Volatility-BasedT h i l A l iTechnical Analysis:Strategies for Trading the Invisble

Kirk Northington

With Companion Websitehttp://www.tradingtheinvisible.com

tradingtheinvisible.com

metaswing.com

Kirk Northington

The author of Volatility-Based Technical Analysis: Strategies for Trading

BIO

The author of Volatility Based Technical Analysis: Strategies for Trading the Invisible. Wiley Trading Series, John Wiley & Sons Publishers. ISBN: 978-0-470-38754-2.

The owner of Northington Trading, LLC, and the creator of MetaSwing, a g g, , g,MetaStock and TradeStation Add-On. He trades his own money, and uses MetaSwing technical analysis methods exclusively.

Kirk Northington is a technical analyst. He is an associate member of the Market Technicians Association, through which he is participating in the Chartered Market Technician (CMT) Program.

Kirk has a B.S. degree from Nicholls State University, in Thibodaux, L i i H h i i i l i iLouisiana. He has extensive experience in control system engineering, software engineering, and project management. Kirk, his wife Faith, and his two sons live in Charlotte, North Carolina.

kirk@metaswing com or (910) 789 0673

Northington Trading Page 2

kirk@metaswing.com or (910) 789-0673

tradingtheinvisible.com metaswing.com

The Companion Website: tradingtheinvisible.com

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Goal of Volatility-Based Technical Analysis

Goal:

Identify a point where, mathematically y p , yspeaking, price should not be, at that point in time;p ;

i.e., find the true inefficiencies.,

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Mantra of Volatility-Based Technical Analysis

Mantra:

Money is made at the Extremesy

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Money is made at the Extremes

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Money is made at the Extremes

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How is this possible?

Volatility Measurement:y

Identifies Extremes

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Can I understand volatility measurement?

YesYes

Volatility Measurement with:Volatility Measurement with:

CalculusCalculus

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VBTA = New Concepts and Capabilitis for TA

This Presentation:

Will pick one concept and capability and solve for it:

Trend Compensation

We will also view volatility-based support and resistance.

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Money is made at the Extremes

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Why is Volatility Measurement Important?

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Why is Volatility Measurement Important?

Why?Why?

• Equity Options Tradingq y p g

• VaR – Value at Risk modeling• Portfolio Managment• Risk Management

• Program Trading

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Why is Volatility Measurement Important?

Brain Power page 5

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Quatitative mathematics focuses heavily on volatility measurement

Why is Volatility Measurement Important?

Horse Power

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Why is Volatility Measurement Important?

Horse Power

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Why is Volatility Measurement Important?

Brain Power page 5

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Quatitative mathematics focuses heavily on volatility measurement

Why is Volatility Measurement Important?

Horse Power

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Opportunities

Take the Offensive

• Redraw the Playing Field• Simple Volatility Measurement• Avoid Systemic RiskAvoid Systemic Risk• Hidden Momentum• True Overbought and Oversold• Exit on Cue

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Preparing to Use VBTA

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Working with Volatility Measurement

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What is Volatility?

Concept . . . Not a Specific Measurement

• “In truth volatility is more of a concept applied to whatever the task at hand needs it to be. So conceptually volatility as it applies to a tradable instrument is just a measurement of an instrument’s price, in terms of rise or fall, within a given time frame.”

• Used to project an extreme that might be reached, within a reasonable probability

• Most commonly expressed with Standard Deviation

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What is Volatility?

Historical and Implied

• “Historical Volatility (also referred to as Statistical Volatility) is a measure of movement within a given period of time. Historical volatility is normally measured using forms ofHistorical volatility is normally measured using forms of standard deviation and is expressed in terms of percent.”

• “Implied Volatility: A measure of possible, or ‘expected’Implied Volatility: A measure of possible, or expected movement of the underlying stock’s price, as projected forward through time, expressed as a percentage. It is created by any of many options pricing models. These pricing models utilize all known options trading factors, in addition to the actual current trading price of the option’s premium.”

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Option Pricing

Historical Implied

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Volatility Unmasked

Basic Forms of Volatility Measurement

• Standard Deviation• Average True RangeAverage True Range• Percentage• Mean (or Average)• Linear Regressiong• Standard Error• R Squared• Variance

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Volatility Measurement is Simple as 1 - 2 - 3

Standard Deviation (20)

1. Difference between Close and moving average

2. Square it (Key Step)

3. Add the most recent 20 of these, and calculate square rootand calculate square root.

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Stdev(C, 20)tradingtheinvisible.com metaswing.com

Average True Range

It is the greatest of:

• The distance from today’s high to today’s low.y g y• The distance from yesterday’s close to today’s high.• The distance from yesterday’s close to today’s low.

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ATR(C, 14)

Linear Regression

Most Efficient – Least SquaresMost Efficient Least Squares

1. Difference between price and h i l li h itheoretical line, then square it.

2. Add up all the squared values

3. Redraw the line so that the sum of the squared values is lower.(lather, rince, repeat)

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( , , p )

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LinearReg(C, 20)

Predictive Qualities

Basic Forms of Volatility Measurement

• Standard Deviation• Average True Range• Average True Range• Percentage• Mean (or Average)• Linear Regression• Standard Error• R Squared

V i

Forward Predictive Value = 2 to 5 Periods

• Variance

• Are Fractal and therfore Chart Periodicity independent

• Dependent on lack of conflicting / overriding fundamental news; as is all TA

• Amplified by Trend

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• Design specific components for specific purposes

Specific Purpose

Basic Forms of Volatility Measurement

• Standard Deviation• Average True Range• Average True Range• Percentage• Mean (or Average)• Linear Regression• Standard Error• R Squared

V i

T d C t d

• Variance

Trend Compensated

O S ld / O b ht D t tiOverSold / Overbought Detection

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Northington RSIV

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Northington RSIV

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Northington RSIV{Copyright Kirk Northington, Northington Trading, LLC. { py g g , g g,All rights reserved}

{User Inputs}pds1:= Input("Lookback", 2, 1000, 30);pds2:= Input("Linear Regression Periods", 2, 1000, 40);pds3:= Input("ATR Periods", 2, 1000, 7);

(" h h ld" 50 99 70)Upper:= Input("Upper Threshold", 50, 99, 70);Lower:= Input("Lower Threshold", 1, 59, 30);

{Express the prevailing trend}x1:= (C - LinearReg(C, pds2));

{Calculate the RSIV indicator}

Trend Compensation{Calculate the RSIV indicator}x2:= If(x1 > Ref(x1, -1), 1, 0);x3:= If(x1 > Ref(x1, -1), x1 - Ref(x1, -1), 0);x4:= If(x1 < Ref(x1, -1), 1, 0);x5:= If(x1 < Ref(x1, -1), Ref(x1, -1) - x1, 0);x6:= Sum(x3, pds1) * Sum(x2, pds1);x7:= (Sum(x5, pds1) * Sum(x4, pds1)) + .00001;x8:= 100-(100/(1+(x6/x7)));

{Volatility threshold calculation}x9:= (ATR(pds3) / Mov(C, pds3, E)) * 100;x10:= x9 - LinRegSlope(x9, pds2);

{Plot the indicator}{Plot the indicator}Upper + x10;Upper;x8;{Fml("Northington RSIV Fast");}Lower;Lower - x10;

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Example

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Required Capabilities

Capabilities of a VBTA Trading System

• Oversold and Overbought• Trend Detection• Broad Market Integration

S t d R i t• Support and Resistance• Historical Volatility• Implied Volatility• Multi-Timeframe Verification• Multi-Timeframe Verification

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The FrameworkCapabilities Components TTI ATR Extreme TTI Fabric SD TTI Fabric Ratio LR-SD TTI RSIV-1

Application TTI StochEx TTI Fabric LG TTI Trend Strength TTI Composite1 Oversold / OverBought

Trending x x x xNon-Trending x x x x x xTTI Trend Entry x x

2 Trend DetectionTrending x xNon-Trending xTTI Trend Entry x x

3 Broad Market IntegrationT di

Capabilities of aVBTA Trading System

TrendingNon-TrendingTTI Trend Entry

4 Support and ResistanceTrendingNon-Trending

• Oversold and Overbought• Trend Detection• Broad Market Integration• Support and Resistance• Historical Volatility TTI Trend Entry

5 Historical VolatilityTrending x x x x x xNon-Trending x x x x x x xTTI Trend Entry x x x x

Historical Volatility• Implied Volatility• Multi-Timeframe Verification

6 Implied VolatilityTrendingNon-TrendingTTI Trend Entry

7 Multi Time Frame VerificationTrending x x x

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Trending x x xNon-Trending x x x x x xTTI Trend Entry x

Volatility-BasedTrading Bands (N Bands)

N Bands are calculation of price volatilityprice volatility.

They represent an extreme level of support and resistance

h ton a chart.

When price approaches the N Bands a reversal or at least aBands a reversal, or at least a pause is likely.

Higher significance when l tilit i hi hvolatility is higher.

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Volatility-BasedSupport and Resistance (S/R) Lines

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Volatility-BasedSupport and Resistance (S/R) Lines

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Other Examples

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Other Examples

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Other Examples

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Other Examples

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Other Examples

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Other Examples

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Live Charts

Live Charts of Your Choice

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Volatility-Based Technical Analysis

Kirk Northington

www.tradingtheinvisible.com

www.metaswing.com

kirk@metaswing.com or (910) 789-0673

Northington Trading Page 47tradingtheinvisible.com metaswing.com

Volatility-BasedT h i l A l iTechnical Analysis:Strategies for Trading the Invisble

Kirk Northington

With Companion Websitehttp://www.tradingtheinvisible.com

tradingtheinvisible.com

metaswing.com