Suboptimality of Asian Executive Option

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    Suboptimality of Asian Executive Indexed

    Options

    Carole BernardPhelim Boyle

    Jit Seng Chen

    Actuarial Research Conference

    August 13, 2011

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    Outline

    1. Options Preliminaries

    2. Assumptions

    3. Asian Executive Indexed Option

    4. Cost-Efficiency

    5. Constructing a Cheaper Payoff

    6. True Cost Efficient Counterpart

    7. Numerical Results

    8. Stochastic Interest Rates

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    Options Preliminaries

    1 2 3 470

    75

    80

    85

    90

    95

    100

    105

    110

    115

    120

    125

    Time

    Price

    S1 = 100

    H1 = 110

    S2 = 75

    H2 = 80

    S3 = 120

    H3 = 100

    S4 = 80

    H4 = 110

    K= 90

    Sample Price Paths

    Stock, S

    Benchmark, H

    Strike, K

    S4 = 4

    S1S2S3S4 = 92.12, H4 =4

    H1H2H3H4 = 99.19

    European Call Option Payoff = max(S4 K, 0) = 0

    Asian Option Payoff = max(S4

    K, 0) = 2.12

    Asian Indexed Option Payoff = max(S4 H4, 0) = 0

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    Assumptions

    1. Black-Scholes market: Extension to Vasicek short rate

    2. Stock St and benchmark Ht driven by Brownian motions

    3. Existence of state-price process t

    4. Agents preferences depend only on the terminal distribution ofwealth

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    Asian Executive Indexed Option

    Asian Executive Indexed Option (AIO) proposed by Tian (2011):

    Averaging: Prevent stock price manipulation Indexing: Only reward out-performance More cost-effective than traditional stock options

    Provide stronger incentives to increase stock prices

    Construct a better payoff:

    Same features as the AIO

    Strictly cheaper Use the concept of cost-efficiency

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    Cost-Efficiency

    From Bernard, Boyle and Vanduffel (2011):

    Definition (1)

    The cost of a strategy with terminal payoff XT is given by

    c(XT) = EP[TXT]

    where the expectation is taken under the physical measure P.

    Intuition: T represents the price of a particular state

    Definition (2)

    A payoff is cost-efficient (CE) if any other strategy that generatesthe same distribution costs at least as much.

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    Cost-Efficiency

    Theorem (1)Let T be continuous. Define

    YT = F1XT

    (1 FT(T))

    as the cost-efficient counterpart (CEC) of the payoff XT. Then,YT is a CE payoff with the same distribution as XT and is almostsurely unique.

    Intuition: CEC is achieved by reshuffling the outcome of XT in

    each state in reverse order with T while preserving the originaldistribution

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    Constructing a Cheaper Payoff

    1. Apply Theorem 1 to each term of the AIO

    AT = max(ST HT, 0)

    to get

    AT

    = maxdS

    S1/

    3

    T dH

    H1/

    3

    T, 0

    2. It can be shown that: AT

    d=AT

    AT costs strictly less than AT

    AT inherits the desired features of AT, but comes at a cheaperprice

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    True Cost Efficient Counterpart

    True CEC

    AT = F

    1

    AT (1 FT(T))is estimated numerically

    Examples:

    1. Empirical cumulative distribution functions (CDFs) for eachpayoff in the base case 1

    2. Reshuffling of AT to AT and AT

    3. Order of AT, A and AT vs T

    4. Price of each payoff and the efficiency loss

    1K = 100, S0 = 100, r = 6%, S = 12%, I = 10%, S = 30%, I = 20%, = 0.75, qS = 2%,

    qI = 3%, T = 1

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    Numerical Results

    0 10 20 30 40 50 60 70 800

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    Payoffs

    Probability

    distribution

    Empirial CDFs ofAT, A

    T and AT

    AT

    A

    T

    AT

    Figure: Comparison of the CDFs of AT, A

    T andAT.

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    Numerical Results

    0 10 20 30 40 50 60 70 800

    10

    20

    30

    40

    50

    60

    70

    AT

    A T

    Plot of AT vs A

    T

    Figure: Reshuffling of outcomes ofAT to A

    T

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    Numerical Results

    0 10 20 30 40 50 60 70 800

    10

    20

    30

    40

    50

    60

    70

    AT

    AT

    Plot of AT vs AT

    Figure: Reshuffling of outcomes ofAT to AT

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    Numerical Results

    0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

    10

    20

    30

    40

    50

    60

    70

    T

    AT

    Plot of AT vs T

    Figure: Plot of outcomes ofAT vs T

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    Numerical Results

    0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

    10

    20

    30

    40

    50

    60

    70

    80

    T

    A T

    Plot of AT

    vs T

    Figure: Plot of outcomes of A

    T vs T

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    Numerical Results

    0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

    10

    20

    30

    40

    50

    60

    70

    T

    AT

    Plot of AT vs T

    Figure: Plot of outcomes of AT vs T

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    Numerical Results

    CaseAT

    AT

    AT

    VT VT Eff Loss VT Eff Loss

    Base Case 3.26 4.34 33% 4.36 34%r = 4% 2.96 4.37 48% 4.40 49%S = 8% 3.97 4.35 10% 4.36 10%

    I = 13% 3.26 4.34 33% 4.36 34%S = 35% 3.97 5.04 27% 5.07 28%I = 15% 3.27 4.34 33% 4.36 33% = 0.9 2.28 2.86 25% 2.87 26%

    qS = 1.5% 3.27 4.35 33% 4.37 34%

    qI = 2% 3.25 4.34 33% 4.36 34%

    Table: Prices and efficiency loss of AT and AT compared against ATacross different parameters.

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    Stochastic Interest Rates

    Extension to a market with Vasicek short rate:

    1. State price process expressed as a function of market variables2. Pricing formula for the AIO

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    Summary

    Reviewed the use of averaging and indexing in the context of

    executive compensation

    Constructed a strictly cheaper payoff with the same featuresas the AIO using cost-efficiency

    Numerical examples that illustrate reshuffling of payoffs and

    loss of efficiency Extension to the case of stochastic interest rates

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