Upload
others
View
4
Download
2
Embed Size (px)
Citation preview
Rajib Ranjan Borah & Nitesh Khandelwal
QuantInsti Bangkok, 6 Oct 2014
Option Trading Techniques: A Trader’s Approach for a Retail Investor
Option Fundamentals
2
Fundamentals
Strategies
Managing
positions
Sophistication
through
automation
Topics
3
Topics
• Understanding basics of options
and derivatives
Fundamentals
Strategies
Managing
positions
Sophistication
through
automation
4
Topics
• A Few Simple Option Trading Strategies
Fundamentals
Strategies
Managing
positions
Sophistication
through
automation
5
Topics
• Initiating and Managing Option Positions
• Handling risks – different risk management parameters
Fundamentals
Strategies
Managing
positions
Sophistication
through
automation
6
Topics
Fundamentals
Strategies
Managing
positions
Sophistication
through
automation
• Advanced Trading Strategies
• Complex Position Management using Automation
7
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: Similar to futures, but traded OTC instead of in the exchange
Fundamentals Strategies Position Management Automation & Sophistication
8
• 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
Option Types
9
CALL OPTION PUT OPTION
B
U
Y
E
R
S
E
L
L
E
R
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
Fundamentals Strategies Position Management Automation & Sophistication
10
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
0
2
4
6
8
10
12
14
20 22 24 26 28 30 32 34 36 38 40 42
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.
Fundamentals Strategies Position Management Automation & Sophistication
11
Payoff from holding a put option instrument
Consider a Put Option on XYZ stock with strike = 30, expiry date = 30th August
201X.
At Expiry the payoff of the put option for the buyer is as shown below:
0
2
4
6
8
10
12
20 22 24 26 28 30 32 34 36 38 40 42
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
Fundamentals Strategies Position Management Automation & Sophistication
12
12
-4
-2
0
2
4
6
8
10
12
20 22 24 26 28 30 32 34 36 38 40 42
Underlying price at expiry
Payoff - Buy Call Option
Premium
Breakeven Point
-12
-10
-8
-6
-4
-2
0
2
4
20 22 24 26 28 30 32 34 36 38 40 42
Underlying price at expiry
Payoff - Sell Call Option
-4
-2
0
2
4
6
8
10
20 22 24 26 28 30 32 34 36 38 40 42
Underlying Price at Expiry
Payoff - Buy Put Option
-10
-8
-6
-4
-2
0
2
4
20 22 24 26 28 30 32 34 36 38 40 42
Payoff - Sell Put Option
Premium Strike
Fundamentals Strategies Position Management Automation & Sophistication
13
Moneyness
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
Fundamentals Strategies Position Management Automation & Sophistication
14
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
15
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
16
Option Pricing Methodology
• Common Pricing Formulations
Underlying Characteristic Pricing Methodology Constant Volatility Black Scholes Constant Volatility with Dividends Black Scholes Merton Constant Volatility with Poisson Jumps Merton Jump Diffusion Volatility as a function of Underlying price CEV Volatility as a function of Underlying price & time to expiry
Derman Kani
Volatility is volatile Heston American type expiry Barone Adesi Whaley, Bjerksund Stensland Currency Options Garman Kohlhagen
Fundamentals Strategies Position Management Automation & Sophistication
17
Thank You
Merci
Danke
Gracias
Arigato
Asante
Grazi
Shukriya
[email protected] / +91 – 9920 – 44 - 88 – 77 / +65 – 6549 – 7213
Go Algo! Join QI’s EPAT (Executive Program on Algorithmic Trading)!
Fundamentals Strategies Position Management Automation & Sophistication
Question & Answers
Global Trends in Option Trading
Rajib Ranjan Borah & Nitesh Khandelwal
QuantInsti Bangkok, 6th October 2014
Options Trading Techniques:
A Trader’s Approach for a Retail Investor
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
As a trading manager, how do you decide which geographies to trade ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Regulations
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Regulations
Market Size
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Regulations
Market Size
Competition
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Regulations
Market Size
Competition
Technology
How do you decide: where to trade?
As a trading manager, how do you decide which geographies to trade ? – Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?
• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ? • What are the listed instruments ?
• What is the volume traded ?
– Will I be able to make profits ? • What is the level of sophistication of competition ?
• Who are the leading players ?
– What are the complexities to connecting to these markets ? • Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols
• Brokers to connect to these markets
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Regulations
Market Size
Competition
Technology
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Trading in various landscapes
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Equity volumes – avg monthly volumes (USD million)
Americas
Bermuda SE 4
BM&FBOVESPA 67,550
Buenos Aires SE 279
Colombia SE 2,162
Lima SE 338
Mexican Exchange 14,780
NASDAQ OMX 798,729
NYSE Euronext
(US) 1,141,704
Santiago SE 3,640
TMX Group 114,290
Total region 2,143,474
APAC
Australian SE 73,463
BSE India 7,046
Bursa Malaysia 12,323
Colombo SE 130
GreTai Securities Market 11,241
HoChiMinh SE 869
Hong Kong Exchanges 110,281
Indonesia SE 9,664
Japan Exchange Group - Osaka 17,594
Japan Exchange Group - Tokyo 525,411
Korea Exchange 107,050
National Stock Exchange India 39,913
New Zealand Exchange 752
Philippine SE 3,889
Shanghai SE 310,927
Shenzhen SE 321,542
Singapore Exchange 23,410
Taiwan SE Corp. 51,996
The Stock Exchange of Thailand 31,335
Total region 1,658,838
Europe
Athens Exchange 1,981
BME Spanish Exchanges 74,464
Budapest SE 869
Casablanca SE 263
Cyprus SE 3
Deutsche Börse 111,212
Irish SE 1,206
Ljubljana SE 33
Luxembourg SE 12
Malta SE 6
Moscow Exchange 20,167
NASDAQ OMX Nordic Exchange 52,153
NYSE Euronext (Europe) 138,490
Oslo Børs 10,200
SIX Swiss Exchange 56,413
Wiener Börse 2,154
Total region 469,626
MEA: Middle East + Africa
Abu Dhabi SE 1,816
Amman SE 285
Borsa Istanbul 34,947
Cyprus SE 3
Egyptian Exchange 1,077
Irish SE 1,206
Johannesburg SE 28,608
Kazakhstan SE 58
Mauritius SE 26
Muscat Securities Market 478
Qatar Exchange 1,714
Saudi Stock Exchange - Tadawul 30,202
Tel Aviv SE 4,475
Total region 104,895
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Index FO – annual volumes (USD million)
Americas Options Future
BM&FBOVESPA 238 119.0 504 342.0
Bourse de Montreal 3 550.8 555 764.0
CBOE Future Exchange x NA
Chicago Board Options Exchange NA x
CME Group 9 987 400.0 46 628 400.0
Colombia SE x 19.2
ICE Futures US 6 516.0 2 962 600.0
International Securities Exchange NA NA
MexDer 1 761.5 30 896.1
NASDAQ OMX (US) NA NA
NYSE Euronext (US) NA NA
APAC Options Future
ASX Derivatives Trading 441 915.0 2 561.6
ASX SFE Derivatives Trading 46 330.5 1 204 770.0
Bombay SE 1 168 300.0 10 210.9
Bursa Malaysia Derivatives NA 71 423.6
China Financial Futures Exchange NA 22 909 400.0
Hong Kong Exchanges 1 838 560.0 4 539 370.0
Korea Exchange 67 864 200.0 5 855 830.0
National Stock Exchange India 4 668 890.0 498 918.0
Osaka SE NA 7 468 830.0
Shanghai Futures Exchange 0.0 0.0
Singapore Exchange NA NA
TAIFEX 1 485 740.0 1 480 410.0
Thailand Futures Exchange NA NA
Tokyo SE Group NA 2 630 990.0
EMEA Options Future
Athens Derivatives Exchange 432.3 28 113.5
BME Spanish Exchanges 60 489.2 672 335.0
Borsa Istanbul 35.1 63 631.4
Budapest SE 0.0 341.8
EUREX 13 764 800.0 18 691 000.0
ICE Futures Europe 0.0 0.0
Johannesburg SE 2 946.5 487 400.0
Moscow Exchange 118 079.0 752 618.0
NYSE.Liffe Europe 3 297 390.0 6 282 720.0
OMX Nordic Exchange 151 241.0 573 599.0
Oslo Børs 439.1 1 752.9
Tel Aviv SE 641 250.0 976.1
Wiener Börse 56.2 22 030.8
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Equity FO – annual volumes (USD million)
Americas Options Future
BM&FBOVESPA 994 498.0 NA
Bourse de Montreal 73 960.1 0.0
Buenos Aires SE NA NA
Chicago Board Options Exchange NA NA
Colombia SE NA 480.6
International Securities Exchange NA NA
MexDer 90.0 13.4
NASDAQ OMX (US) NA NA
NYSE Euronext (US) 104 464.0 NA
BM&FBOVESPA 994 498.0 NA
Bourse de Montreal 73 960.1 0.0
APAC Options Future
ASX Derivatives Trading 284 474.0 11 867.0
Bombay SE 3 076.7 7 442.2
Hong Kong Exchanges 167 335.0 1 485.5
Korea Exchange 0.0 56 761.0
National Stock Exchange India 416 644.0 811 791.0
New Zealand 0.0 NA
Osaka SE NA NA
Shanghai Futures Exchange 0.0 0.0
TAIFEX 177.6 22 743.6
Thailand Futures Exchange NA NA
Tokyo SE Group NA NA
EMEA Options Future
Athens Derivatives Exchange 17.0 2 450.0
BME Spanish Exchanges 31 668.0 15 271.2
Borsa Istanbul 14.4 11.9
Budapest SE 0.0 2 684.7
EUREX 784 435.0 752 475.0
ICE Futures Europe 0.0 0.0
Johannesburg SE 311.3 16 625.5
Moscow Exchange 2 829.0 106 339.0
NYSE.Liffe Europe 343 406.0 455 497.0
OMX Nordic Exchange 52 967.4 4 658.3
Oslo Børs 1 874.3 1 836.7
Tel Aviv SE 4 335.2 NA
Wiener Börse 307.0 0.0
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Currency – annual volumes (USD million)
Americas Options Future
BM&FBOVESPA 435 060.6 4 196 493.1
Bourse de Montreal 68.2 0.0
CME Group 2 076 378.0 25 281 026.0
Colombia SE NA 10 674.9
ICE Futures US 3 410.0 658 019.0
MexDer 181.9 135 749.3
APAC Options Future
Hong Kong Exchanges NA 13 948.8
Korea Exchange NA 532 393.2
National Stock Exchange India 252 897.5 614 399.2
Osaka SE NA 61 932.8
Thailand Futures Exchange NA NA
EMEA Options Future
Borsa Istanbul NA 4 658.1
Johannesburg SE 8 934.8 25 155.6
Moscow Exchange 4 040.0 483 914.0
NYSE.Liffe Europe 2 324.6 37.3
Tel Aviv SE 108 322.8 0.0
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Interest Rate – annual volumes (USD million)
Americas Options Future
BM&FBOVESPA 3 600 770.0 18 193 900.0
Bourse de Montreal 569 518.0 23 217 400.0
Buenos Aires SE NA NA
CME Group 163 885
000.0 614 271
000.0
Colombia SE NA 32 850.9
MexDer NA 93 456.0
NYSE Euronext (US) NA NA
APAC Options Future
ASX SFE Derivatives Trading 393 778.0 47 596 300.0
Bombay SE NA NA
China Financial Futures Exchange NA 50 232.7
Hong Kong Exchanges NA 7.2
Korea Exchange NA 4 084 080.0
National Stock Exchange India NA NA
Shanghai Futures Exchange 0.0 0.0
TAIFEX NA 2.2
Tokyo SE Group NA NA
EMEA Options Future
BME Spanish Exchanges 0.0 1 413.4
EUREX 11 544 400.0 76 220 100.0
Johannesburg SE 47.7 54 109.3
London Metal Exchange NA NA
Moscow Exchange 0.0 5 323.7
NYSE.Liffe Europe 175 658 000.0 443 350 000.0
OMX Nordic Exchange 915 175.0 3 560 020.0
Tel Aviv SE NA NA
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
ETF – annual volumes (USD million)
Americas ETF ETF Opt
BM&FBOVESPA 11 366.8 138.7
Colombia SE 1 070.1
Lima SE 9.8
Mexican Exchange 104 903.9 1.8
NASDAQ OMX 6 695 703.4 NA
NYSE Euronext (US) 3 589 241.4 48 077.3
Santiago SE 117.1
TMX Group 73 824.8
Bourse de Montreal NA 5 123.0
CME NA NA
ISE NA NA
APAC ETF ETF Opt
Australian SE 7 487.3
BSE India 1 118.3
Bursa Malaysia 43.6
Hong Kong Exchanges 116 431.5 16 776.7
Indonesia SE 2.1
Japan Exchange Group - Osaka 73 386.2 NA
Japan Exchange Group - Tokyo 163 170.1 NA
Korea Exchange 178 724.6
National Stock Exchange India 2 132.8
New Zealand Exchange 59.6
Shanghai SE 109 240.5
Shenzhen SE 36 707.2
Singapore Exchange 2 591.1
Taiwan SE Corp. 9 496.8
The Stock Exchange of Thailand 250.3
EMEA ETF ETF Opt
Athens Exchange 14.7
BME Spanish Exchanges 5 732.2
Borsa Istanbul 4 350.9
Budapest SE 1.9
Deutsche Börse 162 958.7
Irish SE 19.3
Johannesburg SE 5 624.3 ~ 0
Ljubljana SE 0.0
Luxembourg SE 0.0
NASDAQ OMX Nordic Exchange 15 593.7
NYSE Euronext (Europe) 100 747.8
Oslo Børs 4 736.7
Saudi Stock Exchange - Tadawul 18.6
SIX Swiss Exchange 98 074.8
Wiener Börse 5.3
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Commodity– annual volumes (USD million)
Americas Options Future
BM&FBOVESPA 602.9 21 666.2
CME Group 10 561
200.0 47 823 300.0
Colombia SE NA 6.6
ICE Futures Canada 47.4 57 599.8
ICE Futures US 305 023.0 1 347 450.0
NYSE Euronext (US) NA NA
APAC Options Future
ASX SFE Derivatives Trading 5 284.0 17 687.1
Bursa Malaysia Derivatives NA 151 944.0
Dalian Commodity Exchange NA 7 676 520.0
Korea Exchange NA 161.1
New Zealand 0.0 132.1
Shanghai Futures Exchange NA 9 852 290.0
TAIFEX 717.9 1 146.7
Zhengzhou Commodity Exchange NA 3 074 910.0
EMEA Options Future
Borsa Istanbul NA 807.7
Budapest SE 0.0 138.5
ICE Futures Europe 31 495.0 29 469 200.0
Johannesburg SE 349.9 50 124.3
London Metal Exchange 663 968.0 13 965 900.0
Moscow Exchange 309.6 46 291.3
NYSE.Liffe Europe 1 918.0 403 586.0
Q & A
Relevant factors for analyzing different markets → Current landscape in different geographies → QA
Copyright © 2014 by QuantInsti Quantitative Learning Private Limited.
Although great care has been taken to ensure accuracy of the information
in this presentation – however the author (and QuantInsti) accepts no
liability or warranty for the precision, correctness or completeness of any
statement, estimate or opinion. QuantInsti also accepts no liability for the
consequences of any actions taken on the basis of the information
provided.
The slides of this presentation cannot be taken separately from the whole
set of slides.
Prior approval from QuantInsti is necessary before usage of this
presentation for educational and (or) commercial purposes.
This document provides an outline of a presentation and is incomplete
without the accompanying oral commentary and discussion.
Disclaimer
Rajib Ranjan Borah & Nitesh Khandelwal
QuantInsti Bangkok, 6 Oct 2014
Option Trading Techniques: A Trader’s Approach for a Retail Investor
Option Trading Strategies
Directional strategies:
• Long / short call • Long / short put
• Long / short call(/bull) spread
• buy lower strike, sell higher strike
• Long / short put(/bear) spread • sell lower strike, buy higher strike
• Long / short combo
• call at higher strike, put at lower
Option Strategies – basic strategies Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Volatility strategies:
• Long / short straddle • Put and call of same strike
• Long / short strangle • OTM Put and call of different strikes
• Long / short gut • ITM Put and call of different strikes
• Long / short butterfly
• Buy wings and sell ATM – or vice versa • Long / short condor
• Buy farther away OTMs and sell nearest OTMs – or vice versa
• Long / short iron butterfly • Buy straddle & sell strangle
Option Strategies – basic strategies Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Time Value strategies:
• Long / short calendar spread (a.k.a. horizontal trades) • Sell near expiry options, buy far expiry
options
• Long / short diagonal calendar spread • Same as above but different strikes
• Interest Plays • Sell underlying and deep ITM puts • Earn interest on cash from selling
Option Strategies – basic strategies Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Hedging strategies
• Protective Calls • Short underlying hedged using long OTM call
• Protective Puts • Long underlying hedged using long OTM put
• Covered Call Writes • Long underlying to cover short OTM call • Short underlying to cover short OTM put
• Fences or Collars • Combining Protective option with covered writes Long Underlying + Long OTM puts + short OTM
calls
Option Strategies – basic strategies Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Backspread (also known as ratio backspread / long ratio
spread)
• Delta neutral spread consisting of more long options than short • Options with lower delta purchased • Options with higher delta sold
Ratio Vertical Spread (also known as ratio spread, short ratio spread, vertical
spread or front spread) • Basically the opposite of backspreads
• Options with higher delta purchased • Options with lower delta sold
Option Strategies – volatility spreads Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Volatility Curve Skew Trades
• Risk Reversal (a.k.a. risky)
• Long OTM calls + Short OTM puts • Often a bet on vol curve skew
Advanced Volatility Spreads:
• Forward Volatility Based Spreads • Volatility for forward periods
Option Strategies – volatility spreads Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
• Conversal: • Synthetically short underlying + long
underlying • (Short call + long put) + long
underlying
• Reversal: • Synthetically long underlying + short
underlying • (Long call + short put) + short
underlying
• In both cases, risks are minimal (Except dividend & interest rates exposures. Or pin risks for stock settled options)
Option Strategies – simple option arbitrages Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
• Dispersion:
• Index constituted of a basket of stocks • Implied volatility of index options should
therefore be linked to implied volatility of stock options (of stocks making up the index)
• Dispersion trading is a way to trade “Implied Correlation” between volatility of index and index components i.e. bet on the degree to which constituent
stocks disperse
Option Strategies – correlation & dispersion Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
• Dispersion (contd) • The volatility of a basket with two assets is
• Where ρ is the correlation coefficient • Volatility of a basket with ‘n’ assets will be
• Instead of n.(n-1)/2 correlations for a basket of n stocks, define a single average correlation
Option Strategies – correlation & dispersion Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
• The strategy becomes: • Buy index volatility & sell component
volatility when correlation is towards lower band
• Do reverse when correlation is towards upper band
Option Strategies – correlation & dispersion Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Option Strategies – advanced option arbitrages Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
• Dividend Plays • Buying underlying and selling deep ITM
calls
• Skew Dividends • Dividend expectations at different
underlying levels
Option Strategies – advanced option arbitrages
• Boxes: • A conversal at one exercise price/strike • A reversal at another exercise price/strike
• Long box = • Synthetically long the lower exercise price • Synthetically short the higher exercise price
• What would be the price of a 90/100 box ? • Value of box at expiry (=10) – carrying costs
• Often cheaper way of borrowing funds from
the market
Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
Option Strategies – advanced option arbitrages Directional
Volatility
Time Value
Hedging
Volatility Spreads
Option Arb
Correlation
Dividend
Borrowing Tool
• Jelly Rolls: • A synthetic long position in one expiry • A synthetic short position in another expiry
• Long jelly roll = • Synthetically long the near expiry options • Synthetically short the far dated expiry
options
• What would be the price of a 90/100 Jun/Sep jelly roll? • Value of roll = cost of holding underlying for
the 3 month period from Jun to Sep.
Rajib Ranjan Borah & Nitesh Khandelwal
QuantInsti
Bangkok 06 Oct 2014
Managing Option Portfolios
Options Trading Techniques:
A Trader’s Approach for a Retail Investor
2
• 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)
Risk Evaluations
3
• 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)
Risk Evaluations
4
Price of Call Option vs Price of Underlying
4
Options price is dependent on price of underlying
5
• The Hedge Ratio
• Equivalent Underlying Position
• Rate of change of price of option to change in underlying
• Probability of option finishing in the money
5
Delta
6
• i.e. Delta is dependent on • underlying price,
• time to expiry
• volatility
6
Delta
7
Delta vs Underlying price/Moneyness
7
Delta vs Underlying Price
8
Call Delta vs Time left to expiry
8
Delta vs Time
9
Put Delta vs Time left to expiry
9
Delta vs Time
10
Combined Visualization
10
Delta vs Underlying Price & Time
11
Call Delta vs Volatility
11
Delta vs Volatility
12
Put Delta vs Volatility
12
Delta vs Volatility
13
• As we have seen, deltas change with underlying price (more so towards expiry)
• Gamma is the second derivative of the change of option price with respect to change in underlying price
• = ∂2C/∂S2 = ∂Δ/∂S = N’(h)/ (Sσ√t)
13
Gamma
14
Gamma vs Price of Underlying
14
Gamma vs Price of Underlying
15
Gamma vs Time
15
Gamma vs Time / Volatility
16
Overall impact
16
Gamma vs Underlying Price & Time / Volatility
17
Gamma vs Volatility
17
Gamma vs Time / Volatility
18
• Delta is a poor estimate because unit change in underlying varies from underlying to underlying
• Lambda gets change in option price to a percentage change in the underlying
18
Lambda / Gearing
19
• Rate of change of price with respect to strike • Strike 100, price = 10
• Strike 120, price = 12
• Dual delta = (12-10)/(120-100) = 2/20 = 0.1
• Relationship between delta & Dual Delta • Delta = 1/ Stock Price * (Option Price –
Strike * DualDelta)
19
Dual Delta
20
• Change in Gamma with respect to change in underlying
• Also known as gamma of the gamma
20
Speed
21
• Change in Gamma with respect to change in time
• As seen previously: color is highest near the date of expiry and for ATM strikes
21
Color / Gamma decay
22
• Change of option price with respect to change in volatility
• = ∂C/∂σ
• = S √t N’(h)
• = ∂P/∂σ
22
Vega
23
Option price at different volatility levels
23
Option Price vs Volatility
24
Vega at different strikes
24
Vega vs Underlying Price
25
Vega of an option with varying time left to expiry
25
Vega vs Time
26
Sensitivity to volatility is sensitive to volatility itself
26
Vega vs Volatility
27
27
Vega vs Underlying Price & Time/Volatility
28
• Long call or long put = Long vega
= Long gamma as well
• Long vega & long gamma require volatility to profit
• Vega = S√t N’(h)
= S√t N’(h) . √tσSN’(h) / (√tσSN’(h))
= S√t N’(h) . √tσS/N’(h) .(N’(h) / (√tσS))
= S√t N’(h) . √tσS/N’(h) .(Gamma)
= S2tσGamma
28
Vega & Gamma
29
• Different expirations will react differently to changes in perception of future volatility • Long term volatility expectation is fairly
stable but short term is not
• Vegas for different months need to be weighted differently to get net vega across expiries
• Modified Vega =
• How to calculate Weightages ?
29
Calibrating different Vegas
n
i
ii WeightageVega1
.
30
• How to calculate Weightages ?
• Empirical (based on observed historical volatility for different time periods)
– Theoretical/ square root weightages. Weightages proportionate to
–But is being weighted neutral enough?
– Forward volatilities
30
Calibrating different Vegas