1 Financial Options. 2 Topics in Chapter 1. What is a financial option? 2. Options Terminology 3....

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Financial Options

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Topics in Chapter

1. What is a financial option?2. Options Terminology3. Profit and Loss Diagrams4. Where and How Options Trade?5. The Binomial Model 6. Black-Scholes Option Pricing Model

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1. What is a financial option?

An option is a contract which gives its holder the right, but not the obligation, to buy (or sell) an asset at some predetermined price within a specified period of time.

It does not obligate its owner to take any action. It merely gives the owner the right to buy or sell an asset.

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2.Option Terminology

A call option gives you the right to buy within a specified time period at a specified price

The owner of the option pays a cash premium to the option seller in exchange for the right to buy

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2. Option Terminology

A put option gives you the right to sell within a specified time period at a specified price

It is not necessary to own the asset before acquiring the right to sell it

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Strike (or exercise) price: The price stated in the option contract at which the security can be bought or sold.

Expiration date: The last date the option can be exercised.

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Exercise value: The value of a call option if it were exercised today = Max[0, Current stock price - Strike price] Note: The exercise value is zero if the

stock price is less than the strike price.

Option price: The market price of the option contract.

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The price of an option has two components: Intrinsic value:

For a call option equals the stock price minus the striking price

For a put option equals the striking price minus the stock price

Time value equals the option premium minus the intrinsic value


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3. Profit and Loss Diagrams

For the Disney JUN 22.50 Call buyer:

-$0.25

$22.50

$0

Maximum loss

Breakeven Point = $22.75Maximum profit is unlimited

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For the Disney JUN 22.50 Call writer:

$0.25

$22.50

$0

Maximum profit Breakeven Point = $22.75

Maximum loss is unlimited

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For the Disney JUN 22.50 Put buyer:

-$1.05

$22.50

$0

Maximum loss

Breakeven Point = $21.45

Maximum profit = $21.45

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3. Profit and Loss DiagramsConsider the following data:

Strike price = $25.

Stock Price Call Option Price

$25 $3.00

30 7.50

35 12.00

40 16.50

45 21.00

50 25.50

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3. Profit and Loss Diagrams Exercise Value of Option

Price of stock (a)

Strike price (b)

Exercise valueof option (a)–(b)

$25.00 $25.00 $0.00

30.00 25.00 5.00

35.00 25.00 10.00

40.00 25.00 15.00

45.00 25.00 20.00

50.00 25.00 25.00

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3. Profit and Loss Diagrams Market Price of Option

Price of stock (a)

Strike price (b)

Exer.val. (c)

Mkt. Price of opt. (d)

$25.00 $25.00 $0.00 $3.00

30.00 25.00 5.00 7.50

35.00 25.00 10.00 12.00

40.00 25.00 15.00 16.50

45.00 25.00 20.00 21.00

50.00 25.00 25.00 25.50

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Time Value of Option

Price of stock (a)

Strike price (b)

Exer.Val. (c)

Mkt. P of

opt. (d)

Time value

(d) – (c)

$25.00 $25.00 $0.00 $3.00 $3.00

30.00 25.00 5.00 7.50 2.50

35.00 25.00 10.00 12.00 2.00

40.00 25.00 15.00 16.50 1.50

45.00 25.00 20.00 21.00 1.00

50.00 25.00 25.00 25.50 0.50

165 10 15 20 25 30 35 40 Stock Price

Option value

30

25

20

15

10

5

Market price

Exercise value

Call Time Value Diagram

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4. Where and How Options Trade?

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4. Where and How Options Trade? Options trade on four principal

exchanges: Chicago Board Options Exchange (CBOE)

American Stock Exchange (AMEX)

Philadelphia Stock Exchange

Pacific Stock Exchange

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4. Where and How Options Trade? AMEX and Philadelphia Stock Exchange

options trade via the specialist system All orders to buy or sell a particular security

pass through a single individual (the specialist)

The specialist: Keeps an order book with standing orders from

investors and maintains the market in a fair and orderly fashion

Executes trades close to the current market price if no buyer or seller is available

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CBOE and Pacific Stock Exchange options trade via the marketmaker system Competing marketmakers trade in a

specific location on the exchange floor near the order book official

Marketmakers compete against one another for the public’s business

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Any given option has two prices at any given time: The bid price is the highest price

anyone is willing to pay for a particular option

The asked price is the lowest price at which anyone is willing to sell a particular option

5. The Binomial Model

The value of the replicating portfolio at time T, with stock price ST, is

ΔST + (1+r)T*B where Δ is the # of share s and B is cash invested

At the prices ST = Sou and ST = Sod, a replicating portfolio will satisfy

(Δ * Sou ) + (B * (1+r)T )= Cu

(Δ * Sod ) + (B * (1+r)T )= Cd

Solving for Δ and B

Δ = (Cu - Cd) / (So(u –d) )

B = (Cu - (Δ * Sou) )/ (1+r)T

and substitute in C = ΔSo + B to get the option price


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5. The Binomial Model Stock assumptions:

Current price: So = $27 In next 6 months, stock can either

Go up by factor of u = 1.41 Go down by factor of 0.71

Call option assumptions Expires in t = 6 months = 0.5 years Exercise price: X = $25 Risk-free rate: 6% a year a day (r = 0.06/365

a day)

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Currentstock priceSo = $27

Ending "up" price = fu = Sou = $38.07

Option payoff: Cu = MAX[0, fu−X] = $13.07

Ending “down" price = = fd = Sod = $19.17

Option payoff: Cd = MAX[0, fd −X] = $0.00u = 1.41d = 0.71X = $25

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5. Riskless Portfolio’s Payoffs at Call’s Expiration: $13.26

Currentstock priceSo = $27

Ending "up" price = fu = $38.07

Ending "up" stock value = Δ*fu = $26.33Option payoff: Cu = MAX[0, fu −X] = $13.07

Portfolio's net payoff = Δ*fu - Cu = $13.26

Ending “down" stock price = fd = $19.17

Ending “down" stock value = Δ*fd = $13.26Option payoff: Cd = MAX[0, fd −X] = $0.00Portfolio's net payoff = Δ*fd - Cd = $13.26

u = 1.41d = 0.71X = $25Δ = 0.6915

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5. Create portfolio by writing 1 option and buying Δ shares of stock.

Portfolio payoffs:

Stock is up: Δ * Sou − Cu

Stock is down: Δ * Sod − Cd

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5. The Hedge Portfolio with a Riskless Payoff

Set payoffs for up and down equal, solve for number of shares: Δ = (Cu − Cd) / (So(u − d)) B = (Cu − (Δ * Sou) )/ (1+r)T

= - (Portfolio's net payoff )/ (1+r)T In our example:

Δ = ($13.07 − $0) / $27(1.41 − 0.71) =0.6915 B = - $13.26/(1 + 0.06 / 365 )365*0.5 = -$12.87

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5. The Hedge Portfolio with a Riskless Payoff

Option Price C = ΔSo + B

= 0.6915($27) + (-$12.87) = $18.67 − $12.87

= $5.80If the call option’s price is not the same as the cost

of the replicating portfolio, then there will be an opportunity for arbitrage.

Option Premium C + (Commission)

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5. Arbitrage Example Suppose the option sells for $6.

You can write option, receiving $6. Create replicating portfolio for $5.80,

netting $6.00 −$5.80 = $0.20. Arbitrage:

You invested none of your own money. You have no risk (the replicating portfolio’s

payoffs exactly equal the payoffs you will owe because you wrote the option.

You have cash ($0.20) in your pocket.

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5. Arbitrage and Equilibrium Prices If you could make a sure arbitrage profit,

you would want to repeat it (and so would other investors).

With so many trying to write (sell) options, the extra “supply” would drive the option’s price down until it reached $5.80 and there were no more arbitrage profits available.

The opposite would occur if the option sold for less than $5.80.

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5. Multi-Period Binomial Pricing If you divided time into smaller periods

and allowed the stock price to go up or down each period, you would have a more reasonable outcome of possible stock prices when the option expires.

This type of problem can be solved with a binomial lattice.

As time periods get smaller, the binomial option price converges to the Black-Scholes price, which we discuss in later slides.

6. Black-Scholes

Fischer Black and Myron Scholes published the derivation and equation of the Black-Scholes Option Pricing Model in 1973 under several assumptions.

Bottom line: options of traded stocks are fundamentally priced

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6. Black-Scholes Option Pricing Model

The stock underlying the call option provides no dividends during the call option’s life.

There are no transactions costs for the sale/purchase of either the stock or the option.

Risk-free rate, rRF, is known and constant during the option’s life.

(More...)

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Security buyers may borrow any fraction of the purchase price at the short-term risk-free rate.

No penalty for short selling and sellers receive immediately full cash proceeds at today’s price.

Call option can be exercised only on its expiration date.

Security trading takes place in continuous time, and stock prices move randomly in continuous time.

6. Black Scholes Equation★Integration of statistical and mathematical models

★For example in the standard Black-Scholes model, the stock price evolves as

dS = μ(t)Sdt + σ(t)SdWt.

where μ is the drift parameter and σ is the implied volatility

★To sample a path following this distribution from time 0 to T, we divide the time interval into M units of length δt, and approximate the Brownian motion over the interval dt by a single normal variable of mean 0 and variance δt.

★The price f of any derivative (or option) of the stock S is a solution of the following partial-differential equation:

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The Black-Scholes OPM:

1 2

2

1

2 1

( ) ( )

ln( / ) ( / 2)

rtC S N d Ke N d

S K R td

t

d d t

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Variable definitions: C = theoretical call premium S = current stock price t = time in years until option

expiration K = option striking price R = risk-free interest rate

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Variable definitions (cont’d): = standard deviation of stock

returns N(x) = probability that a value less

than “x” will occur in a standard normal distribution

ln = natural logarithm e = base of natural logarithm (2.7183)

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Example

Stock ABC currently trades for $30. A call option on ABC stock has a striking price of $25 and expires in three months. The current risk-free rate is 5%, and ABC stock has a standard deviation of 0.45.

According to the Black-Scholes OPM, but should be the call option premium for this option?

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Example (cont’d)

Solution: We must first determine d1 and d2:

2

1

2

ln( / ) ( / 2)

ln(30 / 25) 0.05 (0.45 / 2) 0.25

0.45 0.250.1823 0.0378

0.9780.225

S K R td

t

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Example (cont’d)

Solution (cont’d):

2 1

0.978 (0.45) 0.25

0.978 0.225

0.753

d d t

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6. What is the value of the following call option according to the OPM?

Assume: N = P = $27 X = $25 rRF = 6% t = 0.5 years σ = 0.49

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d1 = {ln($27/$25) + [(0.06 + 0.492/2)](0.5)}

÷ {(0.49)(0.7071)}

d1 = 0.4819

d2 = 0.4819 - (0.49)(0.7071)

d2 = 0.1355

6. First, find d1 and d2.

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6. Second, find N(d1) and N(d2)

N(d1) = N(0.4819) = 0.6851 N(d2) = N(0.1355) = 0.5539

Note: Values obtained from Excel using NORMSDIST function. For example:

N(d1) = NORMSDIST(0.4819)

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6. Third, find value of option.

VC = $27(0.6851) - $25e-(0.06)(0.5)

(0.5539) = $19.3536 - $25(0.97045)(0.6327) = $5.06

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What impact do the following parameters have on a call option’s value?

Current stock price: Call option value increases as the current stock price increases.

Strike price: As the exercise price increases, a call option’s value decreases.

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6. Impact on Call Value

Option period: As the expiration date is lengthened, a call option’s value increases (more chance of becoming in the money.)

Risk-free rate: Call option’s value tends to increase as rRF increases (reduces the PV of the exercise price).

Stock return variance: Option value increases with variance of the underlying stock (more chance of becoming in the money).

6. Negative Affects Myron Scholes was a partner of Long-Term Capital

Management (LTCM) established in 1994. LTCM would use models and experienced investing

knowledge to pick differences in short and long securities, profiting from the small margin.

In 1998 the firm had $5B in equity and $125B in liability August 17, 1998 Russia devalues the rouble and suspended

$13.5B of it’s Treasury Bonds, causing LTCM’s equity to decrease drastically, ever increasing it’s leverage ratio

In order to prevent a stock market crash due to the outflux of investors and banks from LTCM’s funds the Federal Reserve organized a $3.5 B rescue effort to take over LTCM’s management

Had LTCM lost leverage, all banks and creditors would pull out of other firms – including Salomon Brothers, Merrill Lynch.

★In the field of mathematical finance, many problems, for instance the problem of finding the arbitrage-free value of a particular derivative, boil down to the computation of a particular integral.

★When the number of dimensions (or degrees of freedom) in the problem is large, PDE’s and numerical integrals become intractable, and in these cases Monte Carlo methods often give better results.

★Monte Carlo methods converge to the solution more quickly than numerical integration methods, require less memory , have less data dependencies and are easier to program.

★The idea is to use the result of Central Limit Theorem to allow us to generate a random set of samples as a valid representation of the previous value of the stock.

“The sum of large number of independent and identically distributed random variables will be approximately normal.”

7. Monte Carlo method

7. Monte Carlo method

St = S0e(a – 0.5 σ 2)t + σ√tZ

V Sne V S TrT

Ti

i

n( , ) ( , )0

1

01

If V(St,t) is the option payoff at time t, then the time-0 Monte Carlo price V(S0,0) is

where ST1, … , STn are n randomly drawn time-T stock prices

7. Option Pricing SensitivitiesThe Greeks

8. Parallel Computing

drift = mu*delt;sigma_sqrt_delt = sigma*sqrt(delt);S_old = zeros(N_sim,1);S_new = zeros(N_sim,1);S_old(1:N_sim,1) = S_init;for i=1:N % timestep loop% now, for each timestep, generate info for% all simulationsS_new(:,1) = S_old(:,1) +...S_old(:,1).*( drift + sigma_sqrt_delt*randn(N_sim,1) );S_new(:,1) = max(0.0, S_new(:,1) );% check to make sure that S_new cannot be < 0S_old(:,1) = S_new(:,1);%% end of generation of all data for all simulations% for this timestepend % timestep loop

8. MATLAB program for Monte Carlo

Peter Forsyth 2008

function [Pmean, width] = Asian(S, K, r, q, v, T, nn, nSimulations, CallPut) dt = T/nn;Drift = (r - q - v ^ 2 / 2) * dt;vSqrdt = v * sqrt(dt);pathSt = zeros(nSimulations,nn); Epsilon = randn(nSimulations,nn);St = S*ones(nSimulations,1);% for each time stepfor j = 1:nn; St = St .* exp(Drift + vSqrdt * Epsilon(:,j)); pathSt(:,j)=St;endSS = cumsum(pathSt,2);Pvals = exp(-r*T) * max(CallPut * (SS(:,nn)/nn - K), 0); % Pvals dimension: nSimulations x 1Pmean = mean(Pvals);width = 1.96*std(Pvals)/sqrt(nSimulations);

Elapsed time is 115.923847 seconds.price = 6.1268

8. MATLAB program for Asian Options

2009 Financial Derivatives Proposal

www.fbe.hku.hk/doc/courses/tpg/mfin/2007-2008/mfin7017/Chapter_2.ppt

8. Monte Carlo Parallelism

function MC (S, r, T, sigma, nSamples, nP) dataRand[nSamples] = rand(); start = idP*p/nSamples; end = (idP+1)*p/nSamples; for each idP

mean_value[idP] = findMC(S,E,r,T,sigma,dataRand[start,end));

end reduce(mean_value[idP]);endfunction

★Iterations are independent - Embarrassingly parallel

★Parallel Random Number Generation: Master Processor

★SPRNG (Scalable Pseudorandom Number Generation)

library

8. Binomial Parallelism

function Bin (S, E, r, T, sigma, nTime ) …

for step = nTime:-1:1for i=1:nStep+1

value(i) = (pUp*value(i+1)+pDown*value(i))*exp(-r*dt);

price(i) = price(i+1)*exp(-sigma*sqrt(dt)); value(i) = max(value(i), price(i)-E)endfunction

8. Binomial Parallelism

8. Finite Difference Parallelism

Explicit Finite Differences

★Careful: dt and dS are not independent

★Use Ghost points to minimize the communication

★Communication comes from one side only

Standard options

★Call, put

★European, American

Exotic options (non standard)

★More complex payoff (ex: Asian)

★Exercise opportunities (ex: Bermudian)

8. Types of options

2009 Financial Derivatives Proposal

Bibliography FIR 7155: Global Financial Management (Spring 2013)

https://umdrive.memphis.edu/cjiang/www/teaching/fir7155/powerpoint/FM12%20Ch%2008%20Show.ppt

Grid Enablement of Scientific Applications http://users.cis.fiu.edu/~sadjadi/Teaching/Autonomic%20Grid%20Computing/CEN%205082-Spring-2009/Presentations/FinancialDerivatives_05012009.ppt

“ASX – Australian Stock Exchange.” http://www.asx.com.au/. Tuesday, March 7,2006. “Black-Scholes.” http://en.wikipedia.org/wiki/Black-Scholes. Tuesday, March 7, 2006. “Case Study – LTCM.” http://www.erisk.com/Learning/CaseStudies/ref_case_ltcm.asp. Tuesday, March

7, 2006. Shah, Ajaj. “Black, Merton and Scholes:Their work and its consequences.”

http://www.mayin.org/ajayshah/PDFDOCS/Shah1997_bms.pdf. Tuesday, March 7, 2006. “YHOO: Options for YAHOO INC.” http://finance.yahoo.com/q/op?s=YHOO&m=2007-01. Peter Forsyth, “An Introduction to Computational Finance Without Agonizing Pain” Guangwu Liu , L. Jeff Hong, "Pathwise Estimation of The Greeks of Financial Options” John Hull, “Options, Futures and Other Derivatives” Kun-Lung Wu and Philip S. Yu, “Efficient Query Monitoring Using Adaptive Multiple Key Hashing” Denis Belomestny, Christian Bender, John Schoenmakers, “True upper bounds for Bermudan products

via non-nested Monte Carlo” Desmond J. Higham, “ An Introduction to Financial Option Valuation” Alexandros V. Gerbessiotis, “Architecture independent parallel binomial tree option price valuations” Bernt Arne Odegaard, “Financial Numerical Recipes in C++” Paul Wilmott, “Introduces Quantitative Finance”

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