MAFS5030 Quantitative Modeling of Derivative Securities ...

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1 MAFS5030 Quantitative Modeling of Derivative Securities Tutorial Note 4 MAFS5030 Quantitative Modeling of Derivative Securities Tutorial Note 4 Review on pricing technique in continuous time model (with multiple assets) In this tutorial, we shall review some important techniques in pricing derivatives involving more than one stochastic random variables/ underlying assets. One difficulty in pricing such derivatives is that the calculation involves the computation of expectation involving several correlated random variables. One needs to employ various methods/theorems so that one can compute the price in an easier way. The following summarizes some useful theorems/methods for this purpose: Girsanov Theorem (Describe the price dynamic of the underlying asset when the probability measure is changed from to ) Numeraire invariance theorem (Describe the pricing formula of a contingent claim when there is a change in numeraire) Quanto prewashing technique (A method to determine the drift rate of the target state variable under some probability measure in pricing quanto options). Example 1 (Pricing of exchange options: A quick review) We consider an exchange options (European) which the holder has the right to exchange units of asset for one units of asset . We let be the maturity date of the options. The terminal payoff of the options is seen to be ( , ) = max( βˆ’ , 0), where and are prices of assets and at maturity date respectively. We assume that the price processes of two assets are governed by = ( βˆ’ ) + , , = ( βˆ’ ) + , , where , and , are -Brownian with , , = . Given the current prices of two assets and , compute the current price of the exchange options. Solution We take = as the numeraire (recall that the asset pays continuous dividend at the yield rate ). Using numeraire invariance theorem, the current price of the exchange options can be expressed as

Transcript of MAFS5030 Quantitative Modeling of Derivative Securities ...

1 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Review on pricing technique in continuous time model (with multiple

assets)

In this tutorial, we shall review some important techniques in pricing derivatives

involving more than one stochastic random variables/ underlying assets. One difficulty

in pricing such derivatives is that the calculation involves the computation of

expectation involving several correlated random variables. One needs to employ various

methods/theorems so that one can compute the price in an easier way. The following

summarizes some useful theorems/methods for this purpose:

Girsanov Theorem (Describe the price dynamic of the underlying asset when the

probability measure is changed from 𝑃 to οΏ½ΜƒοΏ½)

Numeraire invariance theorem (Describe the pricing formula of a contingent

claim when there is a change in numeraire)

Quanto prewashing technique (A method to determine the drift rate of the

target state variable under some probability measure in pricing quanto options).

Example 1 (Pricing of exchange options: A quick review)

We consider an exchange options (European) which the holder has the right to

exchange 𝐾 units of asset 𝑋 for one units of asset π‘Œ. We let 𝑇 be the maturity date

of the options. The terminal payoff of the options is seen to be

𝑉𝑇(𝑋𝑇, π‘Œπ‘‡) = max(π‘Œπ‘‡ βˆ’ 𝐾𝑋𝑇 , 0), where 𝑋𝑇 and π‘Œπ‘‡ are prices of assets 𝑋 and π‘Œ at maturity date 𝑇 respectively. We

assume that the price processes of two assets are governed by

𝑑𝑋𝑑 = (π‘Ÿ βˆ’ π‘žπ‘‹)𝑋𝑑𝑑𝑑 + πœŽπ‘‹π‘‹π‘‘π‘‘π‘π‘‹,𝑑𝑄 ,

π‘‘π‘Œπ‘‘ = (π‘Ÿ βˆ’ π‘žπ‘Œ)π‘Œπ‘‘π‘‘π‘‘ + πœŽπ‘Œπ‘Œπ‘‘π‘‘π‘π‘Œ,𝑑𝑄 ,

where 𝑍𝑋,𝑑𝑄 and π‘π‘Œ,𝑑

𝑄 are 𝑄-Brownian with 𝑑𝑍𝑋,𝑑𝑄 π‘‘π‘π‘Œ,𝑑

𝑄 = πœŒπ‘‘π‘‘.

Given the current prices of two assets 𝑋𝑑 and π‘Œπ‘‘, compute the current price of the

exchange options.

Solution

We take �̂�𝑑 = π‘’π‘žπ‘‹π‘‘π‘‹π‘‘ as the numeraire (recall that the asset 𝑋 pays continuous dividend

at the yield rate π‘žπ‘‹). Using numeraire invariance theorem, the current price of the

exchange options can be expressed as

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Tutorial Note 4

𝑉𝑑 = π‘’βˆ’π‘Ÿ(π‘‡βˆ’π‘‘)𝔼𝑄[𝑉𝑇(𝑋𝑇 , π‘Œπ‘‡)|ℱ𝑑] = 𝑀𝑑𝔼

𝑄 [𝑉𝑇(𝑋𝑇, π‘Œπ‘‡)

𝑀𝑇|ℱ𝑑] = �̂�𝑑𝔼

𝑄𝑋 [𝑉𝑇(𝑋𝑇, π‘Œπ‘‡)

�̂�𝑇|ℱ𝑑]

= π‘’π‘žπ‘‹π‘‘π‘‹π‘‘π”Όπ‘„π‘‹ [

max(π‘Œπ‘‡ βˆ’ 𝐾𝑋𝑇 , 0)

π‘’π‘žπ‘‹π‘‡π‘‹π‘‡|ℱ𝑑]

= 𝑋𝑑 π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘)𝔼𝑄𝑋 [max (

π‘Œπ‘‡π‘‹π‘‡βˆ’ 𝐾) |ℱ𝑑]

⏟ π‘π‘Ÿπ‘–π‘π‘’ π‘œπ‘“ π‘‘β„Žπ‘’ 𝑒π‘₯π‘β„Žπ‘Žπ‘›π‘”π‘’ π‘œπ‘π‘‘π‘–π‘œπ‘›π‘  π‘Žπ‘‘ π‘‘π‘–π‘šπ‘’ 𝑑

(π‘šπ‘’π‘Žπ‘ π‘’π‘Ÿπ‘’π‘‘ 𝑖𝑛 𝑒𝑛𝑖𝑑𝑠 π‘œπ‘“ π‘Žπ‘ π‘ π‘’π‘‘ 𝑋)

……(βˆ—)

To calculate the expectation 𝔼𝑄𝑋 [max (π‘Œπ‘‡

π‘‹π‘‡βˆ’ 𝐾) |ℱ𝑑], we need to know the

β€œdistribution” of the random variable π‘Œπ‘‡

𝑋𝑇 under 𝑄𝑋.

By applying Ito’s lemma on the function 𝑓(𝑋𝑑, π‘Œπ‘‘) =π‘Œπ‘‘

𝑋𝑑, we get

𝑑 (π‘Œπ‘‘π‘‹π‘‘) =

[

(π‘Ÿ βˆ’ π‘žπ‘‹)π‘‹π‘‘πœ•π‘“

πœ•π‘‹π‘‘+ (π‘Ÿ βˆ’ π‘žπ‘Œ)π‘Œπ‘‘

πœ•π‘“

πœ•π‘Œπ‘‘βŸ

βˆ‘ πœ‡π‘–πœ•π‘“πœ•π‘‹π‘–

𝑛𝑖=1

+1

2πœŽπ‘‹2𝑋𝑑

2πœ•2𝑓

πœ•π‘‹π‘‘2 + πœŒπœŽπ‘‹πœŽπ‘Œπ‘‹π‘‘π‘Œπ‘‘

πœ•2𝑓

πœ•π‘‹π‘‘πœ•π‘Œπ‘‘+1

2πœŽπ‘Œ2π‘Œπ‘‘

2πœ•2𝑓

πœ•π‘Œπ‘‘2

⏟ 12βˆ‘ βˆ‘ πœŽπ‘–πœŽπ‘—

πœ•2π‘“πœ•π‘‹π‘–πœ•π‘‹π‘—

𝑛𝑗=1

𝑛𝑖=1 ]

𝑑𝑑 + πœŽπ‘‹π‘‹π‘‘πœ•π‘“

πœ•π‘‹π‘‘π‘‘π‘π‘‹,𝑑

𝑄

+ πœŽπ‘Œπ‘Œπ‘‘πœ•π‘“

πœ•π‘Œπ‘‘π‘‘π‘π‘Œ,𝑑

𝑄 .

β‡’ 𝑑 (π‘Œπ‘‘π‘‹π‘‘) = [(π‘Ÿ βˆ’ π‘žπ‘‹)𝑋𝑑 (βˆ’

π‘Œπ‘‘

𝑋𝑑2) + (π‘Ÿ βˆ’ π‘žπ‘Œ)π‘Œπ‘‘ (

1

𝑋𝑑) +

1

2πœŽπ‘‹2𝑋𝑑

2 (2π‘Œπ‘‘

𝑋𝑑3)

+ πœŒπœŽπ‘‹πœŽπ‘Œπ‘‹π‘‘π‘Œπ‘‘ (βˆ’1

𝑋𝑑2) +

1

2πœŽπ‘Œ2π‘Œπ‘‘

2(0)] 𝑑𝑑 + πœŽπ‘‹π‘‹π‘‘ (βˆ’π‘Œπ‘‘

𝑋𝑑2)𝑑𝑍𝑋,𝑑

𝑄

+ πœŽπ‘Œπ‘Œπ‘‘ (1

𝑋𝑑)π‘‘π‘π‘Œ,𝑑

𝑄

β‡’ 𝑑 (π‘Œπ‘‘π‘‹π‘‘) = [(π‘Ÿ βˆ’ π‘žπ‘Œ) βˆ’ (π‘Ÿ βˆ’ π‘žπ‘‹) + πœŽπ‘‹

2 βˆ’ πœŒπœŽπ‘‹πœŽπ‘Œ]π‘Œπ‘‘π‘‹π‘‘π‘‘π‘‘ βˆ’ πœŽπ‘‹

π‘Œπ‘‘π‘‹π‘‘π‘‘π‘π‘‹,𝑑

𝑄 + πœŽπ‘Œπ‘Œπ‘‘π‘‹π‘‘π‘‘π‘π‘Œ,𝑑

𝑄

By taking π‘Šπ‘‘ =π‘Œπ‘‘

𝑋𝑑, we get

Unfortunately, the above equation is not useful because the random variables 𝑍𝑋,𝑑𝑄 and

π‘π‘Œ,𝑑𝑄 are no longer to be the Brownian motion under 𝑄𝑋.

Step 1: Compute the price dynamic of π‘Œπ‘‘/𝑋𝑑

π‘‘π‘Šπ‘‘ = [(π‘Ÿ βˆ’ π‘žπ‘Œ) βˆ’ (π‘Ÿ βˆ’ π‘žπ‘‹) + πœŽπ‘‹2 βˆ’ πœŒπœŽπ‘‹πœŽπ‘Œ]π‘Šπ‘‘π‘‘π‘‘ βˆ’ πœŽπ‘‹π‘Šπ‘‘π‘‘π‘π‘‹,𝑑

𝑄 + πœŽπ‘Œπ‘Šπ‘‘π‘‘π‘π‘Œ,𝑑𝑄

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Tutorial Note 4

To do this, we shall use Girsanov theorem. Firstly, the Radon-Nikodym derivative is

given by

𝐿𝑑 =𝑑𝑄𝑋𝑑𝑄

|β„±0 =�̂�𝑑/οΏ½Μ‚οΏ½0𝑀𝑑/𝑀0

=⏞

�̂�𝑑=π‘‹π‘‘π‘’π‘žπ‘‹π‘‘

𝑀𝑑=π‘’π‘Ÿπ‘‘ 𝑋𝑑𝑒

π‘žπ‘‹π‘‘

𝑋0π‘’π‘Ÿπ‘‘

1

=

𝑋0𝑒(π‘Ÿβˆ’π‘žπ‘‹βˆ’

πœŽπ‘‹2

2)𝑑+πœŽπ‘‹π‘π‘‹,𝑑

𝑄

π‘’π‘žπ‘‹π‘‘

𝑋0π‘’π‘Ÿπ‘‘

= π‘’βˆ’πœŽπ‘‹2

2𝑑+πœŽπ‘‹π‘π‘‹,𝑑

𝑄

= π‘’βˆ« βˆ’(βˆ’πœŽπ‘‹)𝑑𝑍𝑋,𝑑𝑄𝑑

0βˆ’12∫

(βˆ’πœŽπ‘‹)2𝑑𝑠

𝑑0 .

By taking 𝛾(𝑑) = βˆ’πœŽπ‘‹, one can deduce from Girsanov’s theorem that the process

𝑍𝑋,𝑑𝑄𝑋 = 𝑍𝑋,𝑑

𝑄 +∫ 𝛾(𝑠)𝑑𝑠𝑑

0

= 𝑍𝑋,𝑑𝑄 βˆ’ πœŽπ‘‹π‘‘

is a 𝑄𝑋-Brownian.

It remains to get a corresponding 𝑄𝑋-Brownian for π‘π‘Œ,𝑑𝑄 . From the result in the Lecture

Note (I skipped the details here), we get that the process

π‘π‘Œ,𝑑𝑄𝑋 = π‘π‘Œ,𝑑

𝑄 βˆ’ πœŒπœŽπ‘‹π‘‘,

is also a 𝑄𝑋-Brownian with 𝑑𝑍𝑋,𝑑𝑄𝑋(π‘‘π‘π‘Œ,𝑑

𝑄𝑋) = πœŒπ‘‘π‘‘.

Using 𝑄𝑋, the price dynamic of π‘‘π‘Šπ‘‘ can now be expressed as

π‘‘π‘Šπ‘‘ = [(π‘Ÿ βˆ’ π‘žπ‘Œ) βˆ’ (π‘Ÿ βˆ’ π‘žπ‘‹) + πœŽπ‘‹2 βˆ’ πœŒπœŽπ‘‹πœŽπ‘Œ]π‘Šπ‘‘π‘‘π‘‘ βˆ’ πœŽπ‘‹π‘Šπ‘‘π‘‘ (𝑍𝑋,𝑑

𝑄 + πœŽπ‘‹π‘‘)⏟

𝑍𝑋,𝑑𝑄

+ πœŽπ‘Œπ‘Šπ‘‘π‘‘ (π‘π‘Œ,𝑑𝑄𝑋 + πœŒπœŽπ‘‹π‘‘)⏟

π‘π‘Œ,𝑑𝑄

Hence, we get

Note that the sum βˆ’πœŽπ‘‹π‘Šπ‘‘π‘‘π‘π‘‹,𝑑𝑄𝑋 + πœŽπ‘Œπ‘Šπ‘‘π‘‘π‘π‘Œ,𝑑

𝑄𝑋 is normally distributed with mean 0 and

variance (πœŽπ‘‹2 βˆ’ 2πœŒπœŽπ‘‹πœŽπ‘Œ + πœŽπ‘Œ

2)π‘Šπ‘‘2𝑑𝑑. So we can write the above equation as

where 𝑍𝑑𝑄𝑋 is 𝑄𝑋-Brownian.

Step 2: Replace 𝑍𝑋,𝑑𝑄 and π‘π‘Œ,𝑑

𝑄 by two 𝑄𝑋-Brownians

π‘‘π‘Šπ‘‘ = (π‘žπ‘‹ βˆ’ π‘žπ‘Œ)π‘Šπ‘‘π‘‘π‘‘ βˆ’ πœŽπ‘‹π‘Šπ‘‘π‘‘π‘π‘‹,𝑑𝑄𝑋 + πœŽπ‘Œπ‘Šπ‘‘π‘‘π‘π‘Œ,𝑑

𝑄𝑋

π‘‘π‘Šπ‘‘ = (π‘žπ‘‹ βˆ’ π‘žπ‘Œ)π‘Šπ‘‘π‘‘π‘‘ + √(πœŽπ‘‹2 βˆ’ 2πœŒπœŽπ‘‹πœŽπ‘Œ + πœŽπ‘Œ

2)⏟

πœŽπ‘Š

π‘Šπ‘‘π‘‘π‘π‘‘π‘„π‘‹

4 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Given the current value of 𝑋𝑑, π‘Œπ‘‘ (so that π‘Šπ‘‘ =π‘Œπ‘‘

𝑋𝑑 is known), the value of π‘Šπ‘‡ at maturity

date 𝑇 can now be expressed as

π‘Šπ‘‡ = π‘Šπ‘‘π‘’(π‘žπ‘‹βˆ’π‘žπ‘Œβˆ’

πœŽπ‘Š2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘Šπ‘π‘‡βˆ’π‘‘

𝑄𝑋

.

Note that

π‘Šπ‘‡ =π‘Œπ‘‡π‘‹π‘‡> 𝐾 ⇔ π‘π‘‡βˆ’π‘‘

𝑄𝑋 >lnπΎπ‘Šπ‘‘βˆ’ (π‘žπ‘‹ βˆ’ π‘žπ‘Œ βˆ’

πœŽπ‘Š2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘ŠβŸ π‘‘π‘’π‘›π‘œπ‘‘π‘’π‘‘ 𝑏𝑦 𝑑

From equation (βˆ—), the time-𝑑 price of the exchange options can now be expressed as

𝑉𝑑 = π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘)𝔼𝑄𝑋 [max (

π‘Œπ‘‡π‘‹π‘‡βˆ’ 𝐾) |ℱ𝑑] = 𝑋𝑑𝑒

βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘)𝔼𝑄𝑋[max(π‘Šπ‘‡ βˆ’ 𝐾) |ℱ𝑑]

= π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) [∫ (π‘Šπ‘‘π‘’

(π‘žπ‘‹βˆ’π‘žπ‘Œβˆ’πœŽπ‘Š2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘Šπ‘§

βˆ’πΎ)(1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))π‘‘π‘§βˆž

𝑑

+∫ (0) (1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))𝑑𝑧𝑑

βˆ’βˆž

]

= π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) [∫ π‘Šπ‘‘π‘’

(π‘žπ‘‹βˆ’π‘žπ‘Œβˆ’πœŽπ‘Š2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘Šπ‘§

(1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))π‘‘π‘§βˆž

𝑑

βˆ’ 𝐾∫ (1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))π‘‘π‘§βˆž

𝑑

]

= π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) [π‘Šπ‘‘π‘’

(π‘žπ‘‹βˆ’π‘žπ‘Œ)(π‘‡βˆ’π‘‘)∫ (1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’(π‘§βˆ’πœŽπ‘Š(π‘‡βˆ’π‘‘))

2

2(π‘‡βˆ’π‘‘) )π‘‘π‘§βˆž

𝑑

βˆ’ 𝐾∫ (1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’12(

𝑧

βˆšπ‘‡βˆ’π‘‘)2

)π‘‘π‘§βˆž

𝑑

]

=⏞

𝑧1=π‘§βˆ’πœŽπ‘Š(π‘‡βˆ’π‘‘)

βˆšπ‘‡βˆ’π‘‘

𝑧2=𝑧

βˆšπ‘‡βˆ’π‘‘

π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) [π‘Šπ‘‘π‘’

(π‘žπ‘‹βˆ’π‘žπ‘Œ)(π‘‡βˆ’π‘‘)∫ (1

√2πœ‹π‘’βˆ’

𝑧12

2 )𝑑𝑧1

∞

π‘‘βˆ’πœŽπ‘Š(π‘‡βˆ’π‘‘)

βˆšπ‘‡βˆ’π‘‘

βˆ’ 𝐾∫ (1

√2πœ‹π‘’βˆ’

𝑧22 )𝑑𝑧2

∞

𝑑

βˆšπ‘‡βˆ’π‘‘

]

Step 3: Obtain the price process of π‘Šπ‘‘ under 𝑄𝑋

Step 4: Obtain the pricing formula

5 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

= π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘)π‘Šπ‘‘π‘’

(π‘žπ‘‹βˆ’π‘žπ‘Œ)(π‘‡βˆ’π‘‘) [1 βˆ’ 𝑁 (𝑑 βˆ’ πœŽπ‘Š(𝑇 βˆ’ 𝑑)

βˆšπ‘‡ βˆ’ 𝑑)]

βˆ’ πΎπ‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) [1 βˆ’ 𝑁 (

𝑑

βˆšπ‘‡ βˆ’ 𝑑)]

= π‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) (

π‘Œπ‘‘π‘‹π‘‘) 𝑒(π‘žπ‘‹βˆ’π‘žπ‘Œ)(π‘‡βˆ’π‘‘) [𝑁 (βˆ’

𝑑 βˆ’ πœŽπ‘Š(𝑇 βˆ’ 𝑑)

βˆšπ‘‡ βˆ’ 𝑑)]

βˆ’ πΎπ‘‹π‘‘π‘’βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘) [𝑁 (βˆ’

𝑑

βˆšπ‘‡ βˆ’ 𝑑)]

= π‘Œπ‘‘π‘’βˆ’π‘žπ‘Œ(π‘‡βˆ’π‘‘)𝑁(𝑑1) βˆ’ 𝐾𝑋𝑑𝑒

βˆ’π‘žπ‘‹(π‘‡βˆ’π‘‘)𝑁(𝑑2),

where

𝑑1 = βˆ’π‘‘ βˆ’ πœŽπ‘Š(𝑇 βˆ’ 𝑑)

βˆšπ‘‡ βˆ’ 𝑑=ln (

π‘Œπ‘‘πΎπ‘‹π‘‘

) + (π‘žπ‘‹ βˆ’ π‘žπ‘Œ +πœŽπ‘Š2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘Šβˆšπ‘‡ βˆ’ 𝑑

𝑑2 = βˆ’π‘‘

βˆšπ‘‡ βˆ’ 𝑑=ln (

π‘Œπ‘‘πΎπ‘‹π‘‘

) + (π‘žπ‘‹ βˆ’ π‘žπ‘Œ βˆ’πœŽπ‘Š2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘Šβˆšπ‘‡ βˆ’ 𝑑

Example 2 (Quantos digital options)

(a) We consider a quanto on a foreign currency denominated asset which pays

holder an amount 𝐹𝑇 (1 unit of foreign currency) at the maturity date 𝑇 if the

asset price 𝑆𝑇 is above 𝑋𝑓 and nothing if otherwise. So the terminal payoff of

the options can be expressed as

𝑉𝑇(𝑆𝑇, 𝐹𝑇) = {𝐹𝑇 𝑖𝑓 𝑆𝑇 β‰₯ 𝑋𝑓

0 𝑖𝑓 𝑆𝑇 < 𝑋𝑓.

Here, 𝐹𝑇 denotes the exchange rate for the foreign currency and 𝑆𝑇 is the

price (measured in foreign currency) of the underlying asset. We assume that

both 𝐹𝑇 and 𝑆𝑇 are governing by Geometric Brownian motion.

Given the value of 𝐹𝑑 and 𝑆𝑑, what is the time-𝑑 price of the options?

(b) We consider a quanto on a foreign currency denominated asset which pays

holder an amount 𝐹𝑇 (1 unit of foreign currency) at the maturity date 𝑇 if the

asset price 𝑆𝑇 is above 𝑋𝑓 and nothing if otherwise. So the terminal payoff of

the options can be expressed as

𝑉𝑇(𝑆𝑇, 𝐹𝑇) = {1 𝑖𝑓 𝑆𝑇 β‰₯ 𝑋𝑓

0 𝑖𝑓 𝑆𝑇 < 𝑋𝑓.

Here, 𝐹𝑇 denotes the exchange rate for the foreign currency and 𝑆𝑇 is the

price (measured in foreign currency) of the underlying asset. What is the

corresponding time-𝑑 price of the options?

6 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Some notations:

We let 𝑄𝑑 and 𝑄𝑓 be the risk neutral probability measure under domestic

currency and foreign currency respectively.

We let π‘Ÿπ‘‘ and π‘Ÿπ‘“ be the risk-free interest rate of domestic currency and foreign

currency respectively.

Solution of (a)

Assuming the options is attainable, the time-𝑑 price of the quanto options can be

expressed, using risk neutral valuation principle, as

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝑉𝑇(𝑆𝑇, 𝐹𝑇)|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑 [πΉπ‘‡πŸ{𝑆𝑇>𝑋𝑓}|ℱ𝑑].

We take 𝑁(𝑑) = π‘’π‘Ÿπ‘“π‘‘πΉπ‘‘ as the numeraire (*Here, 𝑁𝑑 is the value of one unit of foreign

currency bought at time 0). Using numeraire invariance theorem, we deduce that

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑 [πΉπ‘‡πŸ{𝑆𝑇>𝑋𝑓}|ℱ𝑑] =⏞

𝑀𝑑(𝑑)=π‘’π‘Ÿπ‘‘π‘‘

𝑀𝑑(𝑑)

𝑀𝑑(𝑇)𝔼𝑄𝑑 [πΉπ‘‡πŸ{𝑆𝑇>𝑋𝑓}|ℱ𝑑]

= 𝑀𝑑(𝑑)𝔼𝑄𝑑 [

πΉπ‘‡πŸ{𝑆𝑇>𝑋𝑓}

𝑀𝑑(𝑇)|ℱ𝑑] =

(βˆ—) 𝑁(𝑑)𝔼𝑄𝑓 [πΉπ‘‡πŸ{𝑆𝑇>𝑋𝑓}

𝑁(𝑇)|ℱ𝑑]

= π‘’π‘Ÿπ‘“π‘‘πΉπ‘‘π”Όπ‘„π‘“ [

πΉπ‘‡πŸ{𝑆𝑇>𝑋𝑓}

π‘’π‘Ÿπ‘“π‘‡πΉπ‘‡|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝐹𝑑𝔼𝑄𝑓 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑].

So we get

To calculate the expectation, we need to obtain the price dynamic of 𝑆𝑇 under the

probability measure 𝑄𝑓.

Since 𝑆𝑑 is assumed to follow Geometric Brownian Motion and its value is in foreign

currency, so under risk neutral probability measure 𝑄𝑓 (in foreign currency world), 𝑆𝑑

should follow:

Here, π‘ž is dividend yield rate of the asset (π‘ž = 0 if the asset is non-dividend paying) and

πœŽπ‘† is the volatility of the asset.

IDEA: It may be difficult to compute the expectation directly since we need to

handle two correlated random variables (𝐹𝑇 , 𝑆𝑇) simultaneously. The computation

would be easier if we apply change of numeraire technical by taking the foreign

currency as the numeraire.

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝐹𝑑𝔼

𝑄𝑓 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑]

𝑑𝑆𝑑 = (π‘Ÿπ‘“ βˆ’ π‘ž)𝑆𝑑𝑑𝑑 + πœŽπ‘†π‘†π‘‘π‘‘π‘π‘‘π‘„π‘“ .

7 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Given the current value of 𝑆𝑑, the asset price at the maturity date can be expressed as

𝑆𝑇 = 𝑆𝑑𝑒(π‘Ÿπ‘“βˆ’π‘žβˆ’

πœŽπ‘†2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘†π‘π‘‡βˆ’π‘‘

𝑄𝑓

.

Together with the fact that π‘π‘‡βˆ’π‘‘π‘„π‘“ is normally distributed with mean 0 and variance 𝑇 βˆ’ 𝑑

and the fact that

𝑆𝑇 > 𝑋𝑓 ⇔ π‘π‘‡βˆ’π‘‘π‘„π‘“ >

lnπ‘‹π‘“π‘†π‘‘βˆ’ (π‘Ÿπ‘“ βˆ’ π‘ž βˆ’

πœŽπ‘†2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘†βŸ 𝑑

the expectation can be computed as

𝔼𝑄𝑓 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑] = ∫ (1)1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘)π‘‘π‘§βˆž

𝑑

=⏞

𝑦=𝑧

βˆšπ‘‡βˆ’π‘‘

∫1

√2πœ‹π‘’βˆ’

𝑦2

2 π‘‘π‘¦βˆž

𝑑

βˆšπ‘‡βˆ’π‘‘

= 1 βˆ’ 𝑁 (𝑑

βˆšπ‘‡ βˆ’ 𝑑) = 𝑁 (βˆ’

𝑑

βˆšπ‘‡ βˆ’ 𝑑)

= 𝑁

(

ln𝑆𝑑𝑋𝑓+ (π‘Ÿπ‘“ βˆ’ π‘ž βˆ’

πœŽπ‘†2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘†βˆšπ‘‡ βˆ’ π‘‘βŸ =𝑑1 )

.

Hence, the time-𝑑 price of the quanto options is

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝐹𝑑𝔼

𝑄𝑓 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑] = π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝐹𝑑𝑁(𝑑1).

Solution of (b)

Using risk neutral valuation principle, the time-𝑑 price of the quanto options can be

expressed, using risk neutral valuation principle, as

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝑉𝑇(𝑆𝑇, 𝐹𝑇)|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑].

Recall that the price dynamic of 𝑆𝑇 under 𝑄𝑓 is

𝑑𝑆𝑑𝑆𝑑= (π‘Ÿπ‘“ βˆ’ π‘ž)𝑑𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑

𝑄𝑓 .

Using Girsanov’s theorem, the corresponding price process of 𝑆𝑇 under 𝑄𝑑 is given by 𝑑𝑆𝑑𝑆𝑑= 𝛿𝑆

𝑑𝑑𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑𝑄𝑑 .

Here, 𝑍𝑆,𝑑𝑄𝑑 is standard Brownian motion under 𝑄𝑑.

IDEA: To calculate the expectation, we need to obtain the price dynamic of 𝑆𝑇

under 𝑄𝑑 (in domestic world). To do so, we shall apply the quanto prewashing

technique.

8 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

We note the followings:

Using risk neutral probability measure 𝑄𝑑, the price process π‘†π‘‘βˆ— = 𝑆𝑑𝐹𝑑 (price of

the asset under domestic currency) should have a drift rate π›Ώπ‘†βˆ—π‘‘ = π‘Ÿπ‘‘ βˆ’ π‘ž

Under risk neutral probability measure 𝑄𝑑, the price process 𝐹𝑑 should satisfy 𝑑𝐹𝑑𝐹𝑑= (π‘Ÿπ‘‘ βˆ’ π‘Ÿπ‘“)𝑑𝑑 + πœŽπΉπ‘‘π‘πΉ,𝑑

𝑄𝑑 .

Here, 𝑍𝐹,𝑑𝑄𝑑 is standard Brownian motion under 𝑄𝑑. We assume that

(𝑑𝑍𝑆,𝑑𝑄𝑑)(𝑑𝑍𝐹,𝑑

𝑄𝑑) = πœŒπ‘‘π‘‘.

By applying Ito’s lemma on the function 𝑓(𝑆𝑑, 𝐹𝑑) = 𝑆𝑑𝐹𝑑, we obtain

𝑑(𝑆𝑑𝐹𝑑) = (0 + 𝐹𝑑(𝛿𝑑𝑆𝑆𝑑) + 𝑆𝑑(π‘Ÿπ‘‘ βˆ’ π‘Ÿπ‘“)𝐹𝑑 + πœŒπœŽπ‘†πœŽπΉπΉπ‘‘π‘†π‘‘)𝑑𝑑 + 𝑆𝑑(πœŽπΉπΉπ‘‘)𝑑𝑍𝐹,𝑑

𝑄𝑑

+ 𝐹𝑑(πœŽπ‘†π‘†π‘‘)𝑑𝑍𝑆,𝑑𝑄𝑑

β‡’ 𝑑(𝑆𝑑𝐹𝑑) = 𝑆𝑑𝐹𝑑[(𝛿𝑑𝑆 + π‘Ÿπ‘‘ βˆ’ π‘Ÿπ‘“ + πœŒπœŽπ‘†πœŽπΉ)𝑑𝑑 + πœŽπΉπ‘‘π‘πΉ,𝑑

𝑄𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑𝑄𝑑]

⇒𝑑𝑆𝑑

βˆ—

π‘†π‘‘βˆ— =

𝑑(𝑆𝑑𝐹𝑑)

𝑆𝑑𝐹𝑑= (𝛿𝑑

𝑆 + π‘Ÿπ‘‘ βˆ’ π‘Ÿπ‘“ + πœŒπœŽπ‘†πœŽπΉ)⏟ π›Ώπ‘†βˆ—π‘‘

𝑑𝑑 + πœŽπΉπ‘‘π‘πΉ,𝑑𝑄𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑

𝑄𝑑 .

By comparing the drift rates, we have

𝛿𝑑𝑆 + π‘Ÿπ‘‘ βˆ’ π‘Ÿπ‘“ + πœŒπœŽπ‘†πœŽπΉ = π‘Ÿπ‘‘ βˆ’ π‘ž β‡’ 𝛿𝑑

𝑆 = π‘Ÿπ‘“ βˆ’ π‘ž βˆ’ πœŒπœŽπ‘†πœŽπΉ.

The price process of the 𝑆𝑑 under 𝑄𝑑 is

Given the value of 𝑆𝑑, the asset price at the maturity date 𝑇 is

𝑆𝑇 = 𝑆𝑑𝑒(π‘Ÿπ‘“βˆ’π‘žβˆ’πœŒπœŽπ‘†πœŽπΉβˆ’

𝜎𝐹2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘†π‘π‘†,π‘‡βˆ’π‘‘

𝑄𝑑

.

Using similar method as in (a), the expectation can be computed as

𝔼𝑄𝑑 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑] = ∫ (1)1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘)π‘‘π‘§βˆž

𝑑′= β‹― = 𝑁(βˆ’

𝑑′

βˆšπ‘‡ βˆ’ 𝑑) = 𝑁(𝑑1

β€² ),

where 𝑑′ =ln𝑋𝑓

π‘†π‘‘βˆ’(π‘Ÿβˆ’π‘žβˆ’

πœŽπ‘†2

2)(π‘‡βˆ’π‘‘)

πœŽπ‘† and 𝑑1

β€² =ln𝑆𝑑𝑋𝑓+(π‘Ÿπ‘“βˆ’π‘žβˆ’πœŒπœŽπ‘†πœŽπΉβˆ’

πœŽπ‘†2

2)(π‘‡βˆ’π‘‘)

πœŽπ‘†βˆšπ‘‡βˆ’π‘‘.

Hence, the time-𝑑 price of this quanto options is given by

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑 [𝟏{𝑆𝑇>𝑋𝑓}|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝑁(𝑑1β€² ).

How to determine 𝛿𝑆𝑑?

𝑑𝑆𝑑𝑆𝑑= (π‘Ÿπ‘“ βˆ’ π‘ž βˆ’ πœŒπœŽπ‘†πœŽπΉ)𝑑𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑

𝑄𝑑

9 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Example 3 (Two more examples on quanto options: A quick review)

(a) We consider a foreign equity call struck which the terminal payoff is given by

𝑉𝑇 = 𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓, 0).

Find the time-𝑑 price of the quanto options.

(b) We consider a fixed exchange rate foreign equity call which the terminal

payoff is given by

𝑉𝑇 = 𝐹0max(𝑆𝑇 βˆ’ 𝑋𝑓, 0),

Where 𝐹0 is the predetermined fixed exchange rate. Find the time-𝑑 price of

the quanto options.

(*The notations used in this example is same as those used in Example 2)

Solution of (a)

The time-𝑑 price of the quanto options can be expressed, using risk neutral valuation

principle, as

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝑉𝑇(𝑆𝑇 , 𝐹𝑇)|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓, 0) |ℱ𝑑].

Since the expectation involves two random variables, one shall simplify the expectation

using change of numeraire technique (take foreign currency 𝐹𝑑 as numeraire).

We take 𝑁𝑑 = π‘’π‘Ÿπ‘“π‘‘πΉπ‘‘ as our numeraire. By numeraire invariance theorem, we deduce

that

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0) |ℱ𝑑]

=βžπ‘€π‘‘=𝑒

π‘Ÿπ‘‘π‘€π‘‘π‘€π‘‡

𝔼𝑄𝑑[𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓, 0) |ℱ𝑑]

= 𝑀𝑑𝔼𝑄𝑑 [

𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0)

𝑀𝑇|ℱ𝑑]

= 𝑁𝑑𝔼𝑄𝑓 [

𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0)

𝑁𝑇|ℱ𝑑] = 𝑒

π‘Ÿπ‘“π‘‘πΉπ‘‘π”Όπ‘„π‘“ [

𝐹𝑇max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0)

π‘’π‘Ÿπ‘“π‘‡πΉπ‘‡|ℱ𝑑]

= π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝐹𝑑𝔼𝑄𝑓[max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0) |ℱ𝑑].

So we get

To calculate the above expectation, we observe that the term π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝔼𝑄𝑓[max(𝑆𝑇 βˆ’

𝑋𝑓 , 0) |ℱ𝑑] is simply the time-𝑑 price of the European call option on the foreign asset in

foreign currency. So we have

π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝔼𝑄𝑓[max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0) |ℱ𝑑] = 𝑐𝑓(𝑆, 𝑑)

= π‘†π‘‘π‘’βˆ’π‘ž(π‘‡βˆ’π‘‘)𝑁(𝑑1) βˆ’ 𝑋𝑓𝑒

βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝑁(𝑑2),

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘“(π‘‡βˆ’π‘‘)𝐹𝑑𝔼

𝑄𝑓[max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0) |ℱ𝑑]

10 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

where

𝑑1 =

ln𝑆𝑑𝑋𝑓+ (π‘Ÿπ‘“ βˆ’ π‘ž +

πœŽπ‘†2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘†βˆšπ‘‡ βˆ’ 𝑑, 𝑑2 = 𝑑1 βˆ’ πœŽπ‘†βˆšπ‘‡ βˆ’ 𝑑.

Solution of (b)

The time-𝑑 price of the quanto options can be expressed, using risk neutral valuation

principle, as

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝑉𝑇(𝑆𝑇 , 𝐹𝑇)|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝐹0max(𝑆𝑇 βˆ’ 𝑋𝑓 , 0) |ℱ𝑑].

Since there is only one random variable in the expectation, we can compute the

expectation directly without using change of numeraire.

To compute the expectation, one needs to obtain the price dynamic of 𝑆𝑑 under risk

neutral probability measure 𝑄𝑑 (not 𝑄𝑓).

Using similar method as in Example 2(b), we get

Given the current value of 𝑆𝑑, the value of 𝑆𝑇 can be expressed as

𝑆𝑇 = 𝑆𝑑𝑒(𝛿𝑆

π‘‘βˆ’πœŽπ‘†2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘†π‘π‘†,π‘‡βˆ’π‘‘

𝑄𝑑

. Note that

𝑆𝑇 > 𝑋 ⇔ 𝑍𝑆,π‘‡βˆ’π‘‘π‘„π‘‘ >

lnπ‘‹π‘†π‘‘βˆ’ (𝛿𝑆

𝑑 βˆ’πœŽπ‘†2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘†βŸ 𝑑

.

Together with the fact that 𝑍𝑆,π‘‡βˆ’π‘‘π‘„π‘‘ is normally distributed with mean 0 and variance 𝑇 βˆ’

𝑑, the fair price can be computed as

𝑉𝑑(𝑆𝑑, 𝐹𝑑) = π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘)𝔼𝑄𝑑[𝐹0max(𝑆𝑇 βˆ’ 𝑋𝑓, 0) |ℱ𝑑]

= 𝐹0π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘) [∫ (𝑆𝑑𝑒

(π›Ώπ‘†π‘‘βˆ’πœŽπ‘†2

2)(π‘‡βˆ’π‘‘)+πœŽπ‘†π‘§

βˆ’ 𝑋𝑓)(1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))π‘‘π‘§βˆž

𝑑

]

= β‹― = 𝐹0π‘’βˆ’π‘Ÿπ‘‘(π‘‡βˆ’π‘‘) [𝑆𝑒𝛿𝑆

𝑑(π‘‡βˆ’π‘‘)𝑁(𝑑1) βˆ’ 𝑋𝑓𝑁(𝑑2)],

where

𝑑1 =

ln𝑆𝑑𝑋𝑓+ (𝛿𝑆

𝑑 +πœŽπ‘†2

2 )(𝑇 βˆ’ 𝑑)

πœŽπ‘†βˆšπ‘‡ βˆ’ 𝑑, 𝑑2 = 𝑑1 βˆ’ πœŽπ‘†βˆšπ‘‡ βˆ’ 𝑑.

𝑑𝑆𝑑𝑆𝑑= 𝛿𝑆

𝑑𝑑𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑𝑄𝑑 = (π‘Ÿπ‘“ βˆ’ π‘ž βˆ’ πœŒπœŽπ‘†πœŽπΉ)𝑑𝑑 + πœŽπ‘†π‘‘π‘π‘†,𝑑

𝑄𝑑

11 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Example 4 (Problem 4 of 2013 Final)

We let 𝐹𝑆\π‘ˆ = 𝐹𝑆\π‘ˆ(𝑑) denote the Singaporean currency price of 1 unit of US

currency and 𝐹𝐻\𝑆 denote the Hong Kong currency price of 1 unit of Singaporean

currency.

Assume that 𝐹𝑆\π‘ˆ is governed by the following dynamics (GBM) under the risk

neutral measure 𝑄𝑆 in the Singaporean currency world: 𝑑𝐹𝑆\π‘ˆ

𝐹𝑆\π‘ˆ= (π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ‘ˆπ‘†π·)𝑑𝑑 + πœŽπΉπ‘†\π‘ˆπ‘‘π‘πΉπ‘†\π‘ˆ

𝑄𝑆 ,

where 𝑍𝐹𝑆\π‘ˆπ‘„π‘† is the Brownian motion under 𝑄𝑆.

We consider a quanto option that pays 𝐹𝐻\𝑆 Hong Kong dollars if 𝐹𝑆\π‘ˆ is above the

strike price 𝑋. Find the value of the quanto option in Hong Kong currency in terms of

the riskless interest rates of different currency worlds and volatility values πœŽπΉπ‘†\π‘ˆ and

𝜎𝐹𝐻\𝑆 .

Solution

We shall calculate the price of the quanto options by the following steps:

Using risk neutral valuation principle, the price of the quanto price (in HKD currency) is

given by

𝑉𝑑 = π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄

𝐻[𝑉𝑇|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄𝐻[𝐹𝐻\𝑆(𝑇)𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑].

Since the expectation involves two random variables, one needs to simplify the

expectation by applying β€œchange of numeraire” technique.

Note that 𝐹𝐻\𝑆 represents the price of 1 unit of Singaporean currency in HKD currency.

We shall choose Singaporean currency as our new numeraire.

We take 𝑁𝑑 = π‘’π‘Ÿπ‘†πΊπ·π‘‘πΉπ»\𝑆(𝑑) as the numeriare. By numeraire invariance theorem, the

pricing formula can be expressed as

𝑉𝑑 = π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄

𝐻[𝐹𝐻\𝑆(𝑇)𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑]

=βžπ‘€π‘‘=𝑒

π‘Ÿπ»πΎπ·π‘‘π‘€π‘‘π‘€π‘‡

𝔼𝑄𝐻[𝐹𝐻\𝑆(𝑇)𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑]

= 𝑀𝑑𝔼𝑄𝐻 [

𝐹𝐻\𝑆(𝑇)

π‘€π‘‡πŸ{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑] = 𝑁𝑑𝔼

𝑄𝑆 [𝐹𝐻\𝑆(𝑇)

π‘π‘‡πŸ{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑]

= π‘’π‘Ÿπ‘†πΊπ·π‘‘πΉπ»\𝑆(𝑑)𝔼𝑄𝑆 [

𝐹𝐻\𝑆(𝑇)

π‘’π‘Ÿπ‘†πΊπ·π‘‡πΉπ»\𝑆(𝑇)𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑]

= π‘’βˆ’π‘Ÿπ‘†πΊπ·(π‘‡βˆ’π‘‘)𝐹𝐻\𝑆(𝑑)𝔼𝑄𝑆 [𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑]

Step 1: Choose the β€œcorrect” measure (HKD/SGD/USD) for calculating the price

12 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

So we get

Recall that 𝐹𝑆\π‘ˆ denotes the price of 1 unit of US currency in Singaporean currency and

it can be treated as price of an asset in Singaporean currency. Under risk neutral

probability measure 𝑄𝑆, 𝐹𝑆\π‘ˆ should follow (as given in the question):

(*Note: Here, π‘Ÿπ‘ˆπ‘†π· is seen to be continuous yield rate (risk-free interest of USD

currency) of the underlying asset (USD currency).)

Given the current exchange rate 𝐹𝑆\π‘ˆ = 𝐹𝑆\π‘ˆ(𝑑) at time 𝑑, the exchange rate at the

maturity date 𝑇 can be expressed as

Here, 𝑍𝐹𝑆\π‘ˆπ‘„π‘† = 𝑍𝐹𝑆\π‘ˆ,π‘‡βˆ’π‘‘

𝑄𝑆 is normally distributed with mean 0 and variance 𝑇 βˆ’ 𝑑 under

𝑄𝑆.

Note that

𝐹𝑆\π‘ˆ(𝑇) > 𝑋 ⇔ 𝑍𝐹𝑆\π‘ˆπ‘„π‘† >

ln𝑋𝐹𝑆\π‘ˆ

βˆ’ (π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ‘ˆπ‘†π· βˆ’πœŽπΉπ‘†\π‘ˆ2

2 ) (𝑇 βˆ’ 𝑑)

πœŽπΉπ‘†\π‘ˆβŸ 𝑑

Then the expectation can be computed as

𝔼𝑄𝑆[𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑] = ∫ (1) (

1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))π‘‘π‘§βˆž

𝑑

=⏞

𝑦=𝑧

βˆšπ‘‡βˆ’π‘‘

∫1

√2πœ‹π‘’βˆ’

𝑦2

2 π‘‘π‘¦βˆž

𝑑

βˆšπ‘‡βˆ’π‘‘

= 1 βˆ’ 𝑁 (𝑑

βˆšπ‘‡ βˆ’ 𝑑) = 𝑁 (βˆ’

𝑑

βˆšπ‘‡ βˆ’ 𝑑)

𝑉𝑑 = π‘’βˆ’π‘Ÿπ‘†πΊπ·(π‘‡βˆ’π‘‘)𝐹𝐻\𝑆(𝑑)𝔼

𝑄𝑆 [𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝑋}|ℱ𝑑]

Step 2: Predict the price dynamic of 𝐹𝑆\π‘ˆ

𝑑𝐹𝑆\π‘ˆ

𝐹𝑆\π‘ˆ= (π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ‘ˆπ‘†π·)𝑑𝑑 + πœŽπΉπ‘†\π‘ˆπ‘‘π‘πΉπ‘†\π‘ˆ

𝑄𝑆 .

Step 3: Compute the price of the options

𝐹𝑆\π‘ˆ(𝑇) = 𝐹𝑆\π‘ˆπ‘’(π‘Ÿπ‘†πΊπ·βˆ’π‘Ÿπ‘ˆπ‘†π·βˆ’

πœŽπΉπ‘†\π‘ˆ2

2)(π‘‡βˆ’π‘‘)+πœŽπΉπ‘†\π‘ˆπ‘πΉπ‘†\π‘ˆ

𝑄𝑆

.

13 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

= 𝑁

(

ln𝐹𝑆\π‘ˆπ‘‹ + (π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ‘ˆπ‘†π· βˆ’

πœŽπΉπ‘†\π‘ˆ2

2 ) (𝑇 βˆ’ 𝑑)

πœŽπΉπ‘†\π‘ˆβˆšπ‘‡ βˆ’ π‘‘βŸ =𝑑1 )

.

Then the current price of the derivative is given by

𝑉𝑑 = π‘’βˆ’π‘Ÿπ‘†πΊπ·(π‘‡βˆ’π‘‘)𝐹𝐻\𝑆(𝑑)𝑁(𝑑1).

Example 5 (Problem 9 of HW3)

We let 𝐹𝑆\π‘ˆ denote the Singaporean currency price of one unit of US currency and

𝐹𝐻\𝑆 denote the Hong Kong currency price of one unit of Singaporean currency.

Suppose we assume 𝐹𝑆\π‘ˆ to be governed by the following dynamics under the risk

neutral measure 𝑄𝑆 in the Singaporean currency world: 𝑑𝐹𝑆\π‘ˆ

𝐹𝑆\π‘ˆ= (π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ‘ˆπ‘†π·)𝑑𝑑 + πœŽπΉπ‘†\π‘ˆπ‘‘π‘πΉπ‘†\π‘ˆ

𝑄𝑆 ,

Where π‘Ÿπ‘†πΊπ· and π‘Ÿπ‘ˆπ‘†π· are the Singaporean and US riskless interest rates, respectively.

Similar Geometric Brownian motion assumption is made of other exchange rate

processes.

We consider a digital quanto option pays 1 US dollar at maturity if 𝐹𝑆\π‘ˆ is above

𝛼𝐹𝐻\π‘ˆ for some constant value 𝛼. Find the value of the digital quanto option in Hong

Kong currency.

Solution

We shall calculate the price of the quanto options by the following steps:

Using risk neutral valuation principle, the price of the quanto price (in HKD currency) is

given by

𝑉𝑑 = π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄

𝐻[𝑉𝑇|ℱ𝑑] = 𝑒

βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄𝐻[𝐹𝐻\π‘ˆ(𝑇)𝟏{𝐹𝑆\π‘ˆ(𝑇)>𝛼𝐹𝐻\π‘ˆ(𝑇)}|ℱ𝑑]

= π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄𝐻[𝐹𝐻\π‘ˆ(𝑇)𝟏

{𝐹𝑆\π‘ˆ(𝑇)

𝐹𝐻\π‘ˆ(𝑇)>𝛼}|ℱ𝑑]

=⏞

πΉπ‘ˆ\𝐻=1

𝐹𝐻\π‘ˆ

π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄𝐻[𝐹𝐻\π‘ˆ(𝑇)𝟏{𝐹𝑆\π‘ˆ(𝑇)πΉπ‘ˆ\𝐻(𝑇)>𝛼}|ℱ𝑑]

=⏞

𝐹𝑆\𝐻=𝐹𝑆\π‘ˆπΉπ‘ˆ\𝐻

π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄𝐻[𝐹𝐻\π‘ˆ(𝑇)𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑].

Step 1: Choose the β€œcorrect” measure (HKD/SGD/USD) for calculating the price

14 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Since the expectation involves two random variables, one needs to simplify the

expectation by applying β€œchange of numeraire” technique.

Note that 𝐹𝐻\π‘ˆ represents the price of 1 unit of USD currency in HKD currency. We shall

choose USD currency as our new numeraire.

We take 𝑁𝑑 = π‘’π‘Ÿπ‘ˆπ‘†π·π‘‘πΉπ»\π‘ˆ(𝑑) as the numeriare. By numeraire invariance theorem, the

pricing formula can be expressed as

𝑉𝑑 = π‘’βˆ’π‘Ÿπ»πΎπ·(π‘‡βˆ’π‘‘)𝔼𝑄

𝐻[𝐹𝐻\π‘ˆ(𝑇)𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑]

=βžπ‘€π‘‘=𝑒

π‘Ÿπ»πΎπ·π‘‘π‘€π‘‘π‘€π‘‡

𝔼𝑄𝐻[𝐹𝐻\π‘ˆ(𝑇)𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑]

= 𝑀𝑑𝔼𝑄𝐻 [

𝐹𝐻\π‘ˆ(𝑇)

π‘€π‘‡πŸ{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑] = 𝑁𝑑𝔼

π‘„π‘ˆ [𝐹𝐻\π‘ˆ(𝑇)

π‘π‘‡πŸ{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑]

= π‘’π‘Ÿπ‘ˆπ‘†π·π‘‘πΉπ»\π‘ˆ(𝑑)π”Όπ‘„π‘ˆ [

𝐹𝐻\π‘ˆ(𝑇)

π‘’π‘Ÿπ‘ˆπ‘†π·π‘‡πΉπ»\π‘ˆ(𝑇)𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑]

= π‘’βˆ’π‘Ÿπ‘ˆπ‘†π·(π‘‡βˆ’π‘‘)𝐹𝐻\π‘ˆ(𝑑)π”Όπ‘„π‘ˆ [𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑]

So we get

Since 𝐹𝑆\𝐻 is assumed to follow GBM, so the governing equation for 𝐹𝑆\𝐻 is

where 𝑍𝐹𝑆\π»π‘„π‘ˆ is π‘„π‘ˆ-Brownian.

However, 𝐹𝑆\𝐻 denotes the price of 1 HKD currency in SGD currency (not USD currency).

So we CANNOT simply say that the drift rate 𝛿𝐹𝑆\π»π‘ˆ equals π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ»πΎπ·.

Here, one has to apply quanto prewashing technique to find the drift rate 𝛿𝐹𝑆\π»π‘ˆ .

By treating 𝐹𝑆\𝐻 as the foreign asset (price in SGD currency) and taking πΉπ‘ˆ\𝑆 as the

exchange rate (SGD β†’ USD), we observe that the product πΉπ‘ˆ\𝑆𝐹𝑆\𝐻 = πΉπ‘ˆ\𝐻 is simply the

price of 1 HKD currency in USD currency.

So under π‘„π‘ˆ, the price dynamic of πΉπ‘ˆ\𝐻 should satisfy

π‘‘πΉπ‘ˆ\𝐻

πΉπ‘ˆ\𝐻= (π‘Ÿπ‘ˆπ‘†π· βˆ’ π‘Ÿπ»πΎπ·)⏟

π‘‘π‘Ÿπ‘–π‘“π‘‘ π‘Ÿπ‘Žπ‘‘π‘’

𝑑𝑑 + πœŽπΉπ‘ˆ\π»π‘‘π‘πΉπ‘ˆ\π»π‘„π‘ˆ ……(2).

𝑉𝑑 = π‘’βˆ’π‘Ÿπ‘ˆπ‘†π·(π‘‡βˆ’π‘‘)𝐹𝐻\π‘ˆ(𝑑)𝔼

π‘„π‘ˆ [𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑].

Step 2: Predict the price dynamic of 𝐹𝑆\𝐻 in π‘„π‘ˆ

𝑑𝐹𝑆\𝐻

𝐹𝑆\𝐻= 𝛿𝐹𝑆\𝐻

π‘ˆ 𝑑𝑑 + πœŽπΉπ‘†\𝐻𝑑𝑍𝐹𝑆\π»π‘„π‘ˆ , …… (1)

.

15 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

On the other hand, the price dynamic of πΉπ‘ˆ\𝑆 under π‘„π‘ˆ is given by

π‘‘πΉπ‘ˆ\𝑆

πΉπ‘ˆ\𝑆= (π‘Ÿπ‘ˆπ‘†π· βˆ’ π‘Ÿπ‘†πΊπ·)⏟

π‘‘π‘Ÿπ‘–π‘“π‘‘ π‘Ÿπ‘Žπ‘‘π‘’

𝑑𝑑 + πœŽπΉπ‘ˆ\π‘†π‘‘π‘πΉπ‘ˆ\π‘†π‘„π‘ˆ ……(3).

applying Ito’s lemma on 𝑓 = πΉπ‘ˆ\𝑆𝐹𝑆\𝐻, we get (*Note: We assume π‘‘π‘πΉπ‘ˆ\π‘†π‘„π‘ˆ 𝑑𝑍𝐹𝑆\𝐻

π‘„π‘ˆ = πœŒπ‘‘π‘‘)

𝑑(πΉπ‘ˆ\𝑆𝐹𝑆\𝐻)

πΉπ‘ˆ\𝑆𝐹𝑆\𝐻⏟

=π‘‘πΉπ‘ˆ\π»πΉπ‘ˆ\𝐻

= [(π‘Ÿπ‘ˆπ‘†π· βˆ’ π‘Ÿπ‘†πΊπ·) + 𝛿𝐹𝑆\π»π‘ˆ + πœŒπœŽπΉπ‘ˆ\π‘†πœŽπΉπ‘†\𝐻] 𝑑𝑑 + πœŽπΉπ‘ˆ\π‘†π‘‘π‘πΉπ‘ˆ\𝑆

π‘„π‘ˆ + πœŽπΉπ‘†\𝐻𝑑𝑍𝐹𝑆\π»π‘„π‘ˆ .

By comparing the drift rates [with equation (2)], we have

(π‘Ÿπ‘ˆπ‘†π· βˆ’ π‘Ÿπ‘†πΊπ·) + 𝛿𝐹𝑆\π»π‘ˆ + πœŒπœŽπΉπ‘ˆ\π‘†πœŽπΉπ‘†\𝐻 = π‘Ÿπ‘ˆπ‘†π· βˆ’ π‘Ÿπ»πΎπ·

Given the current value of 𝐹𝑆\𝐻 = 𝐹𝑆\𝐻(𝑑), the exchange rate at the maturity date can

be expressed as (from equation (1)):

𝐹𝑆\𝐻(𝑇) = 𝐹𝑆\𝐻𝑒(𝛿𝐹𝑆\𝐻

π‘ˆ βˆ’πœŽπΉπ‘†\𝐻2

2)(π‘‡βˆ’π‘‘)+πœŽπΉπ‘†\𝐻𝑍𝐹𝑆\𝐻

π‘„π‘ˆ

,

where 𝑍𝐹𝑆\π»π‘„π‘ˆ = 𝑍𝐹𝑆\𝐻

π‘„π‘ˆ (𝑇 βˆ’ 𝑑) is normally distributed with mean 0 and variance 𝑇 βˆ’ 𝑑

under 𝑄𝐢. Note that

𝐹𝑆\𝐻(𝑇) > 𝛼 ⇔ 𝑍𝐹𝑆\π»π‘„π‘ˆ

>

ln𝛼𝐹𝑆\𝐻

βˆ’ (𝛿𝐹𝑆\π»π‘ˆ βˆ’

πœŽπΉπ‘†\𝐻2

2 ) (𝑇 βˆ’ 𝑑)

πœŽπΉπ‘†\𝐻⏟ 𝑑

So the expectation (in step 1) can be computed as

π”Όπ‘„π‘ˆ[𝟏{𝐹𝑆\𝐻(𝑇)>𝛼}|ℱ𝑑] = ∫ (1) (

1

√2πœ‹(𝑇 βˆ’ 𝑑)π‘’βˆ’

𝑧2

2(π‘‡βˆ’π‘‘))π‘‘π‘§βˆž

𝑑

=⏞

𝑦=𝑧

βˆšπ‘‡βˆ’π‘‘

∫1

√2πœ‹π‘’βˆ’

𝑦2

2 π‘‘π‘¦βˆž

𝑑

βˆšπ‘‡βˆ’π‘‘

= 1 βˆ’ 𝑁 (𝑑

βˆšπ‘‡ βˆ’ 𝑑) = 𝑁 (βˆ’

𝑑

βˆšπ‘‡ βˆ’ 𝑑)

= 𝑁

(

ln𝐹𝑆\𝐻𝛼+ (𝛿𝐹𝑆\𝐻

π‘ˆ βˆ’πœŽπΉπ‘†\𝐻2

2) (𝑇 βˆ’ 𝑑)

πœŽπΉπ‘†\π»βˆšπ‘‡ βˆ’ π‘‘βŸ =𝑑1 )

.

Then the current price of the derivative is given by

𝑉𝑑 = π‘’βˆ’π‘Ÿπ‘ˆπ‘†π·(π‘‡βˆ’π‘‘)𝐹𝐻\π‘ˆ(𝑑)𝑁(𝑑1),

where 𝛿𝐹𝑆\π»π‘ˆ = π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ»πΎπ· βˆ’ πœŒπœŽπΉπ‘ˆ\π‘†πœŽπΉπ‘†\𝐻 .

β‡’ 𝛿𝐹𝑆\π»π‘ˆ = π‘Ÿπ‘†πΊπ· βˆ’ π‘Ÿπ»πΎπ· βˆ’ πœŒπœŽπΉπ‘ˆ\π‘†πœŽπΉπ‘†\𝐻

Step 3: Compute the price of the options

16 MAFS5030 Quantitative Modeling of Derivative Securities

Tutorial Note 4

Appendix – Some useful theorem

Girsanov Theorem

Let 𝑍𝑃(𝑑) be a Brownian motion under the probability measure 𝑃. Consider a non-

anticipative function 𝛾(𝑑) with respect to 𝑍𝑃(𝑑) that satisfies the Novikov condition:

𝔼 [π‘’βˆ«12𝛾(𝑠)2𝑑𝑠

𝑑0 ] < ∞

We let οΏ½ΜƒοΏ½ be another probability measure and consider the Radon-Nikodym derivative

𝑑�̃�

𝑑𝑃= 𝜌(𝑑) = exp(∫ βˆ’π›Ύ(𝑠)𝑑𝑍𝑝(𝑠)

𝑑

0

βˆ’1

2∫ 𝛾(𝑠)2𝑑𝑠𝑑

0

).

Then under the new probability measure οΏ½ΜƒοΏ½, the stochastic process

𝑍�̃�(𝑑) = 𝑍𝑃(𝑑) + ∫ 𝛾(𝑠)𝑑𝑠𝑑

0

.

is a Brownian motion under οΏ½ΜƒοΏ½.

Remark

Suppose that a stochastic process 𝑆𝑑 satisfies

𝑑𝑆𝑑 = π‘Ž(𝑑, 𝑆𝑑)𝑑𝑑 + 𝑏(𝑑, 𝑆𝑑)𝑑𝑍𝑑𝑃,

where 𝑍𝑑𝑃 is the Brownian motion under 𝑃.

Suppose that the probability measure 𝑃 is changed to οΏ½ΜƒοΏ½, then the dynamics of the

process 𝑆𝑑 becomes

𝑑𝑆𝑑 = π‘Ž(𝑑, 𝑆𝑑)𝑑𝑑 + 𝑏(𝑑, 𝑆𝑑)𝑑 (𝑍𝑑�̃� βˆ’βˆ« 𝛾(𝑠)𝑑𝑠

𝑑

0

) = π‘Ž(𝑑, 𝑆𝑑)𝑑𝑑 + 𝑏(𝑑, 𝑆𝑑)[𝑑𝑍𝑑�̃� βˆ’ 𝛾(𝑑)𝑑𝑑]

β‡’ 𝑑𝑆𝑑 = [π‘Ž(𝑑, 𝑆𝑑) βˆ’ 𝛾(𝑑)𝑏(𝑑, 𝑆𝑑)]𝑑𝑑 + 𝑏(𝑑, 𝑆𝑑)𝑑𝑍𝑑�̃�.

(*Note: Remember that 𝛾(𝑑) is non-anticipative and the value is fixed up to time 𝑑).

Numeraire Invariance Theorem

Let 𝑁(𝑑) be a numeraire and assume that there is an equivalent probability measure 𝑄𝑁

such that

𝔼𝑄𝑁 [𝑆(𝑇)

𝑁(𝑇)|ℱ𝑑] =

𝑆(𝑑)

𝑁(𝑑).

Here, 𝑆(𝑑) is the price of an asset. Suppose that a contingent claim π‘Œ is attainable, then

we have

𝑀(𝑑)𝔼𝑄 [π‘Œ

𝑀(𝑇)|ℱ𝑑] = 𝑁(𝑑)𝔼

𝑄𝑁 [π‘Œ

𝑁(𝑇)|ℱ𝑑].

Here, 𝑄 is risk neutral probability measure and 𝑀(𝑑) = π‘’π‘Ÿπ‘‘ is the money market

account.