MANAGING OPTIONS POSITIONS MARCH 2013

INTRODUCTION

OPTION VALUATION & RISK MEASURES – THE “GREEKS”

PRE-TRADE

• RICH VS. CHEAP ANALYSIS

• SELECTING TERM STRUCTURE

PORTFOLIO CONSTRUCTION

• CONDITIONAL RISK PROFILES

• STRESS TESTING

BIOGRAPHIES / CONTACT INFORMATION

APPENDIX

DISCLAIMER

2

AGENDA

INTRODUCTION

• MICHAEL SCHMANSKE

Glenshaw Capital, Founder & Senior PM

• DAVID MITCHELL

Bloomberg, Equity Derivatives Application Specialist

3

OPTIONS RISK MEASURES – “THE GREEKS”

4

• DELTA

The change in the price of an option for a $1 move in the price of the

underlying stock.

• GAMMA

The change in delta for a $1 change in the price of the underlying stock.

• VEGA

The change in the price of an option for a one-point change in implied volatility.

• THETA

The change in the price of an option given a one-day decrease in the time

to expiration.

• RHO

The change in price of an option given a 1% change in the risk-free

interest rate.

OPTION VALUATION

5

VALUE FILTERS

When trading an option position to efficiently meet an investment objective, an

investor must consider the variables that affect both the price and performance of the

portfolio.

• Implied volatility

• Volatility surface (including skew)

• Conditional risks

VALUATION MODEL INPUTS

• Underlying Price

• Strike Price

• Time to Expiration

• Risk-Free Interest Rate

• Volatility & Dividends

OVME <GO>

PRE-TRADE: RICH VS. CHEAP ANALYSIS

6

• DETERMINING “RICH” VS. “CHEAP” IMPLIED VOLATILITY

1. Use a data analysis tool to calculate the realized volatility for multiple

time periods.

2. Compare realized volatility to the current implied volatility in the

options.

3. Repeat this procedure for similar underlying assets, then compare

spreads of implied to realized volatility.

4. Consider any asset-specific catalysts (earnings, pending

announcements or macroeconomic factors) that may justify the

presence of a particular spread.

PRE-TRADE: RICH VS. CHEAP ANALYSIS

7

VOLATILITY DASHBOARD

Tabs available for index, commodity and currency volatility data

VCA <GO>

PRE-TRADE: RICH VS. CHEAP ANALYSIS

8

VCA <GO>

Implied correlation calculations for indices. ETFs available soon.

PRE-TRADE: RICH VS. CHEAP ANALYSIS

9

GV <GO>

PRE-TRADE: RICH VS. CHEAP ANALYSIS

10

G <GO>

CROSS-ASSET: SPX VS CDX

IDEA GENERATION CASE STUDY - Quantitative Analysis

FRONT

MONTH

SKEW

11

-12.6

-10.6

-8.6

-6.6

-4.6

-2.6

-0.6

1 Month 2 Months 3 Months 6 Months 1 Year 2 Years

Min

Max

Mean

99 Percentile

1 Percentile

Skew Case Study

SPX PUT SKEW

Short term skew is

priced very high to

historical levels

-$60

-$40

-$20

$0

$20

$40

$60

1100 1150 1200 1250 1300 1350 1400

IDEA GENERATION CASE STUDY - Trade Initiation

SKEWED PUT CONDOR PAYOUT

12

ATTRIBUTES

Low initial premium

Short skew

Positive carry

Limits loss potential to

$55

THE PORTFOLIO

Buys 1x the 1350 put

Sells 1x the 1300 put

Sells 1x the 1250

Buys 1x the 1150 put

Net premium

investment of $5.00.

PRE-TRADE: SELECTING TERM STRUCTURE

13

• SELECTING THE APPROPRIATE SEGMENT

1. Use data analysis tool and graph the term structure of implied volatility

surface.

2. Compare the current implied volatility surface to the asset’s historical

implied surfaces.

3. Consider whether skew is relatively steep or flat as compared with the

asset’s historical data.

4. Observe the asset’s term structure to understand whether it is inverted

or upward-sloping.

5. Compare the term structure to the asset’s historic term structure data

and to that of similar assets.

OPTIONS RISK MEASURES –

IMPLIED VOLATILITY SURFACE

14

OVDV <GO>

PRE-TRADE: SELECTING TERM STRUCTURE

15

OSCH <GO>

PRE-TRADE: SELECTING TERM STRUCTURE

16

OMON <GO>

PRE-TRADE: SELECTING TERM STRUCTURE

17

TRMS <GO>

OMON R <GO>

IDEA GENERATION CASE STUDY - Fundamental Analysis

18

1050

1100

1150

1200

1250

1300

1350

1400

1450

1500

0%

5%

10%

15%

20%

25%

Jan-11 Mar-11 May-11 Jul-11 Sep-11 Nov-11 Jan-12 Mar-12 May-12

1X2 CALL SPREAD

Implied Volatility

SPX Index

IVol SPX

-$60

-$40

-$20

$0

$20

$40

$60

1300 1325 1350 1375 1400 1425 1450 1475

IDEA GENERATION CASE STUDY - Hedging Analysis

19

ATTRIBUTES

Short gamma

Short vega

Low initial premium

Useful in high volatility

environment where a

controlled rebound is

expected

1X2 CALL SPREAD PAYOUT

THE PORTFOLIO

2 Month 1350 – 1400 call

1x2

Buy 1x 1350 call

Sell 2x 1400 call

Net premium is $5.00

IDEA GENERATION CASE STUDY - Hedging Analysis

20

1X2 CALL SPREAD PAYOUT OVER TIME

1X2 CALL SPREAD DELTA OVER TIME

OSA <GO>

PORTFOLIO CONSTRUCTION

21

• UNDERSTANDING CONDITIONAL RISK PROFILES

1. Recognize an options portfolio is dynamic and the goal is to create

limited loss scenarios that can be actively managed and used as

efficient trade vehicles.

2. Consider what the expected move would be in implied volatility given

different price movement scenarios.

3. Consider the impact of time on the options positions. Determine

whether the position should be unwound, rolled or otherwise hedged.

PORTFOLIO CONSTRUCTION: STRESS TESTING

22

OSA <GO>

PARALLEL VOL SHIFT UP

CUSTOM SHIFT OF SKEW &

TERM STRUCTURE

PORTFOLIO CONSTRUCTION: STRESS TESTING

23

OSA <GO>

PORTFOLIO-LEVEL GREEKS

CUSTOM SHOCKS & STRESS

TESTING

PORTFOLIO CONSTRUCTION: STRESS TESTING

24

OSA <GO>

PRICE SHIFT TO A BENCHMARK

WILL SHIFT PORTFOLIO

CONSTITUENTS BY RELATED BETA

DETAILS OF P/L AND GREEKS AT

EACH PRICE POINT

BIOGRAPHIES

MICHAEL SCHMANSKE – Glenshaw Capital, Founder & Senior Portfolio Manager

Mr. Schmanske founded Glenshaw Capital, an equity volatility hedge fund, July 2012. Before Glenshaw, he

was a Managing Director at Barclays and the Head of Index Volatility trading. Prior to Barclays, Michael was

the Head of US Index Volatility trading at Lehman Brothers. Michael built a trading platform that became the

largest volatility trading desk in the financial services industry. Michael and his team developed a unique

trading strategy, which utilized proprietary theoretical pricing models for the VIX, skew, the volatility of volatility

and introduced a cross-asset approach to risk management. Building on this market-leading experience in the

VIX, Michael oversaw the launch of the volatility asset class platform which includes the iPath volatility ETNs

(VXX and VXZ). Michael began his trading career as a market marker for Susquehanna International Group on

the CBOE, becoming the lead trader and risk manager for high-cap index derivatives products in 1998.

He holds a BS in Aerospace Engineering from MIT and a MSE in Mechanical and Aerospace Engineering from

Princeton University. Currently, Michael serves on the board of directors for the CBOE Futures Exchange.

DAVID MITCHELL – Bloomberg, Equity Derivatives Applications Specialist

Mr. Mitchell joined Bloomberg in 2009 as an Applications Specialist focusing on listed and OTC derivatives,

and also convertible bonds. In this capacity he interacts with buy-side and sell-side derivatives traders and

portfolio managers to support all related analytical, market surveillance, and transaction-related functionality

available thru the Bloomberg Professional Service. Prior to joining Bloomberg, Mr. Mitchell worked as a

Managing Director in the Structured Equity Products group at Bear Stearns & Co. Prior to joining Bear Stearns,

Mr. Mitchell worked for Deutsche Bank and Merrill Lynch in equity derivatives sales and structuring.

Mr. Mitchell has a BS in Electrical Engineering from the University of Maryland and an MBA in Finance and

Statistics from the NYU Stern School of Business..

25

CONTACT INFORMATION

26

MICHAEL SCHMANSKE

investor@glenshawcapital.com

+1 (646) 237-7882

www.glenshawcapital.com

DAVID MITCHELL

dmitchell28@bloomberg.net

+1 (212) 617-5606

www.bloomberg.net

APPENDIX: VOLATILITY

27

• HISTORICAL VOLATILITY

Aggregate measure of past price fluctuations of underlying instrument

Annualized standard deviation of the log returns;

• IMPLIED VOLATILITY

Embedded prediction of future price fluctuations based on solving options-pricing

formula after including market parameters.

2

1

2

1

252ii t

n

i

t xxn

t

tt

S

Sx 1ln

APPENDIX: SENSITIVITY ANALYSIS

28

HOW CHANGES IN PARAMETERS AFFECT OPTION VALUE

• DELTA Ratio of change in underlying to change in option’s price (1st derivative) Range=-1 to+1

Delta=the N(d1) term of the Black Scholes Equation

100 WTI Call. Delta is 0.52

WTI +$1.00

Option Increases by $0.52

A snapshot

A hedging parameter.

Long 100 of the 100 WTI Call. SELL 52 of the WTI Futures = Delta Neutral

• GAMMA Rate of Change of Delta wrt change in underlying price. (2nd derivative/acceleration)

Gamma=0.1/1.00 move

WTI +$1.00

Option Delta goes from 0.52 to 0.62

Highest for ATM

Used to measure the convexity of the option delta

APPENDIX: SENSITIVITY ANALYSIS

29

HOW CHANGES IN PARAMETERS AFFECT OPTION VALUE

• VEGA Sensitivity to a 1% change in implied volatility.

Rule of thumb: ATM option: % change in vol=% change in option’s value

Highest for ATM

WTI 100c WTI=100 Call=4.00

Vega=.04

IVol 30 goes to 30.3 (1%) Option now 4.04

• THETA Time decay

The “rent” you must pay if Long or collect if you are short

The “bleed”

If trading a delta-neutral book, it let’s you know how much the market has to move for the portfolio to make money

• RHO Interest rate sensitivity

Shows the sensitivity to changes in interest rates.

The model uses the risk-free rate to provide the discounting factor.

DISCLAIMER & RISKS This presentation is for educational and informational purposes only and should not be construed as legal, tax, investment or other advice. This

document does not constitute an offer to sell, or a solicitation of an offer to buy

any interest. Any offer will be made pursuant to a private offering memorandum, which should be reviewed carefully before making an

investment.

Structured securities, derivatives, and options are complex instruments that are not suitable for all investors, may involve a high degree of risk,

and may be appropriate investments only for sophisticated investors who are capable of understanding and assuming the risks involved.

Prior to buying or selling an option, an investor should read and understand the booklet "Characteristics and Risks of Standardized Options."

You can access and download a copy of the booklet on The Options /Clearing Corporations'(OCC) website at

http://www.theocc.com/about/publications/character-risks.jsp. This link reference is provided as a courtesy and does not imply that the OCC is

endorsing IT or its products. This booklet is also available for free from your broker or from any of the U.S. options exchanges.

• Call or put purchasing: The risk of purchasing a call/put is that investors will lose the entire premium paid.

• Uncovered call writing: The risk of selling an uncovered call is unlimited and may result in losses significantly greater than the premium

received.

• Uncovered put writing: The risk of selling an uncovered put is significant and may result in losses significantly greater than the premium

received.

• Call or put vertical spread purchasing (same expiration month for both options): The basic risk of effecting a long spread transaction is

limited to the premium paid when the position is established.

• Call or put vertical spread writing/writing calls or puts (usually referred to as uncovered writing), combinations or straddles (same expiration

month for both options): The basic risk of effecting a short spread transaction is limited to the difference between the strike prices less the

amount received in premiums.

• Call or put calendar spread purchasing (different expiration months and short must expire prior to the long): The basic risk of effecting a long

calendar spread transaction is limited to the premium paid when the position is established.

30