SlideShare a Scribd company logo
1 of 37
Option PricingOption Pricing
..
Stochastic ProcessStochastic Process
A variable whose value changes overA variable whose value changes over
time in an uncertain way is said totime in an uncertain way is said to
follow a stochastic process.follow a stochastic process.
Stochastic processes can be “discreteStochastic processes can be “discrete
time” or “continuous time” and alsotime” or “continuous time” and also
“discrete variable” or “continuous“discrete variable” or “continuous
variable”variable”
Markov ProcessMarkov Process
It is a particular type of stochastic processIt is a particular type of stochastic process
where only the present value of a variable iswhere only the present value of a variable is
relevant for predicting the future. The pastrelevant for predicting the future. The past
history of the variable and the way in which thehistory of the variable and the way in which the
present value has emerged from the past arepresent value has emerged from the past are
irrelevant.irrelevant.
It is consistence with the weak form of marketIt is consistence with the weak form of market
efficiency and means that while statisticalefficiency and means that while statistical
properties of the stock prices may be useful inproperties of the stock prices may be useful in
determining the characteristics of the stochasticdetermining the characteristics of the stochastic
process followed by the stock price but theprocess followed by the stock price but the
particular path followed in the past is irrelevant.particular path followed in the past is irrelevant.
Wiener ProcessWiener Process
It is a particular type of Markov StochasticIt is a particular type of Markov Stochastic
Process and has been used in physics toProcess and has been used in physics to
describe the motion of a particular subjected todescribe the motion of a particular subjected to
a large number of small molecular shocks and isa large number of small molecular shocks and is
sometimes referred to as Brownian Motion. Itsometimes referred to as Brownian Motion. It
has two properties;has two properties;
1.1. Small change is equal to root of change inSmall change is equal to root of change in
time multiplied by a random variable following atime multiplied by a random variable following a
standardized normal distribution.standardized normal distribution.
2.2. For two different short intervals, the smallFor two different short intervals, the small
changes are independent.changes are independent.
Lognormal DistributionLognormal Distribution
It is the variable whose logarithmIt is the variable whose logarithm
values are normally distributed. Wevalues are normally distributed. We
need to convert lognormalneed to convert lognormal
distributions (stochastic stock pricedistributions (stochastic stock price
changes) to normal distributions sochanges) to normal distributions so
that one could undertake analysisthat one could undertake analysis
using confidence limits, hypothesisusing confidence limits, hypothesis
testing etc.testing etc.
Option Pricing ModelsOption Pricing Models
DCF criterion cannot be used since risk ofDCF criterion cannot be used since risk of
anan
option is virtually indeterminate and henceoption is virtually indeterminate and hence
the discount rate is impossible to bethe discount rate is impossible to be
estimated. The two popular models are:estimated. The two popular models are:
 The Binomial ModelThe Binomial Model
 Black – Scholes ModelBlack – Scholes Model
The Binomial ModelThe Binomial Model
The model assumes,The model assumes,
 The price of asset can only go up orThe price of asset can only go up or
go down in fixed amounts ingo down in fixed amounts in
discrete time.discrete time.
 There is no arbitrage between theThere is no arbitrage between the
option and the replicating portfoliooption and the replicating portfolio
composed of underlying asset andcomposed of underlying asset and
risk-less asset.risk-less asset.
The Binomial ModelThe Binomial Model
 Current stock price = SCurrent stock price = S
 Next Year values = uS or dSNext Year values = uS or dS
 B amount can be borrowed at ‘r’.B amount can be borrowed at ‘r’.
Interest factor is (1+r) = RInterest factor is (1+r) = R
 d < R < u (no risk free arbitraged < R < u (no risk free arbitrage
possible)possible)
 E is the exercise priceE is the exercise price
The Binomial ModelThe Binomial Model
Depending on the change in stockDepending on the change in stock
value, option value will bevalue, option value will be
Cu = Max (uS – E, 0)Cu = Max (uS – E, 0)
Cd = Max (dS – E, 0)Cd = Max (dS – E, 0)
The Binomial ModelThe Binomial Model
..
S
Su
Sd
Su2
Sud
Sd2
The Binomial ModelThe Binomial Model
We now set a portfolio of ∆ shares and B amountWe now set a portfolio of ∆ shares and B amount
ofof
debt such that its payoff is equal to that of calldebt such that its payoff is equal to that of call
option after 1 year. Then,option after 1 year. Then,
Cu = ∆uS + RB……………Cu = ∆uS + RB…………… (1)(1)
Cd = ∆dS + RB…………….Cd = ∆dS + RB……………. (2)(2)
Solving these equations,Solving these equations,
(Cu – Cd)(Cu – Cd)
∆∆ == ; and; and
S(u-d)S(u-d)
(uCd – dCu)(uCd – dCu)
B =B =
(u – d)R(u – d)R
Hence C = ∆S + B, since portfolio has same payoff asHence C = ∆S + B, since portfolio has same payoff as
IllustrationIllustration
A stock is currently selling for Rs.40.A stock is currently selling for Rs.40.
The call option on the stockThe call option on the stock
exercisable a year from now at aexercisable a year from now at a
strikestrike
price of Rs.45 is currently selling atprice of Rs.45 is currently selling at
Rs.8. The risk-free rate is 10%. TheRs.8. The risk-free rate is 10%. The
stock can either rise or fall after astock can either rise or fall after a
year.year.
It can fall by 20%. By whatIt can fall by 20%. By what
percentagepercentage
Black-Scholes Model as the LimitBlack-Scholes Model as the Limit
of the Binomial Modelof the Binomial Model
The Binomial Model converges to the Black-The Binomial Model converges to the Black-
Scholes model as the number of timeScholes model as the number of time
periods increases.periods increases.
Black-Scholes Model: The originBlack-Scholes Model: The origin
 1820s – Scottish scientist Robert Brown1820s – Scottish scientist Robert Brown
observed motion of suspended particles inobserved motion of suspended particles in
water.water.
 Early 19Early 19thth
century – Albert Einstein usedcentury – Albert Einstein used
Brownian motion to explain movements ofBrownian motion to explain movements of
molecules, many research papers.molecules, many research papers.
 1900 – French scholar, Louis Bachelier wrote1900 – French scholar, Louis Bachelier wrote
dissertation on option pricing and developed adissertation on option pricing and developed a
model strikingly similar to BSM.model strikingly similar to BSM.
 1951 – Japanese mathematician Kiyoshi Ito1951 – Japanese mathematician Kiyoshi Ito
developed Ito’s Lemma that was used in optiondeveloped Ito’s Lemma that was used in option
pricing.pricing.
Black-Scholes Model: The originBlack-Scholes Model: The origin
 Fischer Black and Myron Scholes worked inFischer Black and Myron Scholes worked in
Finance Faculty at MIT Published paper in 1973.Finance Faculty at MIT Published paper in 1973.
They were later joined by Robert Merton.They were later joined by Robert Merton.
 Fischer left academia in 1983, died in 1995 atFischer left academia in 1983, died in 1995 at
57.57.
 1997 – Scholes and Merton got Nobel Prize1997 – Scholes and Merton got Nobel Prize
Black-Scholes ModelBlack-Scholes Model
Fischer Black and Myron Scholes, The Journal of Political Economy, 1973Fischer Black and Myron Scholes, The Journal of Political Economy, 1973
Assumptions:Assumptions:
 The underlying stock pays no dividends.The underlying stock pays no dividends.
 It is a European option.It is a European option.
 The stock price is continuous and is distributedThe stock price is continuous and is distributed
lognormally.lognormally.
 There are no transaction costs and taxes.There are no transaction costs and taxes.
 No restrictions or penalty on short sellingNo restrictions or penalty on short selling
 The risk free rate is known and is constant overThe risk free rate is known and is constant over
the life of the option.the life of the option.
Black-Scholes ModelBlack-Scholes Model
CC00 = S= S00 N (dN (d11 ) – E/e) – E/ertrt
N (dN (d22 ) where,) where,
CC00 = Present equilibrium value of call option= Present equilibrium value of call option
SS00 = Current stock price= Current stock price
EE = Exercise price= Exercise price
ee = Base of natural logarithm= Base of natural logarithm
rr = Continuously compounded risk free interest rate= Continuously compounded risk free interest rate
tt = length of time in years to expiration= length of time in years to expiration
N (*)N (*) = Cumulative probability distribution function of a= Cumulative probability distribution function of a
standardized normal distributionstandardized normal distribution
Black-Scholes ModelBlack-Scholes Model
C = S N (dC = S N (d11 ) – K) – Kee-rt-rt
N (dN (d22 ) where,) where,
CC = Present equilibrium value of call option= Present equilibrium value of call option
SS = Current stock price= Current stock price
KK = Exercise price= Exercise price
ee = Base of natural logarithm= Base of natural logarithm
rr = Continuously compounded risk free interest rate= Continuously compounded risk free interest rate
tt = length of time in years to expiration= length of time in years to expiration
N (*)N (*) = Cumulative probability distribution function of a= Cumulative probability distribution function of a
standardized normal distributionstandardized normal distribution
Black-Scholes ModelBlack-Scholes Model
llnn (S(S00 /E) + (r + ½/E) + (r + ½ σσ22
)t)t
dd11 ==
σσ √t√t
llnn (S(S00 /E) + (r - ½/E) + (r - ½ σσ22
)t)t
dd22 ==
σσ √t√t
where lwhere lnn is the natural logarithmis the natural logarithm
Black-Scholes ModelBlack-Scholes Model
llnn (S/K(S/K ee-rt-rt
))
dd11 == + 0.5+ 0.5 σσ √t√t
σσ √t√t
dd22 == dd11 -- σσ √t√t
where lwhere lnn is the natural logarithmis the natural logarithm
IllustrationIllustration
The standard deviation of the continuouslyThe standard deviation of the continuously
compounded stock price change for acompounded stock price change for a
company is estimated to be 20% per year.company is estimated to be 20% per year.
The stock currently sells for Rs.80 and theThe stock currently sells for Rs.80 and the
effective annual interest rate is Rs.15.03%.effective annual interest rate is Rs.15.03%.
What is the value of a one year call optionWhat is the value of a one year call option
on the stock of the company if the exerciseon the stock of the company if the exercise
price is Rs.82?price is Rs.82?
The Linkage between Calls, Puts,The Linkage between Calls, Puts,
Stock, and Risk-Free BondsStock, and Risk-Free Bonds
..
Call
Stock
Put
Risk-Free
Bond
Black-Scholes
Call Option
Pricing Model
Put-Call
Parity
Black-Scholes
Put Option
Pricing Model
Put-Call Parity TheoremPut-Call Parity Theorem
Payoffs just beforePayoffs just before
expirationexpiration
If SIf S11 < E< E If SIf S11 > E> E
1.1. Buy the equity stockBuy the equity stock SS11 SS11
2.2. Buy a put optionBuy a put option E-SE-S11 00
3.3. Borrow amount equalBorrow amount equal
to exercise priceto exercise price - E- E - E- E
1+2+3=Buy a call option1+2+3=Buy a call option 00 SS11 - E- E
Using Black-Scholes ModelUsing Black-Scholes Model
1.1. Find the Standard Deviation of theFind the Standard Deviation of the
continuously compounded asset value changecontinuously compounded asset value change
and the square root of the time left toand the square root of the time left to
expirationexpiration
2.2. Calculate ratio of the current asset value toCalculate ratio of the current asset value to
the present value of the exercise pricethe present value of the exercise price
3.3. Consult the table giving %age relationshipConsult the table giving %age relationship
between the value of the Call Option and thebetween the value of the Call Option and the
stock price corresponding to the value instock price corresponding to the value in
steps 1 and 2steps 1 and 2
4.4. Value of Put Option = Value of Call Option +Value of Put Option = Value of Call Option +
PV of exercise price – Stock PricePV of exercise price – Stock Price
IllustrationIllustration
Find the value of a one year call option asFind the value of a one year call option as
well as a put option, if the current stockwell as a put option, if the current stock
price is Rs.120, exercise price is Rs.125 andprice is Rs.120, exercise price is Rs.125 and
the S.D. of continuously compounded pricethe S.D. of continuously compounded price
change of the stock is 30%. The effectivechange of the stock is 30%. The effective
interest rate is 15.03% so that the interestinterest rate is 15.03% so that the interest
factor is 1.1503.factor is 1.1503.
IllustrationIllustration
Step 1: Standard Deviation × √Time = 0.30 × √1Step 1: Standard Deviation × √Time = 0.30 × √1
= 0.30= 0.30
Step 2: The ratio of stock price to the PV ofStep 2: The ratio of stock price to the PV of
exercise price = 120 ÷ 125/1.1503exercise price = 120 ÷ 125/1.1503
= 120/108.7 = 1.10= 120/108.7 = 1.10
Step 3: Consulting the table we get 16.5% of theStep 3: Consulting the table we get 16.5% of the
stock price as the value of call option i.e.stock price as the value of call option i.e.
120×0.165 = 19.8120×0.165 = 19.8
Step 4: Value of Put OptionStep 4: Value of Put Option
= 19.8 + 108.7 – 120 = 8.5= 19.8 + 108.7 – 120 = 8.5
Variants of Black-Scholes ModelVariants of Black-Scholes Model
 To price European options on dividendTo price European options on dividend
paying options and American options onpaying options and American options on
non-dividend paying stocks (Robertnon-dividend paying stocks (Robert
Merton, 1973 and Clifford Smith, 1976).Merton, 1973 and Clifford Smith, 1976).
 American call options on dividend-payingAmerican call options on dividend-paying
stocks (Richard Roll, 1977; Robertstocks (Richard Roll, 1977; Robert
Whaley, 1981; and Richard Geske andWhaley, 1981; and Richard Geske and
Richard Roll, 1984)Richard Roll, 1984)
Variants of Black-Scholes ModelVariants of Black-Scholes Model
 When price changes are discontinuousWhen price changes are discontinuous
(Cox, Rubinstein and Ross, 1979). This(Cox, Rubinstein and Ross, 1979). This
was published in Journal of Financialwas published in Journal of Financial
Economics as “Option Pricing: AEconomics as “Option Pricing: A
Simplified Approach”. This is the BinomialSimplified Approach”. This is the Binomial
Model for Option Pricing.Model for Option Pricing.
Garman - Kohlhagen ModelGarman - Kohlhagen Model
The foreign currency option pricing modelThe foreign currency option pricing model
is equivalent to the Black-Scholes modeis equivalent to the Black-Scholes mode
except that the spot rate is discounted byexcept that the spot rate is discounted by
the foreign interest rate and appearsthe foreign interest rate and appears
instead of the Stock Price.instead of the Stock Price.
Sensitivity of Option PremiumsSensitivity of Option Premiums
 An option’s intrinsic value is the amount byAn option’s intrinsic value is the amount by
which it is in the money and the time valuewhich it is in the money and the time value
is the difference between actual premiumis the difference between actual premium
and the intrinsic value i.e. premium =and the intrinsic value i.e. premium =
intrinsic value + time value.intrinsic value + time value.
 At the money option has highest likelihoodAt the money option has highest likelihood
of gaining intrinsic value as compared toof gaining intrinsic value as compared to
that of losing. It has no value to lose butthat of losing. It has no value to lose but
50-50 chance of gaining.50-50 chance of gaining.
Sensitivity of Option PremiumsSensitivity of Option Premiums
Delta (Delta (δδ):): Change in option price relativeChange in option price relative
to the price of underlying asset. Reverseto the price of underlying asset. Reverse
of Delta is used to calculate a hedge ratio.of Delta is used to calculate a hedge ratio.
Gamma:Gamma: The rate of change of Delta. It isThe rate of change of Delta. It is
the second derivative of option price withthe second derivative of option price with
respect to price of the asset and is alsorespect to price of the asset and is also
known as option’s curvature. High gammaknown as option’s curvature. High gamma
makes option less attractive.makes option less attractive.
Sensitivity of Option PremiumsSensitivity of Option Premiums
Lambda:Lambda: Change in option price relative toChange in option price relative to
change in volatility. Its value lies betweenchange in volatility. Its value lies between
zero and infinity and declines as optionzero and infinity and declines as option
approaches maturityapproaches maturity
Theta:Theta: Change in option price relative toChange in option price relative to
Time to Expiration. The value of theta liesTime to Expiration. The value of theta lies
between zero and total value of option.between zero and total value of option.
Rho:Rho: Change in option value in relation toChange in option value in relation to
interest rates and varies from type to typeinterest rates and varies from type to type
of the options.of the options.
Sensitivity of Option PremiumsSensitivity of Option Premiums
Implied volatility is obtained by finding theImplied volatility is obtained by finding the
S.D. that when used in the Black-ScholesS.D. that when used in the Black-Scholes
model makes the model price equal tomodel makes the model price equal to
market price of the option.market price of the option.
The pattern of implied volatility acrossThe pattern of implied volatility across
expirations is often called the termexpirations is often called the term
structure of volatility, and the pattern ofstructure of volatility, and the pattern of
volatility across exercise prices is oftenvolatility across exercise prices is often
called the volatility smile or skew.called the volatility smile or skew.
IllustrationIllustration
If on February 1, one wants to price a MarchIf on February 1, one wants to price a March
European call option of a company,European call option of a company,
WhereWhere SS == Rs.92.00Rs.92.00
KK == Rs.95.00Rs.95.00
tt == 50 days,50 days, or (50/365=0.137 years)or (50/365=0.137 years)
rr == 7.12%7.12%
σσ == 35%35%
and the company does not pay anyand the company does not pay any
dividendsdividends
Return RelativesReturn Relatives
 If P(0) is the beginning wealth andIf P(0) is the beginning wealth and
P(T), the ending wealth, the priceP(T), the ending wealth, the price
relative R(0,T) is given by P(T)/P(0).relative R(0,T) is given by P(T)/P(0).
Since P(T) is a random variable,Since P(T) is a random variable,
P(T)/P(0) is also a random variable.P(T)/P(0) is also a random variable.
 Holding period return is the effectiveHolding period return is the effective
return r(T) is related to R(0,T).return r(T) is related to R(0,T).
 Continuous holding period return rContinuous holding period return r cc (T)(T)
is related to price relative by:is related to price relative by: rrcc (T) =(T) =
ln(R(0,T)).ln(R(0,T)).
 Thus all these are random variables.Thus all these are random variables.

More Related Content

What's hot (20)

Random walk theory
Random walk theoryRandom walk theory
Random walk theory
 
Binomial Option pricing
Binomial Option pricingBinomial Option pricing
Binomial Option pricing
 
Bond Valuation
Bond ValuationBond Valuation
Bond Valuation
 
The Greeks
The GreeksThe Greeks
The Greeks
 
Call option
Call optionCall option
Call option
 
8 a spot-forward markets
8 a spot-forward markets8 a spot-forward markets
8 a spot-forward markets
 
Options, caps, floors
Options, caps, floorsOptions, caps, floors
Options, caps, floors
 
Derivatives - Basics of Derivatives contract covered in this ppt
Derivatives - Basics of Derivatives contract covered in this pptDerivatives - Basics of Derivatives contract covered in this ppt
Derivatives - Basics of Derivatives contract covered in this ppt
 
Option ( Derivatives)
Option ( Derivatives)Option ( Derivatives)
Option ( Derivatives)
 
Fundamentals of Option Contracts
Fundamentals of Option ContractsFundamentals of Option Contracts
Fundamentals of Option Contracts
 
Pricing forward & future contracts
Pricing forward & future contractsPricing forward & future contracts
Pricing forward & future contracts
 
Financial derivatives ppt
Financial derivatives pptFinancial derivatives ppt
Financial derivatives ppt
 
Options
OptionsOptions
Options
 
Swaps (derivatives)
Swaps (derivatives)Swaps (derivatives)
Swaps (derivatives)
 
Futures And Forwards
Futures And ForwardsFutures And Forwards
Futures And Forwards
 
Forward contracts (1)
Forward contracts (1)Forward contracts (1)
Forward contracts (1)
 
forward and future contract
forward and future contractforward and future contract
forward and future contract
 
option greeks
option greeksoption greeks
option greeks
 
Derivative ppt
Derivative pptDerivative ppt
Derivative ppt
 
Swaps
SwapsSwaps
Swaps
 

Viewers also liked

Derivatives Binomial Option Pricing Model Examples
Derivatives  Binomial  Option  Pricing  Model  ExamplesDerivatives  Binomial  Option  Pricing  Model  Examples
Derivatives Binomial Option Pricing Model Examplesuichong
 
Unit principles of option pricing put
Unit  principles of option pricing putUnit  principles of option pricing put
Unit principles of option pricing putSudarshan Kadariya
 
Black Scholes for Techies
Black Scholes for TechiesBlack Scholes for Techies
Black Scholes for TechiesAraik Grigoryan
 
Black-Scholes Calculator on Web
Black-Scholes Calculator on WebBlack-Scholes Calculator on Web
Black-Scholes Calculator on WebEugene Yang
 
F B E559f3 B S Formula
F B E559f3 B S  FormulaF B E559f3 B S  Formula
F B E559f3 B S Formulauichong
 
Introduction to derivatives
Introduction to derivativesIntroduction to derivatives
Introduction to derivativesKiran Shinde
 
Binomial Tree - Option Pricing Theory
Binomial Tree - Option Pricing TheoryBinomial Tree - Option Pricing Theory
Binomial Tree - Option Pricing TheoryJames Dazé
 
Unit principles of option pricing call
Unit  principles of option pricing callUnit  principles of option pricing call
Unit principles of option pricing callSudarshan Kadariya
 
Derivatives basics
Derivatives basicsDerivatives basics
Derivatives basicsAjay Mishra
 
Introduction to derivatives
Introduction to derivativesIntroduction to derivatives
Introduction to derivativesNeelam Asad
 
Derivatives basic concept
Derivatives basic conceptDerivatives basic concept
Derivatives basic conceptSweta Agarwal
 
Derivatives market
Derivatives marketDerivatives market
Derivatives marketNikhiliit
 
Financial derivatives ppt
Financial derivatives pptFinancial derivatives ppt
Financial derivatives pptVaishnaviSavant
 

Viewers also liked (16)

Derivatives Binomial Option Pricing Model Examples
Derivatives  Binomial  Option  Pricing  Model  ExamplesDerivatives  Binomial  Option  Pricing  Model  Examples
Derivatives Binomial Option Pricing Model Examples
 
Unit principles of option pricing put
Unit  principles of option pricing putUnit  principles of option pricing put
Unit principles of option pricing put
 
Black Scholes for Techies
Black Scholes for TechiesBlack Scholes for Techies
Black Scholes for Techies
 
Black-Scholes Calculator on Web
Black-Scholes Calculator on WebBlack-Scholes Calculator on Web
Black-Scholes Calculator on Web
 
F B E559f3 B S Formula
F B E559f3 B S  FormulaF B E559f3 B S  Formula
F B E559f3 B S Formula
 
Introduction to derivatives
Introduction to derivativesIntroduction to derivatives
Introduction to derivatives
 
Binomial Tree - Option Pricing Theory
Binomial Tree - Option Pricing TheoryBinomial Tree - Option Pricing Theory
Binomial Tree - Option Pricing Theory
 
Unit principles of option pricing call
Unit  principles of option pricing callUnit  principles of option pricing call
Unit principles of option pricing call
 
Derivatives in India
Derivatives in IndiaDerivatives in India
Derivatives in India
 
Derivative in india final
Derivative in india finalDerivative in india final
Derivative in india final
 
Derivatives basics
Derivatives basicsDerivatives basics
Derivatives basics
 
Introduction to derivatives
Introduction to derivativesIntroduction to derivatives
Introduction to derivatives
 
Derivatives - Classroom Presentation
Derivatives - Classroom PresentationDerivatives - Classroom Presentation
Derivatives - Classroom Presentation
 
Derivatives basic concept
Derivatives basic conceptDerivatives basic concept
Derivatives basic concept
 
Derivatives market
Derivatives marketDerivatives market
Derivatives market
 
Financial derivatives ppt
Financial derivatives pptFinancial derivatives ppt
Financial derivatives ppt
 

Similar to 11. option pricing

Financial Markets with Stochastic Volatilities - markov modelling
Financial Markets with Stochastic Volatilities - markov modellingFinancial Markets with Stochastic Volatilities - markov modelling
Financial Markets with Stochastic Volatilities - markov modellingguest8901f4
 
Value of options presentation
Value of options presentationValue of options presentation
Value of options presentationTrevor Ruwa
 
Copula-Based Model for the Term Structure of CDO Tranches
Copula-Based Model for the Term Structure of CDO TranchesCopula-Based Model for the Term Structure of CDO Tranches
Copula-Based Model for the Term Structure of CDO Tranchesfinancedude
 
Volatility Smiles and Stylised Facts in the Heston Model
Volatility Smiles and Stylised Facts in the Heston ModelVolatility Smiles and Stylised Facts in the Heston Model
Volatility Smiles and Stylised Facts in the Heston ModelKamrul Hasan
 
Option pricing under quantum theory of securities price formation - with copy...
Option pricing under quantum theory of securities price formation - with copy...Option pricing under quantum theory of securities price formation - with copy...
Option pricing under quantum theory of securities price formation - with copy...Jack Sarkissian
 
Financial engineering3478
Financial engineering3478Financial engineering3478
Financial engineering3478artipradhan
 
Normality_assumption_for_the_log_re.pdf
Normality_assumption_for_the_log_re.pdfNormality_assumption_for_the_log_re.pdf
Normality_assumption_for_the_log_re.pdfVasudha Singh
 
A Comparison of Option Pricing ModelsEkrem Kilic 11.0.docx
A Comparison of Option Pricing ModelsEkrem Kilic 11.0.docxA Comparison of Option Pricing ModelsEkrem Kilic 11.0.docx
A Comparison of Option Pricing ModelsEkrem Kilic 11.0.docxevonnehoggarth79783
 
Uncertain volatillity Models
Uncertain volatillity ModelsUncertain volatillity Models
Uncertain volatillity ModelsLuigi Piva CQF
 
Black scholes pricing consept
Black scholes pricing conseptBlack scholes pricing consept
Black scholes pricing conseptIlya Gikhman
 
option valuation
option valuation option valuation
option valuation latif812
 

Similar to 11. option pricing (20)

Financial Markets with Stochastic Volatilities - markov modelling
Financial Markets with Stochastic Volatilities - markov modellingFinancial Markets with Stochastic Volatilities - markov modelling
Financial Markets with Stochastic Volatilities - markov modelling
 
Value of options presentation
Value of options presentationValue of options presentation
Value of options presentation
 
Copula-Based Model for the Term Structure of CDO Tranches
Copula-Based Model for the Term Structure of CDO TranchesCopula-Based Model for the Term Structure of CDO Tranches
Copula-Based Model for the Term Structure of CDO Tranches
 
Volatility Smiles and Stylised Facts in the Heston Model
Volatility Smiles and Stylised Facts in the Heston ModelVolatility Smiles and Stylised Facts in the Heston Model
Volatility Smiles and Stylised Facts in the Heston Model
 
P1
P1P1
P1
 
presentation
presentationpresentation
presentation
 
BSE.pptx
BSE.pptxBSE.pptx
BSE.pptx
 
Report
ReportReport
Report
 
Levy models
Levy modelsLevy models
Levy models
 
Option pricing under quantum theory of securities price formation - with copy...
Option pricing under quantum theory of securities price formation - with copy...Option pricing under quantum theory of securities price formation - with copy...
Option pricing under quantum theory of securities price formation - with copy...
 
Financial engineering3478
Financial engineering3478Financial engineering3478
Financial engineering3478
 
Normality_assumption_for_the_log_re.pdf
Normality_assumption_for_the_log_re.pdfNormality_assumption_for_the_log_re.pdf
Normality_assumption_for_the_log_re.pdf
 
Aman &Anas Cost ppt.pptx
Aman &Anas Cost ppt.pptxAman &Anas Cost ppt.pptx
Aman &Anas Cost ppt.pptx
 
Black scholes(Venu)
Black scholes(Venu)Black scholes(Venu)
Black scholes(Venu)
 
Vidyasagar rocond09
Vidyasagar rocond09Vidyasagar rocond09
Vidyasagar rocond09
 
A Comparison of Option Pricing ModelsEkrem Kilic 11.0.docx
A Comparison of Option Pricing ModelsEkrem Kilic 11.0.docxA Comparison of Option Pricing ModelsEkrem Kilic 11.0.docx
A Comparison of Option Pricing ModelsEkrem Kilic 11.0.docx
 
Uncertain volatillity Models
Uncertain volatillity ModelsUncertain volatillity Models
Uncertain volatillity Models
 
Black Scholes
Black ScholesBlack Scholes
Black Scholes
 
Black scholes pricing consept
Black scholes pricing conseptBlack scholes pricing consept
Black scholes pricing consept
 
option valuation
option valuation option valuation
option valuation
 

Recently uploaded

Using AI to boost productivity for developers
Using AI to boost productivity for developersUsing AI to boost productivity for developers
Using AI to boost productivity for developersTeri Eyenike
 
Digital collaboration with Microsoft 365 as extension of Drupal
Digital collaboration with Microsoft 365 as extension of DrupalDigital collaboration with Microsoft 365 as extension of Drupal
Digital collaboration with Microsoft 365 as extension of DrupalFabian de Rijk
 
"I hear you": Moving beyond empathy in UXR
"I hear you": Moving beyond empathy in UXR"I hear you": Moving beyond empathy in UXR
"I hear you": Moving beyond empathy in UXRMegan Campos
 
SOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdf
SOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdfSOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdf
SOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdfMahamudul Hasan
 
Introduction to Artificial intelligence.
Introduction to Artificial intelligence.Introduction to Artificial intelligence.
Introduction to Artificial intelligence.thamaeteboho94
 
BIG DEVELOPMENTS IN LESOTHO(DAMS & MINES
BIG DEVELOPMENTS IN LESOTHO(DAMS & MINESBIG DEVELOPMENTS IN LESOTHO(DAMS & MINES
BIG DEVELOPMENTS IN LESOTHO(DAMS & MINESfuthumetsaneliswa
 
2024 mega trends for the digital workplace - FINAL.pdf
2024 mega trends for the digital workplace - FINAL.pdf2024 mega trends for the digital workplace - FINAL.pdf
2024 mega trends for the digital workplace - FINAL.pdfNancy Goebel
 
Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...
Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...
Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...ZurliaSoop
 
ECOLOGY OF FISHES.pptx full presentation
ECOLOGY OF FISHES.pptx full presentationECOLOGY OF FISHES.pptx full presentation
ECOLOGY OF FISHES.pptx full presentationFahadFazal7
 
Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...
Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...
Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...David Celestin
 
Unlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven Curiosity
Unlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven CuriosityUnlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven Curiosity
Unlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven CuriosityHung Le
 
History of Morena Moshoeshoe birth death
History of Morena Moshoeshoe birth deathHistory of Morena Moshoeshoe birth death
History of Morena Moshoeshoe birth deathphntsoaki
 
LITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORN
LITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORNLITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORN
LITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORNtntlai16
 
Ready Set Go Children Sermon about Mark 16:15-20
Ready Set Go Children Sermon about Mark 16:15-20Ready Set Go Children Sermon about Mark 16:15-20
Ready Set Go Children Sermon about Mark 16:15-20rejz122017
 
The Concession of Asaba International Airport: Balancing Politics and Policy ...
The Concession of Asaba International Airport: Balancing Politics and Policy ...The Concession of Asaba International Airport: Balancing Politics and Policy ...
The Concession of Asaba International Airport: Balancing Politics and Policy ...Kayode Fayemi
 
BEAUTIFUL PLACES TO VISIT IN LESOTHO.pptx
BEAUTIFUL PLACES TO VISIT IN LESOTHO.pptxBEAUTIFUL PLACES TO VISIT IN LESOTHO.pptx
BEAUTIFUL PLACES TO VISIT IN LESOTHO.pptxthusosetemere
 

Recently uploaded (19)

Using AI to boost productivity for developers
Using AI to boost productivity for developersUsing AI to boost productivity for developers
Using AI to boost productivity for developers
 
Digital collaboration with Microsoft 365 as extension of Drupal
Digital collaboration with Microsoft 365 as extension of DrupalDigital collaboration with Microsoft 365 as extension of Drupal
Digital collaboration with Microsoft 365 as extension of Drupal
 
"I hear you": Moving beyond empathy in UXR
"I hear you": Moving beyond empathy in UXR"I hear you": Moving beyond empathy in UXR
"I hear you": Moving beyond empathy in UXR
 
SOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdf
SOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdfSOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdf
SOLID WASTE MANAGEMENT SYSTEM OF FENI PAURASHAVA, BANGLADESH.pdf
 
Introduction to Artificial intelligence.
Introduction to Artificial intelligence.Introduction to Artificial intelligence.
Introduction to Artificial intelligence.
 
BIG DEVELOPMENTS IN LESOTHO(DAMS & MINES
BIG DEVELOPMENTS IN LESOTHO(DAMS & MINESBIG DEVELOPMENTS IN LESOTHO(DAMS & MINES
BIG DEVELOPMENTS IN LESOTHO(DAMS & MINES
 
2024 mega trends for the digital workplace - FINAL.pdf
2024 mega trends for the digital workplace - FINAL.pdf2024 mega trends for the digital workplace - FINAL.pdf
2024 mega trends for the digital workplace - FINAL.pdf
 
in kuwait௹+918133066128....) @abortion pills for sale in Kuwait City
in kuwait௹+918133066128....) @abortion pills for sale in Kuwait Cityin kuwait௹+918133066128....) @abortion pills for sale in Kuwait City
in kuwait௹+918133066128....) @abortion pills for sale in Kuwait City
 
Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...
Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...
Jual obat aborsi Jakarta 085657271886 Cytote pil telat bulan penggugur kandun...
 
ECOLOGY OF FISHES.pptx full presentation
ECOLOGY OF FISHES.pptx full presentationECOLOGY OF FISHES.pptx full presentation
ECOLOGY OF FISHES.pptx full presentation
 
Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...
Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...
Proofreading- Basics to Artificial Intelligence Integration - Presentation:Sl...
 
Unlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven Curiosity
Unlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven CuriosityUnlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven Curiosity
Unlocking Exploration: Self-Motivated Agents Thrive on Memory-Driven Curiosity
 
History of Morena Moshoeshoe birth death
History of Morena Moshoeshoe birth deathHistory of Morena Moshoeshoe birth death
History of Morena Moshoeshoe birth death
 
Abortion Pills Fahaheel ௹+918133066128💬@ Safe and Effective Mifepristion and ...
Abortion Pills Fahaheel ௹+918133066128💬@ Safe and Effective Mifepristion and ...Abortion Pills Fahaheel ௹+918133066128💬@ Safe and Effective Mifepristion and ...
Abortion Pills Fahaheel ௹+918133066128💬@ Safe and Effective Mifepristion and ...
 
LITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORN
LITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORNLITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORN
LITTLE ABOUT LESOTHO FROM THE TIME MOSHOESHOE THE FIRST WAS BORN
 
Ready Set Go Children Sermon about Mark 16:15-20
Ready Set Go Children Sermon about Mark 16:15-20Ready Set Go Children Sermon about Mark 16:15-20
Ready Set Go Children Sermon about Mark 16:15-20
 
The Concession of Asaba International Airport: Balancing Politics and Policy ...
The Concession of Asaba International Airport: Balancing Politics and Policy ...The Concession of Asaba International Airport: Balancing Politics and Policy ...
The Concession of Asaba International Airport: Balancing Politics and Policy ...
 
BEAUTIFUL PLACES TO VISIT IN LESOTHO.pptx
BEAUTIFUL PLACES TO VISIT IN LESOTHO.pptxBEAUTIFUL PLACES TO VISIT IN LESOTHO.pptx
BEAUTIFUL PLACES TO VISIT IN LESOTHO.pptx
 
ICT role in 21st century education and it's challenges.pdf
ICT role in 21st century education and it's challenges.pdfICT role in 21st century education and it's challenges.pdf
ICT role in 21st century education and it's challenges.pdf
 

11. option pricing

  • 2. Stochastic ProcessStochastic Process A variable whose value changes overA variable whose value changes over time in an uncertain way is said totime in an uncertain way is said to follow a stochastic process.follow a stochastic process. Stochastic processes can be “discreteStochastic processes can be “discrete time” or “continuous time” and alsotime” or “continuous time” and also “discrete variable” or “continuous“discrete variable” or “continuous variable”variable”
  • 3. Markov ProcessMarkov Process It is a particular type of stochastic processIt is a particular type of stochastic process where only the present value of a variable iswhere only the present value of a variable is relevant for predicting the future. The pastrelevant for predicting the future. The past history of the variable and the way in which thehistory of the variable and the way in which the present value has emerged from the past arepresent value has emerged from the past are irrelevant.irrelevant. It is consistence with the weak form of marketIt is consistence with the weak form of market efficiency and means that while statisticalefficiency and means that while statistical properties of the stock prices may be useful inproperties of the stock prices may be useful in determining the characteristics of the stochasticdetermining the characteristics of the stochastic process followed by the stock price but theprocess followed by the stock price but the particular path followed in the past is irrelevant.particular path followed in the past is irrelevant.
  • 4. Wiener ProcessWiener Process It is a particular type of Markov StochasticIt is a particular type of Markov Stochastic Process and has been used in physics toProcess and has been used in physics to describe the motion of a particular subjected todescribe the motion of a particular subjected to a large number of small molecular shocks and isa large number of small molecular shocks and is sometimes referred to as Brownian Motion. Itsometimes referred to as Brownian Motion. It has two properties;has two properties; 1.1. Small change is equal to root of change inSmall change is equal to root of change in time multiplied by a random variable following atime multiplied by a random variable following a standardized normal distribution.standardized normal distribution. 2.2. For two different short intervals, the smallFor two different short intervals, the small changes are independent.changes are independent.
  • 5. Lognormal DistributionLognormal Distribution It is the variable whose logarithmIt is the variable whose logarithm values are normally distributed. Wevalues are normally distributed. We need to convert lognormalneed to convert lognormal distributions (stochastic stock pricedistributions (stochastic stock price changes) to normal distributions sochanges) to normal distributions so that one could undertake analysisthat one could undertake analysis using confidence limits, hypothesisusing confidence limits, hypothesis testing etc.testing etc.
  • 6. Option Pricing ModelsOption Pricing Models DCF criterion cannot be used since risk ofDCF criterion cannot be used since risk of anan option is virtually indeterminate and henceoption is virtually indeterminate and hence the discount rate is impossible to bethe discount rate is impossible to be estimated. The two popular models are:estimated. The two popular models are:  The Binomial ModelThe Binomial Model  Black – Scholes ModelBlack – Scholes Model
  • 7. The Binomial ModelThe Binomial Model The model assumes,The model assumes,  The price of asset can only go up orThe price of asset can only go up or go down in fixed amounts ingo down in fixed amounts in discrete time.discrete time.  There is no arbitrage between theThere is no arbitrage between the option and the replicating portfoliooption and the replicating portfolio composed of underlying asset andcomposed of underlying asset and risk-less asset.risk-less asset.
  • 8. The Binomial ModelThe Binomial Model  Current stock price = SCurrent stock price = S  Next Year values = uS or dSNext Year values = uS or dS  B amount can be borrowed at ‘r’.B amount can be borrowed at ‘r’. Interest factor is (1+r) = RInterest factor is (1+r) = R  d < R < u (no risk free arbitraged < R < u (no risk free arbitrage possible)possible)  E is the exercise priceE is the exercise price
  • 9. The Binomial ModelThe Binomial Model Depending on the change in stockDepending on the change in stock value, option value will bevalue, option value will be Cu = Max (uS – E, 0)Cu = Max (uS – E, 0) Cd = Max (dS – E, 0)Cd = Max (dS – E, 0)
  • 10. The Binomial ModelThe Binomial Model .. S Su Sd Su2 Sud Sd2
  • 11. The Binomial ModelThe Binomial Model We now set a portfolio of ∆ shares and B amountWe now set a portfolio of ∆ shares and B amount ofof debt such that its payoff is equal to that of calldebt such that its payoff is equal to that of call option after 1 year. Then,option after 1 year. Then, Cu = ∆uS + RB……………Cu = ∆uS + RB…………… (1)(1) Cd = ∆dS + RB…………….Cd = ∆dS + RB……………. (2)(2) Solving these equations,Solving these equations, (Cu – Cd)(Cu – Cd) ∆∆ == ; and; and S(u-d)S(u-d) (uCd – dCu)(uCd – dCu) B =B = (u – d)R(u – d)R Hence C = ∆S + B, since portfolio has same payoff asHence C = ∆S + B, since portfolio has same payoff as
  • 12. IllustrationIllustration A stock is currently selling for Rs.40.A stock is currently selling for Rs.40. The call option on the stockThe call option on the stock exercisable a year from now at aexercisable a year from now at a strikestrike price of Rs.45 is currently selling atprice of Rs.45 is currently selling at Rs.8. The risk-free rate is 10%. TheRs.8. The risk-free rate is 10%. The stock can either rise or fall after astock can either rise or fall after a year.year. It can fall by 20%. By whatIt can fall by 20%. By what percentagepercentage
  • 13. Black-Scholes Model as the LimitBlack-Scholes Model as the Limit of the Binomial Modelof the Binomial Model The Binomial Model converges to the Black-The Binomial Model converges to the Black- Scholes model as the number of timeScholes model as the number of time periods increases.periods increases.
  • 14. Black-Scholes Model: The originBlack-Scholes Model: The origin  1820s – Scottish scientist Robert Brown1820s – Scottish scientist Robert Brown observed motion of suspended particles inobserved motion of suspended particles in water.water.  Early 19Early 19thth century – Albert Einstein usedcentury – Albert Einstein used Brownian motion to explain movements ofBrownian motion to explain movements of molecules, many research papers.molecules, many research papers.  1900 – French scholar, Louis Bachelier wrote1900 – French scholar, Louis Bachelier wrote dissertation on option pricing and developed adissertation on option pricing and developed a model strikingly similar to BSM.model strikingly similar to BSM.  1951 – Japanese mathematician Kiyoshi Ito1951 – Japanese mathematician Kiyoshi Ito developed Ito’s Lemma that was used in optiondeveloped Ito’s Lemma that was used in option pricing.pricing.
  • 15. Black-Scholes Model: The originBlack-Scholes Model: The origin  Fischer Black and Myron Scholes worked inFischer Black and Myron Scholes worked in Finance Faculty at MIT Published paper in 1973.Finance Faculty at MIT Published paper in 1973. They were later joined by Robert Merton.They were later joined by Robert Merton.  Fischer left academia in 1983, died in 1995 atFischer left academia in 1983, died in 1995 at 57.57.  1997 – Scholes and Merton got Nobel Prize1997 – Scholes and Merton got Nobel Prize
  • 16. Black-Scholes ModelBlack-Scholes Model Fischer Black and Myron Scholes, The Journal of Political Economy, 1973Fischer Black and Myron Scholes, The Journal of Political Economy, 1973 Assumptions:Assumptions:  The underlying stock pays no dividends.The underlying stock pays no dividends.  It is a European option.It is a European option.  The stock price is continuous and is distributedThe stock price is continuous and is distributed lognormally.lognormally.  There are no transaction costs and taxes.There are no transaction costs and taxes.  No restrictions or penalty on short sellingNo restrictions or penalty on short selling  The risk free rate is known and is constant overThe risk free rate is known and is constant over the life of the option.the life of the option.
  • 17. Black-Scholes ModelBlack-Scholes Model CC00 = S= S00 N (dN (d11 ) – E/e) – E/ertrt N (dN (d22 ) where,) where, CC00 = Present equilibrium value of call option= Present equilibrium value of call option SS00 = Current stock price= Current stock price EE = Exercise price= Exercise price ee = Base of natural logarithm= Base of natural logarithm rr = Continuously compounded risk free interest rate= Continuously compounded risk free interest rate tt = length of time in years to expiration= length of time in years to expiration N (*)N (*) = Cumulative probability distribution function of a= Cumulative probability distribution function of a standardized normal distributionstandardized normal distribution
  • 18. Black-Scholes ModelBlack-Scholes Model C = S N (dC = S N (d11 ) – K) – Kee-rt-rt N (dN (d22 ) where,) where, CC = Present equilibrium value of call option= Present equilibrium value of call option SS = Current stock price= Current stock price KK = Exercise price= Exercise price ee = Base of natural logarithm= Base of natural logarithm rr = Continuously compounded risk free interest rate= Continuously compounded risk free interest rate tt = length of time in years to expiration= length of time in years to expiration N (*)N (*) = Cumulative probability distribution function of a= Cumulative probability distribution function of a standardized normal distributionstandardized normal distribution
  • 19. Black-Scholes ModelBlack-Scholes Model llnn (S(S00 /E) + (r + ½/E) + (r + ½ σσ22 )t)t dd11 == σσ √t√t llnn (S(S00 /E) + (r - ½/E) + (r - ½ σσ22 )t)t dd22 == σσ √t√t where lwhere lnn is the natural logarithmis the natural logarithm
  • 20. Black-Scholes ModelBlack-Scholes Model llnn (S/K(S/K ee-rt-rt )) dd11 == + 0.5+ 0.5 σσ √t√t σσ √t√t dd22 == dd11 -- σσ √t√t where lwhere lnn is the natural logarithmis the natural logarithm
  • 21. IllustrationIllustration The standard deviation of the continuouslyThe standard deviation of the continuously compounded stock price change for acompounded stock price change for a company is estimated to be 20% per year.company is estimated to be 20% per year. The stock currently sells for Rs.80 and theThe stock currently sells for Rs.80 and the effective annual interest rate is Rs.15.03%.effective annual interest rate is Rs.15.03%. What is the value of a one year call optionWhat is the value of a one year call option on the stock of the company if the exerciseon the stock of the company if the exercise price is Rs.82?price is Rs.82?
  • 22. The Linkage between Calls, Puts,The Linkage between Calls, Puts, Stock, and Risk-Free BondsStock, and Risk-Free Bonds .. Call Stock Put Risk-Free Bond Black-Scholes Call Option Pricing Model Put-Call Parity Black-Scholes Put Option Pricing Model
  • 23. Put-Call Parity TheoremPut-Call Parity Theorem Payoffs just beforePayoffs just before expirationexpiration If SIf S11 < E< E If SIf S11 > E> E 1.1. Buy the equity stockBuy the equity stock SS11 SS11 2.2. Buy a put optionBuy a put option E-SE-S11 00 3.3. Borrow amount equalBorrow amount equal to exercise priceto exercise price - E- E - E- E 1+2+3=Buy a call option1+2+3=Buy a call option 00 SS11 - E- E
  • 24. Using Black-Scholes ModelUsing Black-Scholes Model 1.1. Find the Standard Deviation of theFind the Standard Deviation of the continuously compounded asset value changecontinuously compounded asset value change and the square root of the time left toand the square root of the time left to expirationexpiration 2.2. Calculate ratio of the current asset value toCalculate ratio of the current asset value to the present value of the exercise pricethe present value of the exercise price 3.3. Consult the table giving %age relationshipConsult the table giving %age relationship between the value of the Call Option and thebetween the value of the Call Option and the stock price corresponding to the value instock price corresponding to the value in steps 1 and 2steps 1 and 2 4.4. Value of Put Option = Value of Call Option +Value of Put Option = Value of Call Option + PV of exercise price – Stock PricePV of exercise price – Stock Price
  • 25. IllustrationIllustration Find the value of a one year call option asFind the value of a one year call option as well as a put option, if the current stockwell as a put option, if the current stock price is Rs.120, exercise price is Rs.125 andprice is Rs.120, exercise price is Rs.125 and the S.D. of continuously compounded pricethe S.D. of continuously compounded price change of the stock is 30%. The effectivechange of the stock is 30%. The effective interest rate is 15.03% so that the interestinterest rate is 15.03% so that the interest factor is 1.1503.factor is 1.1503.
  • 26. IllustrationIllustration Step 1: Standard Deviation × √Time = 0.30 × √1Step 1: Standard Deviation × √Time = 0.30 × √1 = 0.30= 0.30 Step 2: The ratio of stock price to the PV ofStep 2: The ratio of stock price to the PV of exercise price = 120 ÷ 125/1.1503exercise price = 120 ÷ 125/1.1503 = 120/108.7 = 1.10= 120/108.7 = 1.10 Step 3: Consulting the table we get 16.5% of theStep 3: Consulting the table we get 16.5% of the stock price as the value of call option i.e.stock price as the value of call option i.e. 120×0.165 = 19.8120×0.165 = 19.8 Step 4: Value of Put OptionStep 4: Value of Put Option = 19.8 + 108.7 – 120 = 8.5= 19.8 + 108.7 – 120 = 8.5
  • 27.
  • 28.
  • 29. Variants of Black-Scholes ModelVariants of Black-Scholes Model  To price European options on dividendTo price European options on dividend paying options and American options onpaying options and American options on non-dividend paying stocks (Robertnon-dividend paying stocks (Robert Merton, 1973 and Clifford Smith, 1976).Merton, 1973 and Clifford Smith, 1976).  American call options on dividend-payingAmerican call options on dividend-paying stocks (Richard Roll, 1977; Robertstocks (Richard Roll, 1977; Robert Whaley, 1981; and Richard Geske andWhaley, 1981; and Richard Geske and Richard Roll, 1984)Richard Roll, 1984)
  • 30. Variants of Black-Scholes ModelVariants of Black-Scholes Model  When price changes are discontinuousWhen price changes are discontinuous (Cox, Rubinstein and Ross, 1979). This(Cox, Rubinstein and Ross, 1979). This was published in Journal of Financialwas published in Journal of Financial Economics as “Option Pricing: AEconomics as “Option Pricing: A Simplified Approach”. This is the BinomialSimplified Approach”. This is the Binomial Model for Option Pricing.Model for Option Pricing.
  • 31. Garman - Kohlhagen ModelGarman - Kohlhagen Model The foreign currency option pricing modelThe foreign currency option pricing model is equivalent to the Black-Scholes modeis equivalent to the Black-Scholes mode except that the spot rate is discounted byexcept that the spot rate is discounted by the foreign interest rate and appearsthe foreign interest rate and appears instead of the Stock Price.instead of the Stock Price.
  • 32. Sensitivity of Option PremiumsSensitivity of Option Premiums  An option’s intrinsic value is the amount byAn option’s intrinsic value is the amount by which it is in the money and the time valuewhich it is in the money and the time value is the difference between actual premiumis the difference between actual premium and the intrinsic value i.e. premium =and the intrinsic value i.e. premium = intrinsic value + time value.intrinsic value + time value.  At the money option has highest likelihoodAt the money option has highest likelihood of gaining intrinsic value as compared toof gaining intrinsic value as compared to that of losing. It has no value to lose butthat of losing. It has no value to lose but 50-50 chance of gaining.50-50 chance of gaining.
  • 33. Sensitivity of Option PremiumsSensitivity of Option Premiums Delta (Delta (δδ):): Change in option price relativeChange in option price relative to the price of underlying asset. Reverseto the price of underlying asset. Reverse of Delta is used to calculate a hedge ratio.of Delta is used to calculate a hedge ratio. Gamma:Gamma: The rate of change of Delta. It isThe rate of change of Delta. It is the second derivative of option price withthe second derivative of option price with respect to price of the asset and is alsorespect to price of the asset and is also known as option’s curvature. High gammaknown as option’s curvature. High gamma makes option less attractive.makes option less attractive.
  • 34. Sensitivity of Option PremiumsSensitivity of Option Premiums Lambda:Lambda: Change in option price relative toChange in option price relative to change in volatility. Its value lies betweenchange in volatility. Its value lies between zero and infinity and declines as optionzero and infinity and declines as option approaches maturityapproaches maturity Theta:Theta: Change in option price relative toChange in option price relative to Time to Expiration. The value of theta liesTime to Expiration. The value of theta lies between zero and total value of option.between zero and total value of option. Rho:Rho: Change in option value in relation toChange in option value in relation to interest rates and varies from type to typeinterest rates and varies from type to type of the options.of the options.
  • 35. Sensitivity of Option PremiumsSensitivity of Option Premiums Implied volatility is obtained by finding theImplied volatility is obtained by finding the S.D. that when used in the Black-ScholesS.D. that when used in the Black-Scholes model makes the model price equal tomodel makes the model price equal to market price of the option.market price of the option. The pattern of implied volatility acrossThe pattern of implied volatility across expirations is often called the termexpirations is often called the term structure of volatility, and the pattern ofstructure of volatility, and the pattern of volatility across exercise prices is oftenvolatility across exercise prices is often called the volatility smile or skew.called the volatility smile or skew.
  • 36. IllustrationIllustration If on February 1, one wants to price a MarchIf on February 1, one wants to price a March European call option of a company,European call option of a company, WhereWhere SS == Rs.92.00Rs.92.00 KK == Rs.95.00Rs.95.00 tt == 50 days,50 days, or (50/365=0.137 years)or (50/365=0.137 years) rr == 7.12%7.12% σσ == 35%35% and the company does not pay anyand the company does not pay any dividendsdividends
  • 37. Return RelativesReturn Relatives  If P(0) is the beginning wealth andIf P(0) is the beginning wealth and P(T), the ending wealth, the priceP(T), the ending wealth, the price relative R(0,T) is given by P(T)/P(0).relative R(0,T) is given by P(T)/P(0). Since P(T) is a random variable,Since P(T) is a random variable, P(T)/P(0) is also a random variable.P(T)/P(0) is also a random variable.  Holding period return is the effectiveHolding period return is the effective return r(T) is related to R(0,T).return r(T) is related to R(0,T).  Continuous holding period return rContinuous holding period return r cc (T)(T) is related to price relative by:is related to price relative by: rrcc (T) =(T) = ln(R(0,T)).ln(R(0,T)).  Thus all these are random variables.Thus all these are random variables.