managing an option portfolio and how automated trading makes it easier

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Rajib Ranjan Borah 3-August- 2013 Managing an Option Portfolio - and how automated trading makes it easier

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This presentation is a part of the series of webinars conducted by QI every month. This webinar was conducted on 3rd August, 2013. The topic was 'Managing an Option Portfolio and how Automated Trading makes it easier'. The session was be taken by Mr Rajib Ranjan Borah who is a leading expert in Options Market Making. The talk focused on (i) fundamentals of options trading, (ii) ways to Managing Options Positions, and (iii) Building Sophisticated Algorithmic Options Trading Strategies. To view a recording of the webinar, please email [email protected]

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Page 1: Managing an Option Portfolio and how Automated Trading makes it easier

Rajib Ranjan Borah

3-August-2013

Managing an Option Portfolio- and how automated trading makes it easier

Page 2: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Fundamentals

Strategies

Managing positions

Sophistication through

automation

Topics

Page 3: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

• Understanding basics of options and derivativesFundamentals

Strategies

Managing positions

Sophistication through

automation

Topics

Page 4: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

• A Few Simple Option Trading Strategies

Fundamentals

Strategies

Managing positions

Sophistication through

automation

Topics

Page 5: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

• Initiating and Managing Option Positions

• Handling risks – different risk management parameters

Fundamentals

Strategies

Managing positions

Sophistication through

automation

Topics

Page 6: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Topics

•Advanced Trading Strategies

• Complex Position Management using Automation

Fundamentals

Strategies

Managing positions

Sophistication through

automation

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

• Definitions:

• Derivative is a financial instrument whose price is derived from the price of some other financial instrument.

• Option is a special type of derivative instrument - the buyer of the option has the option (i.e. right but not the obligation) to buy/sell a specified amount of underlying asset at a specified price on or before a specified date

• Other types of common derivatives:Future: the owner of such a derivative is obligated to

buy/sell a specified amount of underlying asset at a specified price on a specified date

Forward: Same as futures, but traded OTC instead of in the exchange

Fundamentals Strategies Position Management Automation & Sophistication

Page 8: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

• Two types of options

• Call Options: Buyer has the option (but not the obligation) to buy the underlying

• Put Options: Buyer has the option (but not the obligation) to sell the underlying

•Defining Characteristics of Option Instruments• Strike: Price of the underlying at which the option can be exercised

• Expiry Date: The date at which the option can be exercised• Premium: Upfront payment made by the buyer of the option (to the seller)

•Option Styles• European: can be exercised only on expiry date

• American: can be exercised anytime prior to expiry date• Exotic – Bermudan, Asian, Binary, Barrier, etc

Fundamentals Strategies Position Management Automation & Sophistication

Page 9: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Fundamentals Strategies Position Management Automation & Sophistication

CALL OPTION PUT OPTIONBUYER

SELLER

The right (but not the obligation) to buy

The right (but not the obligation) to sell

The potential obligation to buy

The potential obligation to sell

Option Types elaborated

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Fundamentals Strategies Position Management Automation & Sophistication

Payoff from holding a call option instrument

Consider a Call Option on XYZ stock with strike = 30, expiry date = 30th August 201X

At Expiry the payoff of the call option for the buyer is as shown below:

Strike at 30

Will only exercise the call option if underlying at expiry is more than the strike

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Underlying price at expiry

For e.g., if the underlying price is at 36, the buyer of the option can buy the underlying at 30. Hence, a payoff of 6.

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Fundamentals Strategies Position Management Automation & Sophistication

Payoff from holding a put option instrument

Consider a Put Option on XYZ stock with strike = 30, expiry date = 30 th August 201X.

At Expiry the payoff of the put option for the buyer is as shown below:

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Strike at 30

For e.g., if the underlying price is at 23, the buyer of the option can sell the underlying at 30. Hence, a payoff of 7.

Will only exercise the call option if underlying at expiry is less than the strike

Page 12: Managing an Option Portfolio and how Automated Trading makes it easier

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited12

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Payoff - Buy Call Option

Underlying price at expiry

Premium

Breakeven Point

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-12-10

-8-6-4-2024

Payoff - Sell Call Option

Underlying price at expiry

20 22 24 26 28 30 32 34 36 38 40 42

-4-202468

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Payoff - Buy Put Option

Underlying Price at Expiry

20 22 24 26 28 30 32 34 36 38 40 42

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Payoff - Sell Put Option

Premium Strike

Fundamentals Strategies Position Management Automation & Sophistication

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Terminology – Moneyness

Fundamentals Strategies Position Management Automation & Sophistication

Terminology Call Option Put Option

In the Money (ITM) Underlying Price > Strike Underlying Price < Strike

At the Money (ATM) Underlying Price = Strike Underlying Price = Strike

Out the Money (OTM) Underlying Price < Strike Underlying Price > Strike

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Option Premium (price) components:

•Option price = Intrinsic Value + Time Value

• Intrinsic Value: Immediate value of the option given the current relationship between the price of underlying and the price of the option For call options, intrinsic value = underlying – option strike For put options, intrinsic value = option strike - underlying

• Time Value: Because the buyer of the option has the upside benefits but not downside obligations, therefore future price movements in the underlying can benefit (but not harm) the buyer – therefore there is an additional value for the option instruments for the extra benefits future price movements might bring

An option with no intrinsic value is an Out of The Money Option

Fundamentals Strategies Position Management Automation & Sophistication

Page 15: Managing an Option Portfolio and how Automated Trading makes it easier

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Option Pricing Methodology

•Pricing depends on key characteristics of instrument • Option Strike• Option Expiry date• Current Underlying Price• Characteristics of price change in underlying (volatility,

price jumps, etc)• Interest Rate & Stock Borrowing Rates• Dividends• Option type (Call/Put)• Option Style (American/European)

Fundamentals Strategies Position Management Automation & Sophistication

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Option Pricing Methodology

•Common Pricing Formulations

Fundamentals Strategies Position Management Automation & Sophistication

Underlying Characteristic Pricing MethodologyConstant Volatility Black ScholesConstant Volatility with Dividends Black Scholes MertonConstant Volatility with Poisson Jumps Merton Jump DiffusionVolatility as a function of Underlying price CEV Volatility as a function of Underlying price & time to expiry Derman KaniVolatility is volatile HestonAmerican type expiry Barone Adesi Whaley, Bjerksund StenslandCurrency Options Garman Kohlhagen

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Simple Option Trading Strategies

•Option Trading can be used to express following types of views• view on the price of the underlying in the future• view on the volatility of the price movements of the

underlying• view on interest rates• combined view on more than one of the above factors

Fundamentals Strategies Position Management Automation & Sophistication

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Expressing views on the price(/direction of price change) of the underlying

•Naked Call/Put option•Call Bull Spread / Put Bull Spread•Call Bear Spread / Put Bear Spread•Combo/Risk Reversal•Ratio Spread• Ladder•Call / Put Strip•Synthetic underlying – conversal / reversal•Diagonal Calendar Spread

Fundamentals Strategies Position Management Automation & Sophistication

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Expressing views on the volatility (of price changes) of the underlying

•Straddle•Strangle•Guts•Butterfly•Condor• Iron Butterfly• Iron Condor•Call / Put Strip•Calendar Spread•Diagonal Calendar Spread

Fundamentals Strategies Position Management Automation & Sophistication

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Expressing views on interest rates

• Jelly Rolls•Box

Fundamentals Strategies Position Management Automation & Sophistication

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Risk Evaluations

•First order risks:• Delta – i.e. change in option price with change in underlying price• Vega – i.e. change in option price with change in underlying volatility• Theta – i.e. change in option price as time to expiry reduces• Rho – i.e. change in option price with change in interest rates

•Second Order risks• Gamma ( change of Delta with change in Underlying price)• Vanna ( change of Delta with change in Volatility)

• Charm ( change of Delta with change in Time)• Vomma ( change of Vega with change in Volatility)• Veta ( change of Vega with change in Time)• Change of Vega with change in Underlying price• Vera (change of Rho with change in Volatility)

Fundamentals Strategies Position Management Automation & Sophistication

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Risk Evaluations

•Third order risks:• Color ( change of Gamma with change in Time)• Speed ( change of Gamma with change in Underlying Price)

• Zomma ( change of Gamma with change in Volatility)• Ultima ( change of Vomma with change in Volatility)

•Other risks• Rega - Volatility curve skew• Sega - Volatility curve wings• Forward Volatility (Volatility between two expiry periods)• Skewed gamma (change in Gamma with change in volatility curve

skew)• Skewed delta (change in Delta with change in volatility curve skew)

Fundamentals Strategies Position Management Automation & Sophistication

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Risk Evaluations (examples)• Delta with changing underlying price

• Delta with changing volatility (Vanna)

Fundamentals Strategies Position Management Automation & Sophistication

• Delta with changing time (Charm)

• Gamma with changing underlying price

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Risk Evaluations (examples)• Gamma with changing time (Color)

• Gamma with changing volatility (Zomma)

Fundamentals Strategies Position Management Automation & Sophistication

• Option price at different volatility levels

• Vega at different underlying levels

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Risk Evaluations (examples)• Vega with changing time (Veta)

• Vega with changing volatility (Vomma)

Fundamentals Strategies Position Management Automation & Sophistication

• Theta with changing time

• Rho at different levels of underlying Price

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An example of a somewhat sophisticated strategy which benefits from automation

• Index constituted of a basket of stocks (e.g. NIFTY50 consists of 50 stocks)• If all stocks (in the index) go up by 5%, then index also

goes up by 5%• However, if the volatility of all stocks go up by 5%, can

we infer the change in volatility of the index ? Not a simple answer. Depends upon correlation amongst

stocks

• Volatility used to price index options = function (volatility used to price stock options, correlation level amongst stocks)

• However, the known values are (i) volatility used to price index options and (ii) volatility used to price stock options we can determine the implied average correlation amongst

stocks we can then trade our view on this implied average

correlation amongst stocks

Fundamentals Strategies Position Management Automation & Sophistication

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Complexities in position management of aforesaid strategy

• Approximation of index basket • maintaining position in stocks in proportion to their weightage in the index

•Position spread across index options and stock options•Calculating total portfolio greeks by combining greeks

for individual stocks & index• for e.g.: portfolio vega = function ( vega position in index

options + vega position in stock1 options + ... + vega position in stockn options )

• As the market moves, the position has to be rolled from one set of option strikes to another

• Delta to be hedge periodically

Fundamentals Strategies Position Management Automation & Sophistication

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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

Any questions ?

Thank You

MerciDanke

GraciasArigatoAsanteGrazi

Shukriya

See you in the QI program – EPAT (Executive Program on Algorithmic Trading)

[email protected]

Fundamentals Strategies Position Management Automation & Sophistication