily - May signal earnings, news, or market event

Best Practices

Optimal Use Cases

When NATR works best:

• Portfolio construction: Creating balanced risk exposure across multiple assets
• Position sizing: Determining appropriate position sizes based on volatility
• Asset comparison: Comparing relative volatility across different price levels
• Risk management: Setting stops and targets based on normalized volatility
• Sector rotation: Identifying changing volatility patterns by sector

Combining with Other Indicators

Recommended combinations:

• With ATR: Use NATR for comparison, ATR for absolute dollar risk on specific positions

• With RSI/MACD: Combine NATR (volatility) with momentum indicators for complete picture

• High NATR + oversold RSI = high-risk reversal opportunity

• Low NATR + strong MACD = stable trending opportunity

• With Bollinger Bands: NATR confirms Band width changes

• Rising NATR + expanding Bands = confirmed volatility increase
• Falling NATR + contracting Bands = consolidation phase

Common Pitfalls

What to avoid:

1. Using as entry/exit signal: NATR measures volatility, not direction. Don't use crosses or levels as trade signals.

2. Ignoring historical context: 3% NATR means different things for tech stocks vs utilities. Always compare to historical norms.

3. Not adjusting for market conditions: During market stress, "normal" NATR levels shift higher across all assets.

4. Comparing across asset classes: Don't compare stock NATR to forex or commodity NATR directly.

Parameter Selection Guidelines

• Short-term traders (day trading): 7-10 period NATR for recent volatility
• Swing traders: 14 period NATR (standard) for medium-term volatility
• Position traders: 21-30 period NATR for longer-term volatility profile
• Backtesting: Use period matching your typical holding period

Practical Example

Complete portfolio risk management example:

require 'sqa/tai'

# Portfolio of different stocks
portfolio = [
  { symbol: 'AAPL', shares: 100, price: 175.0 },
  { symbol: 'TSLA', shares: 50, price: 250.0 },
  { symbol: 'KO', shares: 200, price: 60.0 },
  { symbol: 'SPY', shares: 150, price: 450.0 }
]

# Calculate NATR for each position
portfolio.each do |position|
  high, low, close = load_ohlc_data(position[:symbol])
  natr = SQA::TAI.natr(high, low, close, period: 14)
  atr = SQA::TAI.atr(high, low, close, period: 14)

  position[:natr] = natr.last
  position[:atr] = atr.last
  position[:value] = position[:shares] * position[:price]
  position[:dollar_risk] = position[:shares] * (2 * atr.last)  # 2xATR stop
  position[:pct_risk] = (position[:dollar_risk] / position[:value]) * 100
end

puts "=== Portfolio Risk Analysis ==="
puts

portfolio.each do |pos|
  puts "#{pos[:symbol]}:"
  puts "  Position Value: $#{pos[:value].round(0)}"
  puts "  NATR: #{pos[:natr].round(2)}%"
  puts "  Dollar Risk (2xATR stop): $#{pos[:dollar_risk].round(0)}"
  puts "  % Risk of Position: #{pos[:pct_risk].round(2)}%"
  puts
end

# Identify high and low volatility positions
high_vol = portfolio.select { |p| p[:natr] > 4.0 }
low_vol = portfolio.select { |p| p[:natr] < 2.0 }

puts "High Volatility Positions (>4% NATR):"
high_vol.each { |p| puts "  #{p[:symbol]}: #{p[:natr].round(2)}%" }

puts "\nLow Volatility Positions (<2% NATR):"
low_vol.each { |p| puts "  #{p[:symbol]}: #{p[:natr].round(2)}%" }

# Calculate total portfolio dollar risk
total_risk = portfolio.sum { |p| p[:dollar_risk] }
total_value = portfolio.sum { |p| p[:value] }
portfolio_risk_pct = (total_risk / total_value) * 100

puts "\nPortfolio Summary:"
puts "  Total Value: $#{total_value.round(0)}"
puts "  Total Dollar Risk: $#{total_risk.round(0)}"
puts "  Portfolio Risk %: #{portfolio_risk_pct.round(2)}%"

Related Indicators

Similar Indicators

• Average True Range (ATR): The foundation of NATR. ATR for absolute dollar risk, NATR for relative percentage risk.

• Bollinger Band Width: Another normalized volatility measure. Band Width uses standard deviation, NATR uses average true range.

Complementary Indicators

• ATR: Use together - NATR for comparison, ATR for position-specific risk calculations

• Standard Deviation: Alternative volatility measure. NATR captures gaps and full range, StdDev focuses on close-to-close changes

Indicator Family

NATR is part of the volatility measurement family: - True Range: Single period volatility - ATR: Average volatility in dollars - NATR: Average volatility as percentage - Bollinger Bands: Volatility bands around price

When to prefer NATR: For comparing volatility across different price levels, portfolio risk management, and cross-asset analysis. Use NATR when you need to answer "which asset is more volatile relative to its price?"

Advanced Topics

Multi-Timeframe Volatility Analysis

Using NATR across timeframes:

• Daily NATR: Standard reference for volatility
• Weekly NATR: Long-term volatility regime
• Hourly NATR: Intraday volatility patterns

Mismatches can reveal important insights (e.g., low daily NATR but high hourly NATR suggests intraday chop within tight daily range).

Market Regime Adaptation

NATR in different market conditions:

• Bull Markets: Average NATR tends lower as prices grind higher
• Bear Markets: Average NATR spikes as fear drives volatility
• Crisis Periods: NATR can exceed 10-15% even for large-caps
• Low Volatility Regimes: NATR under 1% common for indexes and blue-chips

Statistical Validation

NATR characteristics:

• Mean Reversion: High NATR tends to revert to average over time
• Typical Ranges: Most stocks have 1-5% NATR in normal conditions
• Extreme Values: NATR above 10% suggests special situation (earnings, news, crisis)
• Correlation: Rising NATR often coincides with downtrends (volatility and price negatively correlated)

References

• Wilder, J. Welles Jr. "New Concepts in Technical Trading Systems" (1978) - ATR foundation
• StockCharts: ATR and NATR
• TradingView: NATR Documentation

See Also

• Volatility Indicators Overview
• ATR - Average True Range
• TRANGE - True Range
• Basic Usage Guide