Section 11 - Chapter 2 - Measuring Historical Volatility

Section 11 - Chapter 2 - Measuring Historical Volatility - Presented by Rohan Sharma - The CMT Coach - Chartered Market Technician CMT Level 1 Study Material - CMT Level 1 Chapter Wise Short Notes - CMT Level 1 Course Content - CMT Level 1 2025 Exam Syllabus Visit Site : www.learn.ptaindia.com and www.ptaindia.com

1. Chapter 2 – Measuring Historical Volatility Section 11 – Volatility Analysis Presented By : This Content is Copyright Reserved Rights Copyright 2025@PTAIndia

2. Agenda Measuring Historical Volatility Standard Deviation of Closing Prices Average True Range Bollinger Bands Keltner Channels This Content is Copyright Reserved Rights Copyright 2025@PTAIndia

3. True Range (TR) Presented By : This Content is Copyright Reserved Rights Copyright 2025@PTAIndia

4. True Range (TR) 📌 Three Measurements for True Range (TR): Wilder defines True Range (TR) as the greatest of the following three calculations: 1. Current High - Current Low o Measures the normal range for the current period. o Used when there are no gaps in price action. 2. Absolute Value of (Current High - Previous Close) o Captures the range when there is a gap up from the previous close. o Accounts for overnight volatility. 3. Absolute Value of (Current Low - Previous Close) o Captures the range when there is a gap down from the previous close. o Reflects sudden price drops.

5. True Range (TR) 📌 Comparisons: TR vs. Other Volatility Measures Indicator Purpose Formula & Approach True Range (TR) Measures intraday price movement Max of 3 ranges Average True Range (ATR) Smoothed measure of volatility over time TR smoothed using a moving average (typically 14-period EMA or SMA) Standard Deviation Measures dispersion of price from mean Uses closing price deviation Bollinger Bands Measures volatility via upper/lower bands Uses moving average & standard deviation

6. True Range (TR) Interpretation of True Range (TR) 1. Higher TR → Higher Volatility o Indicates strong price movements, often seen during breakouts. 2. Lower TR → Lower Volatility o Suggests market consolidation or sideways movement. 3. Used in ATR Calculation o ATR helps in setting stop losses, position sizing, and identifying market conditions .

7. Average True Range (TR) Presented By : This Content is Copyright Reserved Rights Copyright 2025@PTAIndia

8. Average True Range (TR) Developed by: J. Welles Wilder Jr. (introduced in New Concepts in Technical Trading Systems, 1978) Purpose: Measures market volatility by smoothing True Range (TR) over a specified period (commonly 14 days). Key Facts About ATR 1. ATR is a Volatility Indicator: o It does not indicate trend direction—only price movement intensity. o Higher ATR = More volatility; Lower ATR = Less volatility. 2. Calculated from True Range (TR): o TR = Max of:  (High - Low)  |High - Previous Close|  |Low - Previous Close| o ATR = Smoothed moving average of TR (commonly 14-period ).

9. Average True Range (TR) 3 . Adjusts for Gaps: o Unlike simple range (High - Low), ATR accounts for overnight gaps. 4. Used in Risk Management: o Helps set stop-loss levels (e.g., ATR-based trailing stops). o Useful in position sizing (larger ATR → smaller position size, vice versa ). ATR Calculation Cheat Sheet Formula: ATR=( PreviousATR ×(n−1 ))+ CurrentTR Where: n = Period (usually 14) TR = True Range Quick ATR Interpretation Guide: ATR Value Market Condition High ATR High volatility, strong price movements Low ATR Low volatility, consolidation, sideways market Rising ATR Market becoming more volatile Falling ATR Market stabilizing

10. Average True Range (TR) Interpretation & Trading Uses of ATR 1 . Breakout Trading o High ATR signals potential strong moves → trade breakout strategies. 2. Stop-Loss & Risk Management o ATR-based stop-loss (e.g., 1.5x or 2x ATR) helps adjust for volatility. 3. Trend Confirmation o Rising ATR during an uptrend confirms strength; Falling ATR may signal exhaustion. 4. Position Sizing o Large ATR → Reduce position size (to control risk). o Small ATR → Increase position size (if appropriate ).

11. Bollinger Bands Presented By : This Content is Copyright Reserved Rights Copyright 2025@PTAIndia

12. Bollinger Band Key Facts About Bollinger Bands 1. Consists of Three Lines: o Upper Band: MA+( k×SD )MA + (k \times SD)MA+( k×SD ) o Middle Band (SMA): Typically a 20-period simple moving average (SMA) o Lower Band: MA−( k×SD )MA - (k \times SD)MA−( k×SD ) 2. Uses Standard Deviation (SD) to Measure Volatility o Default setting: 2 standard deviations (SD) from SMA. o Expanding bands = Increased volatility. o Contracting bands = Low volatility (squeeze ).

13. Bollinger Band Key Facts About Bollinger Bands 3 . Price Tends to Stay Within Bands o About 95% of price action remains inside the bands (under normal distribution). o If price touches the upper band, it may be overbought. o If price touches the lower band, it may be oversold. 4. The "Bollinger Squeeze" Predicts Breakouts o Narrow Bands: Low volatility, upcoming breakout likely. o Widening Bands: High volatility, strong trend in place.

14. Bollinger Band Bollinger Bands Cheat Sheet Market Condition Band Behavior Interpretation High Volatility Bands widen Strong price movement expected Low Volatility (Squeeze) Bands contract Potential breakout Uptrend Price moves along the upper band Strong bullish momentum Downtrend Price moves along the lower band Strong bearish momentum Mean Reversion Price returns to middle band Price correction likely Comparisons: Bollinger Bands vs. Other Indicators Indicator Purpose Key Difference Bollinger Bands Measures volatility & identifies overbought/oversold areas Based on standard deviation Keltner Channels Measures volatility using ATR Uses ATR, not standard deviation Donchian Channels Identifies price breakout levels Uses highest/lowest price over a period Moving Average (MA) Tracks price trend Does not account for volatility

15. Keltner Channels Presented By : This Content is Copyright Reserved Rights Copyright 2025@PTAIndia

16. Keltner Channels Key Facts About Keltner Channels 1. Consists of Three Lines: o Upper Band: EMA+( ATR × Multiplier) o Middle Band (EMA): Typically a 20-period Exponential Moving Average (EMA) o Lower Band: EMA−( ATR × Multiplier) o Default multiplier: 2 x ATR (adjustable). 2. Uses ATR Instead of Standard Deviation o Unlike Bollinger Bands (BB), which use standard deviation, Keltner Channels use ATR, which is smoother. o Expanding bands = Increased volatility. o Contracting bands = Low volatility (squeeze ).

17. Keltner Channels Key Facts About Keltner Channels 3 . Price Trends Within the Channel o If price stays near upper band, strong bullish trend. o If price stays near lower band, strong bearish trend. o Price reverting to the middle band suggests mean reversion . 4. Keltner Channel "Squeeze" Predicts Breakouts o When the bands contract, low volatility signals a potential breakout. o Expansion of bands signals high volatility and strong price movement.

18. Keltner Channels Keltner Channels Cheat Sheet . Market Condition Band Behavior Interpretation High Volatility Bands widen Strong price movement expected Low Volatility (Squeeze) Bands contract Potential breakout Uptrend Price stays near upper band Strong bullish momentum Downtrend Price stays near lower band Strong bearish momentum Mean Reversion Price moves back to middle EMA Possible pullback or trend change

19. Keltner Channels Interpretation & Trading Strategies Using Keltner Channels 1. Trend-Following Strategy o Strong Uptrend: Price stays near upper band → Look for buy opportunities. o Strong Downtrend: Price stays near lower band → Look for sell opportunities. 2. Breakout Trading (Squeeze Strategy) o Bands contract (squeeze) → Expect a breakout. o Enter long if price breaks above upper band. o Enter short if price breaks below lower band. 3. Reversal Trading (Mean Reversion) o Price moves far above upper band → Potential overbought (sell signal). o Price moves far below lower band → Potential oversold (buy signal). 4. Double Keltner Channel Strategy o Use two sets of Keltner Channels (1.5 ATR & 2 ATR) for finer trade signals .

20. Next Chapter 3 - Options Derived Volatility Section 11 – Volatility Analysis Presented By : This Content is Copyright Reserved Rights Copyright 2025@PTAIndia