A Delayed Option Pricing Formula (University of Manchester Probability Seminar)

Transcription

1 Southern Illinois University Carbondale OpenSIUC Miscellaneous (presentations, translations, interviews, etc) Department of Mathematics A Delayed Option Pricing Formula (University of Manchester Probability Seminar) Salah-Eldin A. Mohammed Southern Illinois University Carbondale, salah@sfde.math.siu.edu Follow this and additional works at: Part of the Mathematics Commons Invited Talk; Probability Seminar; School of Mathematics; University of Manchester, UK; November 14, 2007 Recommended Citation Mohammed, Salah-Eldin A., "A Delayed Option Pricing Formula (University of Manchester Probability Seminar)" (2007). Miscellaneous (presentations, translations, interviews, etc). Paper 4. This Article is brought to you for free and open access by the Department of Mathematics at OpenSIUC. It has been accepted for inclusion in Miscellaneous (presentations, translations, interviews, etc) by an authorized administrator of OpenSIUC. For more information, please contact opensiuc@lib.siu.edu.

2 A Delayed Option Pricing Formula Salah Mohammed November 14, 2007 Probability Seminar The University Manchester, UK A Delayed OptionPricing Formula p.1/79

3 Joint work with M. Arriojas, Y. Hu and G. Pap. A Delayed OptionPricing Formula p.2/79

4 Joint work with M. Arriojas, Y. Hu and G. Pap. Research supported by NSF Grants DMS and DMS A Delayed OptionPricing Formula p.2/79

5 Outline Get formula for pricing European options when stock price follows a non-linear stochastic delay (or functional) differential equation. A Delayed OptionPricing Formula p.3/79

6 Outline Get formula for pricing European options when stock price follows a non-linear stochastic delay (or functional) differential equation. Proposed model is sufficiently flexible to fit real market data, yet allows for a closed-form explicit representation of the option price during the last delay period before maturity. A Delayed OptionPricing Formula p.3/79

7 Outline Get formula for pricing European options when stock price follows a non-linear stochastic delay (or functional) differential equation. Proposed model is sufficiently flexible to fit real market data, yet allows for a closed-form explicit representation of the option price during the last delay period before maturity. Construction of an equivalent local martingale measure via successive backward conditioning. A Delayed OptionPricing Formula p.3/79

8 Outline Get formula for pricing European options when stock price follows a non-linear stochastic delay (or functional) differential equation. Proposed model is sufficiently flexible to fit real market data, yet allows for a closed-form explicit representation of the option price during the last delay period before maturity. Construction of an equivalent local martingale measure via successive backward conditioning. Model maintains the no-arbitrage property and completeness of the market. A Delayed OptionPricing Formula p.3/79

9 Outline Get formula for pricing European options when stock price follows a non-linear stochastic delay (or functional) differential equation. Proposed model is sufficiently flexible to fit real market data, yet allows for a closed-form explicit representation of the option price during the last delay period before maturity. Construction of an equivalent local martingale measure via successive backward conditioning. Model maintains the no-arbitrage property and completeness of the market. Hedging strategy. A Delayed OptionPricing Formula p.3/79

10 Introduction Black and Scholes model for pricing European options is based on the assumption of constant volatility: A Delayed OptionPricing Formula p.4/79

11 Introduction Black and Scholes model for pricing European options is based on the assumption of constant volatility: But empirical evidence shows that volatility depends on time and chance: Smiles and frowns. A Delayed OptionPricing Formula p.4/79

12 Introduction Black and Scholes model for pricing European options is based on the assumption of constant volatility: But empirical evidence shows that volatility depends on time and chance: Smiles and frowns. Need better ways of understanding stock dynamics. A Delayed OptionPricing Formula p.4/79

13 Introduction Black and Scholes model for pricing European options is based on the assumption of constant volatility: But empirical evidence shows that volatility depends on time and chance: Smiles and frowns. Need better ways of understanding stock dynamics. Proposal: Allow volatility to depend on the history of the stock price: A Delayed OptionPricing Formula p.4/79

14 Introduction Black and Scholes model for pricing European options is based on the assumption of constant volatility: But empirical evidence shows that volatility depends on time and chance: Smiles and frowns. Need better ways of understanding stock dynamics. Proposal: Allow volatility to depend on the history of the stock price: Predictions about the evolution of financial variables take into account the knowledge of their past. A Delayed OptionPricing Formula p.4/79

15 Introduction Black and Scholes model for pricing European options is based on the assumption of constant volatility: But empirical evidence shows that volatility depends on time and chance: Smiles and frowns. Need better ways of understanding stock dynamics. Proposal: Allow volatility to depend on the history of the stock price: Predictions about the evolution of financial variables take into account the knowledge of their past. Objective: To derive an option pricing formula under stock-dynamics with finite memory. (Theorem 4). A Delayed OptionPricing Formula p.4/79

16 Definitions An option is a contract giving the owner the right to buy or sell an asset, in accordance with certain conditions and within a specified period of time. A Delayed OptionPricing Formula p.5/79

17 Definitions An option is a contract giving the owner the right to buy or sell an asset, in accordance with certain conditions and within a specified period of time. A European call option gives its owner the right to buy a share of stock at the maturity or expiration date of the option, for a specified exercise price. A Delayed OptionPricing Formula p.5/79

18 Definitions An option is a contract giving the owner the right to buy or sell an asset, in accordance with certain conditions and within a specified period of time. A European call option gives its owner the right to buy a share of stock at the maturity or expiration date of the option, for a specified exercise price. The option is exercised when the exercise price is paid. A Delayed OptionPricing Formula p.5/79

19 Definitions An option is a contract giving the owner the right to buy or sell an asset, in accordance with certain conditions and within a specified period of time. A European call option gives its owner the right to buy a share of stock at the maturity or expiration date of the option, for a specified exercise price. The option is exercised when the exercise price is paid. European call options can only be exercised at the maturity date. A Delayed OptionPricing Formula p.5/79

20 Delayed Stock Model Consider a stock whose price S(t) at any time t satisfies the following stochastic delay differential equation (sdde): A Delayed OptionPricing Formula p.6/79

21 Delayed Stock Model Consider a stock whose price S(t) at any time t satisfies the following stochastic delay differential equation (sdde): ds(t) = h(t, S(t a))s(t) dt + g(s(t b))s(t) dw (t), t [0, T ] S(t) = ϕ(t), t [ L, 0] (1) on a probability space (Ω, F, P ) with a filtration (F t ) 0 t T satisfying the usual conditions. A Delayed OptionPricing Formula p.6/79

22 Delayed Stock Model-contd A Delayed OptionPricing Formula p.7/79

23 Delayed Stock Model-contd In Drift: Continuous function h : R + R R. A Delayed OptionPricing Formula p.7/79

24 Delayed Stock Model-contd In Drift: Continuous function h : R + R R. Volatility function: g : R R is continuous. A Delayed OptionPricing Formula p.7/79

25 Delayed Stock Model-contd In Drift: Continuous function h : R + R R. Volatility function: g : R R is continuous. Maximum delay: L := max{a, b}, positive delays a, b. C([ L, 0], R) := Banach space of continuous functions [ L, 0] R given the sup norm. A Delayed OptionPricing Formula p.7/79

26 Delayed Stock Model-contd In Drift: Continuous function h : R + R R. Volatility function: g : R R is continuous. Maximum delay: L := max{a, b}, positive delays a, b. C([ L, 0], R) := Banach space of continuous functions [ L, 0] R given the sup norm. Initial process: ϕ : Ω C([ L, 0], R) is F 0 -measurable with respect to the Borel σ-algebra of C([ L, 0], R). A Delayed OptionPricing Formula p.7/79

27 Delayed Stock Model-contd In Drift: Continuous function h : R + R R. Volatility function: g : R R is continuous. Maximum delay: L := max{a, b}, positive delays a, b. C([ L, 0], R) := Banach space of continuous functions [ L, 0] R given the sup norm. Initial process: ϕ : Ω C([ L, 0], R) is F 0 -measurable with respect to the Borel σ-algebra of C([ L, 0], R). Brownian motion: W -one-dimensional standard, adapted to (F t ) 0 t T. A Delayed OptionPricing Formula p.7/79

28 Feasibility of Delayed Stock Model Model is feasible: Admits pathwise unique solution such that S(t) > 0 almost surely for all t 0 whenever the initial path ϕ(t) > 0 for all t [ L, 0]. A Delayed OptionPricing Formula p.8/79

29 Feasibility of Delayed Stock Model Model is feasible: Admits pathwise unique solution such that S(t) > 0 almost surely for all t 0 whenever the initial path ϕ(t) > 0 for all t [ L, 0]. Hypotheses (E): (i) h : R + R R is continuous. A Delayed OptionPricing Formula p.8/79

30 Feasibility of Delayed Stock Model Model is feasible: Admits pathwise unique solution such that S(t) > 0 almost surely for all t 0 whenever the initial path ϕ(t) > 0 for all t [ L, 0]. Hypotheses (E): (i) h : R + R R is continuous. (ii) g : R R is continuous. A Delayed OptionPricing Formula p.8/79

31 Feasibility of Delayed Stock Model Model is feasible: Admits pathwise unique solution such that S(t) > 0 almost surely for all t 0 whenever the initial path ϕ(t) > 0 for all t [ L, 0]. Hypotheses (E): (i) h : R + R R is continuous. (ii) g : R R is continuous. (iii) Delays a and b are positive and fixed. A Delayed OptionPricing Formula p.8/79

32 Theorem 1 Assume Hypotheses (E). Then the delayed stock model ds(t) = h(t, S(t a))s(t) dt + g(s(t b))s(t) dw (t), t [0, T ] S(t) = ϕ(t), t [ L, 0] (1) admits a pathwise unique solution S for a given F 0 - measurable initial process ϕ : Ω C([ L, 0], R). If ϕ(0) > 0 a.s., then S(t) > 0 a.s. for all t 0. A Delayed OptionPricing Formula p.9/79

33 Proof of Theorem 1 A Delayed OptionPricing Formula p.10/79

34 Proof of Theorem 1 Define minimum delay l := min{a, b} > 0. Let t [0, l]. The delayed stock model gives ds(t) = S(t)[h(t, ϕ(t a)) dt + g(ϕ(t b)) dw (t)] t [0, l] S(0) = ϕ(0). (1) A Delayed OptionPricing Formula p.10/79

35 Proof of Theorem 1 Cont d Define the semimartingale N(t) := t 0 h(u, ϕ(u a)) du + t 0 g(ϕ(u b)) dw (u), for t [0, l]. A Delayed OptionPricing Formula p.11/79

36 Proof of Theorem 1 Cont d Define the semimartingale N(t) := t 0 h(u, ϕ(u a)) du + t 0 g(ϕ(u b)) dw (u), for t [0, l]. Its quadratic variation is given by [N, N](t) = t 0 g(ϕ(u b))2 du, t [0, l]. A Delayed OptionPricing Formula p.11/79

37 Proof of Theorem 1 Cont d Define the semimartingale N(t) := t 0 h(u, ϕ(u a)) du + t 0 g(ϕ(u b)) dw (u), for t [0, l]. Its quadratic variation is given by [N, N](t) = t 0 g(ϕ(u b))2 du, t [0, l]. Then (1) becomes ds(t) = S(t) dn(t), t > 0, S(0) = ϕ(0), with the unique solution: A Delayed OptionPricing Formula p.11/79

38 Proof of Theorem 1 Cont d for t [0, l]. S(t) = ϕ(0) exp{n(t) 1 [N, N](t)}, 2 { t = ϕ(0) exp h(u, ϕ(u a)) du t 0 t 0 g(ϕ(u b)) dw (u) } g(ϕ(u b)) 2 du, This implies that S(t) > 0 almost surely for all t [0, l], when ϕ(0) > 0 a.s.. A Delayed OptionPricing Formula p.12/79

39 Proof of Theorem 1 Cont d Similarly, since S(l) > 0, then S(t) > 0 for all t [l, 2l] a.s.. Therefore S(t) > 0 for all t 0 a.s., by induction using forward steps of lengths l. A Delayed OptionPricing Formula p.13/79

40 Proof of Theorem 1 Cont d Similarly, since S(l) > 0, then S(t) > 0 for all t [l, 2l] a.s.. Therefore S(t) > 0 for all t 0 a.s., by induction using forward steps of lengths l. Above argument also gives existence and pathwise uniqueness of the strong solution to the delayed stock model. A Delayed OptionPricing Formula p.13/79

41 Remark 1 In the delayed stock model, we need only require ϕ(0) 0 (or ϕ(0) > 0) to conclude that a.s. S(t) 0 for all t 0 (or S(t) > 0 for all t 0, resp.). A Delayed OptionPricing Formula p.14/79

42 An Extension of the Model Another feasible model for the stock price is ds(t) = f(t, S t a )S(t) dt + g(s(t b))s(t) dw (t), t [0, T ], S(t) = ϕ(t), t [ L, 0], A Delayed OptionPricing Formula p.15/79

43 An Extension of the Model Another feasible model for the stock price is ds(t) = f(t, S t a )S(t) dt + g(s(t b))s(t) dw (t), S(t) = ϕ(t), t [ L, 0], t [0, T ], where f : [0, T ] C([ L, T ], R) R is a continuous functional; and S t C([ L, T ], R), t [ L, T ], is defined by for S C([ L, T ], R). S t (s) := S(t s), s [ L, T ], A Delayed OptionPricing Formula p.15/79

44 The Delayed Market A Delayed OptionPricing Formula p.16/79

45 The Delayed Market Consider a market consisting of: A Delayed OptionPricing Formula p.16/79

46 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). A Delayed OptionPricing Formula p.16/79

47 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). a single stock with price S(t) at time t satisfying the delayed stock model (1) with ϕ(0) > 0 a.s.. A Delayed OptionPricing Formula p.16/79

48 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). a single stock with price S(t) at time t satisfying the delayed stock model (1) with ϕ(0) > 0 a.s.. Consider an option, written on the stock, with maturity at some future time T > 0 and exercise price K. Assume: A Delayed OptionPricing Formula p.16/79

49 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). a single stock with price S(t) at time t satisfying the delayed stock model (1) with ϕ(0) > 0 a.s.. Consider an option, written on the stock, with maturity at some future time T > 0 and exercise price K. Assume: No transaction costs. A Delayed OptionPricing Formula p.16/79

50 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). a single stock with price S(t) at time t satisfying the delayed stock model (1) with ϕ(0) > 0 a.s.. Consider an option, written on the stock, with maturity at some future time T > 0 and exercise price K. Assume: No transaction costs. Stock pays no dividends. A Delayed OptionPricing Formula p.16/79

51 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). a single stock with price S(t) at time t satisfying the delayed stock model (1) with ϕ(0) > 0 a.s.. Consider an option, written on the stock, with maturity at some future time T > 0 and exercise price K. Assume: No transaction costs. Stock pays no dividends. Positive delays a, b; h, g continuous. A Delayed OptionPricing Formula p.16/79

52 The Delayed Market Consider a market consisting of: a riskless asset (e.g., a bond or bank account) B(t) with rate of return r 0 (i.e., B(t) = exp{rt} ). a single stock with price S(t) at time t satisfying the delayed stock model (1) with ϕ(0) > 0 a.s.. Consider an option, written on the stock, with maturity at some future time T > 0 and exercise price K. Assume: No transaction costs. Stock pays no dividends. Positive delays a, b; h, g continuous. g(v) 0 whenever v 0. A Delayed OptionPricing Formula p.16/79

53 Delayed Market Cont d A Delayed OptionPricing Formula p.17/79

54 Delayed Market Cont d Main objectives: A Delayed OptionPricing Formula p.17/79

55 Delayed Market Cont d Main objectives: Derive a formula for the fair price V (t) of the option on the delayed stock, at any time t < T. A Delayed OptionPricing Formula p.17/79

56 Delayed Market Cont d Main objectives: Derive a formula for the fair price V (t) of the option on the delayed stock, at any time t < T. Obtain an equivalent local martingale measure (via Girsanov s theorem). A Delayed OptionPricing Formula p.17/79

57 Delayed Market Cont d Main objectives: Derive a formula for the fair price V (t) of the option on the delayed stock, at any time t < T. Obtain an equivalent local martingale measure (via Girsanov s theorem). Establish completeness and no-arbitrage property of the market. A Delayed OptionPricing Formula p.17/79

58 Delayed Market Cont d Main objectives: Derive a formula for the fair price V (t) of the option on the delayed stock, at any time t < T. Obtain an equivalent local martingale measure (via Girsanov s theorem). Establish completeness and no-arbitrage property of the market. Obtain a hedging strategy. A Delayed OptionPricing Formula p.17/79

59 Discounted Stock Let S(t) := S(t) B(t) = e rt S(t), t [0, T ], be the discounted stock price. Then by the product rule: d S(t) = e rt ds(t) + S(t)( re rt S(t)[ ) dt {h(t, } = S(t a)) r dt +g ( S(t b) ) ] dw (t). A Delayed OptionPricing Formula p.18/79

60 Discounted Stock Cont d Define Ŝ(t) := t 0 + { h(u, S(u a)) r } du t 0 g ( S(u b) ) dw (u), for t [0, T ]. A Delayed OptionPricing Formula p.19/79

61 Discounted Stock Cont d Define Ŝ(t) := t 0 + { h(u, S(u a)) r } du t 0 g ( S(u b) ) dw (u), for t [0, T ]. Then d S(t) = S(t) dŝ(t), 0 < t < T. (2) A Delayed OptionPricing Formula p.19/79

62 Discounted Stock Cont d Since S(0) = ϕ(0), then S(t) = ϕ(0) + t 0 S(u) dŝ(u), t [0, T ]. (3) A Delayed OptionPricing Formula p.20/79

63 Discounted Stock Cont d Since S(0) = ϕ(0), then S(t) = ϕ(0) + t 0 S(u) dŝ(u), t [0, T ]. (3) To establish an equivalent local martingale measure, recall Girsanov s theorem: A Delayed OptionPricing Formula p.20/79

64 Theorem 2 (Girsanov) A Delayed OptionPricing Formula p.21/79

65 Theorem 2 (Girsanov) Let W (t), t [0, T ], be a standard Wiener process on (Ω, F, P ). Let Σ be a predictable process such that T 0 Σ(u) 2 du < a.s.. Define { t ϱ(t) := exp Σ(u) dw (u) 1 t } Σ(u) 2 du, 2 0 for t [0, T ]. Suppose that E P (ϱ(t )) = 1, where E P denotes expectation with respect to the probability measure P. Define the probability measure Q on (Ω, F) by dq := ϱ(t ) dp. 0 A Delayed OptionPricing Formula p.21/79

66 Theorem 2 Cont d Then the process Ŵ (t) := W (t) t 0 Σ(u) du, t [0, T ], is a standard Wiener process under the measure Q. A Delayed OptionPricing Formula p.22/79

67 Backward Conditioning Apply Girsanov s theorem with the process Σ(u) := {h(u, S(u a)) r} g ( S(u b) ), u [0, T ]. A Delayed OptionPricing Formula p.23/79

68 Backward Conditioning Apply Girsanov s theorem with the process Σ(u) := {h(u, S(u a)) r} g ( S(u b) ), u [0, T ]. The hypothesis on g implies that Σ is well-defined, since by Theorem 1, S(t) > 0 for all t [0, T ] a.s.. Clearly Σ(t), t [0, T ], is a predictable process. A Delayed OptionPricing Formula p.23/79

69 Backward Conditioning Apply Girsanov s theorem with the process Σ(u) := {h(u, S(u a)) r} g ( S(u b) ), u [0, T ]. The hypothesis on g implies that Σ is well-defined, since by Theorem 1, S(t) > 0 for all t [0, T ] a.s.. Clearly Σ(t), t [0, T ], is a predictable process. The process S(t), t [0, T ], is a.s. bounded because it is sample continuous. The hypothesis on g implies that 1/g(v), v (0, ), is bounded on bounded intervals. Thus T 0 Σ(u) 2 du < a.s.. A Delayed OptionPricing Formula p.23/79

70 Backward Conditioning Cont d Remains to check the integrability condition in Girsanov s theorem. A Delayed OptionPricing Formula p.24/79

71 Backward Conditioning Cont d Remains to check the integrability condition in Girsanov s theorem. Let l := min{a, b}, minimum delay. A Delayed OptionPricing Formula p.24/79

72 Backward Conditioning Cont d Remains to check the integrability condition in Girsanov s theorem. Let l := min{a, b}, minimum delay. Set F t := F 0 for t 0. A Delayed OptionPricing Formula p.24/79

73 Backward Conditioning Cont d Remains to check the integrability condition in Girsanov s theorem. Let l := min{a, b}, minimum delay. Set F t := F 0 for t 0. Then Σ(u), u [0, T ], is measurable with respect to the σ-algebra F T l. A Delayed OptionPricing Formula p.24/79

74 Backward Conditioning Cont d Remains to check the integrability condition in Girsanov s theorem. Let l := min{a, b}, minimum delay. Set F t := F 0 for t 0. Then Σ(u), u [0, T ], is measurable with respect to the σ-algebra F T l. Hence, the stochastic integral T T l Σ(u) dw (u) conditioned on F T l has a normal distribution with mean zero and variance T T l Σ(u)2 du. A Delayed OptionPricing Formula p.24/79

75 Backward Conditioning Cont d By normality (e.g. moment generating function): { T ) E P (exp Σ(u) dw (u)} F T l T l { 1 T } = exp Σ(u) 2 du 2 a.s.. T l A Delayed OptionPricing Formula p.25/79

76 Backward Conditioning Cont d By normality (e.g. moment generating function): { T ) E P (exp Σ(u) dw (u)} F T l T l { 1 T } = exp Σ(u) 2 du 2 a.s.. Hence { T E P (exp Σ(u)dW (u) 1 T l 2 T l T T l Σ(u) 2 du} F T l = 1, a.s.. ) A Delayed OptionPricing Formula p.25/79

77 Backward Conditioning Cont d This implies: { T E P (exp a.s.. = exp 0 { T l T Σ(u) dw (u) 1 Σ(u) du} 2 F T l 2 0 Σ(u) dw (u) 1 T l } Σ(u) 2 du ) A Delayed OptionPricing Formula p.26/79

78 Backward Conditioning Cont d Let k to be a positive integer such that 0 T kl l. Successive conditioning using backward steps of length l, and induction give: { T E P (exp Σ(u) dw (u) 1 T ) Σ(u) du} 2 F T kl { T kl = exp Σ(u) dw (u) 1 T kl } Σ(u) 2 du 2 a.s A Delayed OptionPricing Formula p.27/79

79 Backward Conditioning Cont d Take conditional expectation with respect to F 0 on both sides of above equation: ( { T E P exp Σ(u) dw (u) 0 1 T } ) Σ(u) 2 du F 0 2 ( { 0 T kl = E P exp Σ(u) dw (u) 0 1 T kl } ) Σ(u) 2 du F 0 = 1 2 a.s.. 0 A Delayed OptionPricing Formula p.28/79

80 Backward Conditioning Cont d Taking the expectation of the above equation, we get E P (ϱ(t )) = 1 where A Delayed OptionPricing Formula p.29/79

81 Backward Conditioning Cont d Taking the expectation of the above equation, we get E P (ϱ(t )) = 1 where ϱ(t ) := exp { T 0 {h(u, S(u a)) r} g ( S(u b) ) dw (u) 1 T h(u, S(u a)) r 2 g ( S(u b) ) 0 2 du a.s.. A Delayed OptionPricing Formula p.29/79

82 Martingale Measure Therefore, the Girsanov theorem (Theorem 2) applies and the process Ŵ (t) := W (t)+ t 0 {h(u, S(u a)) r} g ( S(u b) ) du, t [0, T ], is a standard Wiener process under the measure Q defined by: dq := ϱ(t ) dp. A Delayed OptionPricing Formula p.30/79

83 Martingale Measure Cont d Since Ŝ(t) = t 0 g ( S(u b) ) dŵ (u), t [0, T ], (4) then Ŝ(t), t [0, T ], is a continuous Q-local martingale. A Delayed OptionPricing Formula p.31/79

84 Martingale Measure Cont d Since Ŝ(t) = t 0 g ( S(u b) ) dŵ (u), t [0, T ], (4) then Ŝ(t), t [0, T ], is a continuous Q-local martingale. By the representation S(t) = ϕ(0) + t 0 S(u) dŝ(u), t [0, T ], (3) the discounted stock price S(t), t [0, T ], is also a continuous Q-local martingale. A Delayed OptionPricing Formula p.31/79

85 No Aribtrage I.e. Q is an equivalent local martingale measure. A Delayed OptionPricing Formula p.32/79

86 No Aribtrage I.e. Q is an equivalent local martingale measure. By well-known results on trading strategies (e.g., Theorem 7.1 in [K.K]), it follows that the market consisting of {B(t), S(t) : t [0, T ]} satisfies the no-arbitrage property: A Delayed OptionPricing Formula p.32/79

87 No Aribtrage I.e. Q is an equivalent local martingale measure. By well-known results on trading strategies (e.g., Theorem 7.1 in [K.K]), it follows that the market consisting of {B(t), S(t) : t [0, T ]} satisfies the no-arbitrage property: There is no admissible self-financing strategy which gives an arbitrage opportunity. A Delayed OptionPricing Formula p.32/79

88 Completeness Next get completeness of the market {B(t), S(t) : t [0, T ]}. A Delayed OptionPricing Formula p.33/79

89 Completeness Next get completeness of the market {B(t), S(t) : t [0, T ]}. By proof of Theorem 1, the solution of the delayed stock model (1) satisfies: { t S(t) =ϕ(0) exp g ( S(u b) ) dw (u) + t a.s. for t [0, T ]. 0 0 h(u, S(u a)) du 1 2 t 0 g ( S(u b) ) 2 du } A Delayed OptionPricing Formula p.33/79

90 Completeness Cont d Hence, S(t) =ϕ(0) exp { t g ( S(u b) ) dŵ (u) t 0 g ( S(u b) ) 2 du } (5) for t [0, T ]. A Delayed OptionPricing Formula p.34/79

91 Completeness Cont d By definitions of S, Ŵ, Ŝ and equation (2), then for t 0, Ft S = F S t = F Ŵt = Ft W, the σ-algebras generated by {S(u) : u t}, { S(u) : u t}, {Ŵ (u) : u t}, {W (u) : u t}, respectively. (Clearly, Ft W F t.) A Delayed OptionPricing Formula p.35/79

92 Completeness Cont d By definitions of S, Ŵ, Ŝ and equation (2), then for t 0, Ft S = F S t = F Ŵt = Ft W, the σ-algebras generated by {S(u) : u t}, { S(u) : u t}, {Ŵ (u) : u t}, {W (u) : u t}, respectively. (Clearly, Ft W F t.) Let X be a contingent claim, viz. an integrable non-negative FT S -measurable random variable. Consider the Q-martingale M(t) := E Q (e rt X Ft S ) = E Q (e rt X F Ŵt ), for t [0, T ]. A Delayed OptionPricing Formula p.35/79

93 Completeness Cont d By the martingale representation theorem, there exists an (F Ŵt )-predictable process h 0 (t), t [0, T ], such that T 0 h 0 (u) 2 du < a.s., and M(t) = E Q (e rt X) + t 0 h 0 (u) dŵ (u), t [0, T ]. A Delayed OptionPricing Formula p.36/79

94 Completeness Cont d Combining the two relations d S(t) = S(t) dŝ(t), dŝ(t) = g( S(t b) ) dŵ (t), gives: d S(t) = S(t)g ( S(t b) ) dŵ (u), t [0, T ]. A Delayed OptionPricing Formula p.37/79

95 Completeness Cont d Combining the two relations d S(t) = S(t) dŝ(t), dŝ(t) = g( S(t b) ) dŵ (t), gives: d S(t) = S(t)g ( S(t b) ) dŵ (u), t [0, T ]. Define π S (t) := h 0 (t) S(t)g ( S(t b) ), π B (t) := M(t) π S (t) S(t) for t [0, T ]. A Delayed OptionPricing Formula p.37/79

96 Completeness Cont d Consider the strategy {(π B (t), π S (t)) : t [0, T ]} which consists of holding π S (t) units of the stock and π B (t) units of the bond at time t. The value of the portfolio at any time t [0, T ] is: V (t) := π B (t)e rt + π S (t)s(t) = e rt M(t). A Delayed OptionPricing Formula p.38/79

97 Completeness Cont d Consider the strategy {(π B (t), π S (t)) : t [0, T ]} which consists of holding π S (t) units of the stock and π B (t) units of the bond at time t. The value of the portfolio at any time t [0, T ] is: V (t) := π B (t)e rt + π S (t)s(t) = e rt M(t). By the product rule and the definition of the strategy {(π B (t), π S (t)) : t [0, T ]}, get dv (t) = e rt dm(t) + M(t)d(e rt ) = π B (t)d(e rt ) + π S (t)ds(t), for t [0, T ]. A Delayed OptionPricing Formula p.38/79

98 Completeness Cont d Hence, {(π B (t), π S (t)) : t [0, T ]} is a self-financing strategy. Moreover, V (T ) = e rt M(T ) = X a.s.. Therefore, the contingent claim X is attainable; thus the market {B(t), S(t) : t [0, T ]} is complete: (every contingent claim is attainable). A Delayed OptionPricing Formula p.39/79

99 Completeness Cont d Hence, {(π B (t), π S (t)) : t [0, T ]} is a self-financing strategy. Moreover, V (T ) = e rt M(T ) = X a.s.. Therefore, the contingent claim X is attainable; thus the market {B(t), S(t) : t [0, T ]} is complete: (every contingent claim is attainable). For the augmented market {B(t), S(t), X : t [0, T ]} to satisfy the no-arbitrage property, the price of the claim X must be V (t) = e r(t t) E Q (X F S t ) at each t [0, T ] a.s. See, e.g., [B.R] or Theorem 9.2 in [K.K]. A Delayed OptionPricing Formula p.39/79

100 Delayed Option Pricing Formula Summarize above discussion in the following formula for the fair price V (t) of an option on the delayed stock. A Delayed OptionPricing Formula p.40/79

101 Theorem 3 Suppose that the stock price S is given by the delayed stock model, where ϕ(0) > 0 and g satisfies the given hypotheses. Let T be the maturity time of an option (contingent claim) on the stock with payoff function X, i.e., X is an FT S -measurable non-negative integrable random variable. Then at any time t [0, T ], the fair price V (t) of the option is given by the formula V (t) = e r(t t) E Q (X F S t ), (6) A Delayed OptionPricing Formula p.41/79

102 Theorem 3 Cont d where Q denotes the probability measure on (Ω, F) defined by dq := ϱ(t ) dp with { t {h(u, S(u a)) r} ϱ(t) := exp g ( S(u b) ) dw (u) for t [0, T ] t 0 h(u, S(u a)) r g ( S(u b) ) 2 du A Delayed OptionPricing Formula p.42/79

103 Theorem 3 Cont d The measure Q is a local martingale measure and the market is complete. Moreover, there is an adapted and square integrable process h 0 (u), u [0, T ] such that E Q (e rt X F S t ) = E Q (e rt X) + t 0 h 0 (u) dŵ (u), for t [0, T ],where given by Ŵ is a standard Q-Wiener process A Delayed OptionPricing Formula p.43/79

104 Theorem 3 Cont d t Ŵ (t) := W (t)+ 0 {h(u, S(u a)) r} g ( S(u b) ) du, t [0, T ], The hedging strategy is given by π S (t) := h 0 (t) S(t)g ( S(t b) ), π B (t) := M(t) π S (t) S(t), (7) for t [0, T ]. A Delayed OptionPricing Formula p.44/79

105 Delayed B-S Formula The following result is a consequence of Theorem 3. It gives a Black-Scholes-type formula for the value of a European option on the stock at times prior to maturity. A Delayed OptionPricing Formula p.45/79

106 Delayed B-S Formula The following result is a consequence of Theorem 3. It gives a Black-Scholes-type formula for the value of a European option on the stock at times prior to maturity. Formula is explicit during last delay period before maturity, or when delay is larger than maturity interval. A Delayed OptionPricing Formula p.45/79

107 Theorem 4 Assume the conditions of Theorem 3. Let V (t) be the fair price of a European call option written on the stock S with exercise price K and maturity time T. Let ϕ denote the standard normal distribution function: ϕ(x) := 1 2π x e u2 /2 du, x R. Then for all t [T l, T ] (where l := min{a, b}), V (t) is given by V (t) = S(t)ϕ(β + (t)) Ke r(t t) ϕ(β (t)), (8) A Delayed OptionPricing Formula p.46/79

108 Theorem 4 Cont d where β ± (t) := log S(t) K + T t T t ( r ± 1 2 g(s(u b))2) du g(s(u b)) 2 du. If T > l and t < T l, then ( V (t) = e rt E Q (H S(T l), 1 2 T T l T T l g ( S(u b) ) 2 du, g ( S(u b) ) ) ) 2 du F t (9) A Delayed OptionPricing Formula p.47/79

109 Theorem 4 Cont d where H is given by H(x, m, σ 2 ) := xe m+σ2 /2 ϕ(α 1 (x, m, σ)) Ke rt ϕ(α 2 (x, m, σ)), and α 1 (x, m, σ) := 1 σ [ log ( x K ) + rt + m + σ 2 ], α 2 (x, m, σ) := 1 σ for σ, x R +, m R. [ log ( x K ) ] + rt + m, A Delayed OptionPricing Formula p.48/79

110 Theorem 4 Cont d The hedging strategy is given by π S (t) = ϕ(β + (t)), π B (t) = Ke rt ϕ(β (t)), (10) for t [T l, T ]. A Delayed OptionPricing Formula p.49/79

111 Remarks 2 If g(x) = 1 for all x R + then equation (8) reduces to the classical Black and Scholes formula. A Delayed OptionPricing Formula p.50/79

112 Remarks 2 If g(x) = 1 for all x R + then equation (8) reduces to the classical Black and Scholes formula. In contrast with the classical (non-delayed) Black and Scholes formula, the fair price V (t) in the delayed model in Theorem 4 depends not only on the stock price S(t) at the present time t, but also on the whole segment {S(v) : v [t b, T b]}. ([t b, T b] [0, t] since t T l and l b.) A Delayed OptionPricing Formula p.50/79

113 Proof of Theorem 4 Consider a European call option in the above market with exercise price K and maturity time T. Taking X = (S(T ) K) + in Theorem 3, the fair price V (t) of the option is given by V (t) = e r(t t) E Q ( ( S(T ) K ) + Ft ) = e rt E Q ( ( S(T ) Ke rt ) + Ft ), (11) at any time t [0, T ]. A Delayed OptionPricing Formula p.51/79

114 Proof of Theorem 4 Cont d We now derive an explicit formula for the option price V (t) at any time t [T l, T ]. The representation (5) of S(t) implies: S(T ) = S(t) exp { T t g ( S(u b) ) dŵ (u) 1 2 T t g ( S(u b) ) 2 du } for all t [0, T ]. Clearly S(t) is F t -measurable. If t [T l, T ], then 1 2 F t -measurable. T t g ( S(u b) ) 2 du is also A Delayed OptionPricing Formula p.52/79

115 Proof of Theorem 4 Cont d Furthermore, when conditioned on F t, the distribution of T t g ( S(u b) ) dŵ (u) under Q is the same as that of σξ, where ξ is a Gaussian N(0, 1)-distributed random variable, and σ 2 = T t g ( S(u b) ) 2 du. Consequently, the fair price at time t is given by ( V (t) = e rt H S(t), 1 T g ( S(u b) ) 2 du, 2 t T g ( S(u b) ) ) 2 du, t A Delayed OptionPricing Formula p.53/79

116 Proof of Theorem 4 Cont d where H(x, m, σ 2 ) := E Q (xe m+σξ Ke rt ) +, for σ, x R +, m R. Now, an elementary computation yields the following: H(x, m, σ 2 ) = xe m+σ2 /2 ϕ(α 1 (x, m, σ)) Ke rt ϕ(α 2 (x, m, σ)). A Delayed OptionPricing Formula p.54/79

117 Proof of Theorem 4 Cont d Therefore, V (t) takes the form: V (t) = S(t)ϕ(β + ) Ke r(t t) ϕ(β ), (12) where β ± = log S(t) K + T t T t ( r ± 1 2 g(s(u b))2) du g(s(u b)) 2 du. A Delayed OptionPricing Formula p.55/79

118 Proof of Theorem 4 Cont d For T > l and t < T l, from the representation (5) of S(t), we have S(T ) = S(T l) exp { T T l g ( S(u b) ) dŵ (u) 1 2 T T l g ( S(u b) ) 2 du }. A Delayed OptionPricing Formula p.56/79

119 Proof of Theorem 4 Cont d Consequently, the option price at time t with t < T l is given by V (t) = e rt E Q (H ( 1 S(T l), 2 T T l T T l g ( S(u b) ) 2 du, g ( S(u b) ) ) ) 2 du F t. A Delayed OptionPricing Formula p.57/79

120 Proof of Theorem 4 Cont d Consequently, the option price at time t with t < T l is given by V (t) = e rt E Q (H ( 1 S(T l), 2 T T l T T l g ( S(u b) ) 2 du, g ( S(u b) ) ) ) 2 du F t. To calculate the hedging strategy for t [T l, T ], it suffices to use an idea from [B.R], pages This completes the proof of the theorem. A Delayed OptionPricing Formula p.57/79

121 Remark 3 During last delay period [T l, T ], it is possible to rewrite the option price V (t), t [T l, T ] in terms of the solution of a random Black-Scholes pde of the form F (t, x) t = 1 2 g(s(t b))2 x 2 2 F (t, x) F (t, x) rx x 2 x + rf (t, x), 0 < t < T F (T, x) = (x K) +, x > 0. (13) A Delayed OptionPricing Formula p.58/79

122 Remark 3 During last delay period [T l, T ], it is possible to rewrite the option price V (t), t [T l, T ] in terms of the solution of a random Black-Scholes pde of the form F (t, x) t = 1 2 g(s(t b))2 x 2 2 F (t, x) F (t, x) rx x 2 x + rf (t, x), 0 < t < T F (T, x) = (x K) +, x > 0. (13) Above time-dependent random final-value problem admits a unique (F t ) t 0 -adapted random field F (t, x). A Delayed OptionPricing Formula p.58/79

123 Remark 3 Cont d Using the classical Itô-Ventzell formula ([Kun]) and (6) of Theorem 3, it can be shown that V (t) = e r(t t) F (t, S(t)), t [T b, T ]. A Delayed OptionPricing Formula p.59/79

124 Remark 3 Cont d Using the classical Itô-Ventzell formula ([Kun]) and (6) of Theorem 3, it can be shown that V (t) = e r(t t) F (t, S(t)), t [T b, T ]. Note that the above representation is no longer valid if t T b, because in this range, the solution F of the final-value problem (9) is anticipating with respect to the filtration (F t ) t 0. A Delayed OptionPricing Formula p.59/79

125 A Stock Model with Variable Delay Consider an alternative model for the stock price dynamics with variable delay. A Delayed OptionPricing Formula p.60/79

126 A Stock Model with Variable Delay Consider an alternative model for the stock price dynamics with variable delay. Throughout this section, suppose h is a given fixed positive number. Denote t := kh if kh t < (k + 1)h. A Delayed OptionPricing Formula p.60/79

127 A Stock Model with Variable Delay Consider an alternative model for the stock price dynamics with variable delay. Throughout this section, suppose h is a given fixed positive number. Denote t := kh if kh t < (k + 1)h. Suppose market consist of a riskless asset ξ with a variable (deterministic) continuous rate of return λ, and a stock S satisfying sdde } dξ(t) = λ(t)ξ(t) dt ds(t) = f(t, S( t ))S(t)dt + g(t, S( t ))S(t)dW (t) (14) for t (0, T ]. A Delayed OptionPricing Formula p.60/79

128 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. A Delayed OptionPricing Formula p.61/79

129 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. (F t ) 0 t T and W are as before. A Delayed OptionPricing Formula p.61/79

130 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. (F t ) 0 t T and W are as before. f : [0, T ] R R is continuous. A Delayed OptionPricing Formula p.61/79

131 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. (F t ) 0 t T and W are as before. f : [0, T ] R R is continuous. g : [0, T ] R R is continuous. A Delayed OptionPricing Formula p.61/79

132 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. (F t ) 0 t T and W are as before. f : [0, T ] R R is continuous. g : [0, T ] R R is continuous. g(t, v) 0 for all (t, v) [0, T ] R. A Delayed OptionPricing Formula p.61/79

133 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. (F t ) 0 t T and W are as before. f : [0, T ] R R is continuous. g : [0, T ] R R is continuous. g(t, v) 0 for all (t, v) [0, T ] R. The model is feasible: That is S(t) > 0 a.s. for all t > 0. A Delayed OptionPricing Formula p.61/79

134 A Model with Variable Delay Cont d Initial conditions ξ(0) = 1 and S(0) > 0. (F t ) 0 t T and W are as before. f : [0, T ] R R is continuous. g : [0, T ] R R is continuous. g(t, v) 0 for all (t, v) [0, T ] R. The model is feasible: That is S(t) > 0 a.s. for all t > 0. Follows by an argument similar to the proof of Theorem 1. A Delayed OptionPricing Formula p.61/79

135 Theorem 5 Suppose that the stock price S is given by the sdde (14), where S(0) > 0 and f, g satisfy given hypotheses. Let T be the maturity time of an option (contingent claim) on the stock with payoff function X, i.e., X is an FT S -measurable non-negative integrable random variable. Then at any time t [0, T ], the fair price V (t) of the option is given by the formula V (t) = E Q (X F S t )e T t λ(s) ds, (15) where Q denotes the probability measure on (Ω, F) defined by dq := ϱ(t ) dp with A Delayed OptionPricing Formula p.62/79

136 Theorem 5 Cont d ϱ(t) := exp { t 0 {f(u, S( u )) λ(u)} dw (u) g(u, S( u )) 1 t f(u, S( u )) λ(u) 2 g(u, S( u )) 0 2 du } for t [0, T ]. The measure Q is a local martingale measure and the market is complete. A Delayed OptionPricing Formula p.63/79

137 Theorem 5 Cont d Moreover, there is an adapted and square integrable process h 1 (t), t [0, T ], such that ( ) ( ) X E Q X t ξ(t ) F t S = E Q + h 1 (u) dŵ ξ(t ) (u), 0 t [0, T ], where Ŵ (t) := W (t)+ t 0 {f(u, S( u )) λ(u)} g(u, S( u )) du, t [0, T ]. A Delayed OptionPricing Formula p.64/79

138 Theorem 5 Cont d The hedging strategy is given by π S (t) := h 1 (t) S(t)g(t, S( t )), π ξ (t) := M(t) π S (t) S(t), (16) for t [0, T ]. A Delayed OptionPricing Formula p.65/79

139 Theorem 5 Cont d The hedging strategy is given by π S (t) := h 1 (t) S(t)g(t, S( t )), π ξ (t) := M(t) π S (t) S(t), (16) for t [0, T ]. The following result gives a Black-Scholes-type formula for the value of a European option on the stock at any time prior to maturity. A Delayed OptionPricing Formula p.65/79

140 Theorem 6 Assume the conditions of Theorem 5. Let V (t) be the fair price of a European call option written on the stock S with exercise price K and maturity time T. Then for all t [ T T, T ], V (t) is given by where V (t) = S(t)ϕ(β + (t)) Kϕ(β (t))e T t λ(s)ds, (17) β ± (t) := log S(t) K + T ( t λ(u) ± 1 2 g(u, S( u ))2) du. T t g(u, S( u )) 2 du A Delayed OptionPricing Formula p.66/79

141 Theorem 6 Cont d If T > h and t < T T, then V (t) = e t 0 λ(s)ds E Q (H ( S(T T ), 1 2 T T T T T T g(u, S( u )) 2 du, ) ) g(u, S( u )) 2 du F t (18) where H is given by A Delayed OptionPricing Formula p.67/79

142 Theorem 6 Cont d H(x, m, σ 2 ) := xe m+σ2 /2 ϕ(α 1 (x, m, σ)) and α 1 (x, m, σ) := 1 σ [ log α 2 (x, m, σ) := 1 σ for σ, x R +, m R. Kϕ(α 2 (x, m, σ))e T 0 λ(s)ds, ( x K ) [ log + ( x K ) T 0 + λ(s)ds + m + σ 2 ], T 0 ] λ(s)ds + m, A Delayed OptionPricing Formula p.68/79

143 Theorem 6 Cont d The hedging strategy is given by π S (t) = ϕ(β + (t)), for t [ T T, T ]. π ξ (t) = Kϕ(β (t))e T 0 λ(s)ds, A Delayed OptionPricing Formula p.69/79

144 References Bac Bat B.R B.S Bachelier, L., Theorie de la Speculation, Annales de l Ecole Normale Superieure 3, Gauthier-Villards, Paris (1900). Bates, D. S., Testing option pricing models, Statistical Models in Finance, Handbook of Statistics 14, , North- Holland, Amsterdam (1996). Baxter, M. and Rennie, A., Financial Calculus, Cambridge University Press (1996). Black, F. and Scholes, M., The pricing of options and corporate liabilities, Journal of Political Economy 81 (May-June 1973), A Delayed OptionPricing Formula p.70/79

145 References Cont d C H.R H.M.Y H.Ø Cootner, P. H., The Random Character of Stock Market Prices, MIT Press, Cambridge, MA (1964). Hobson, D., and Rogers, L. C. G., Complete markets with stochastic volatility, Math. Finance 8 (1998), Hu, Y., Mohammed, S.-E. A., and Yan, F., Discrete-time approximations of stochastic delay equations: The Milstein scheme, The Annals of Probability, Vol. 32, No. 1A, (2004), Hu, Y. and Øksendal, B., Fractional white noise calculus and applications to finance, Infinite Dimensional Analysis, Quan tum Probability and Related Topics, 6 (2003), A Delayed OptionPricing Formula p.71/79

146 References Cont d K.K K.S Ku Ma Kallianpur, G. and Karandikar R. J., Introduction to Option Pricing Theory, Birkhäuser, Boston-Basel-Berlin (2000). Karatzas, I. and Shreve S., Brownian Motion and Stochastic Calculus, Springer-Verlag, New York-Berlin (1987). Kunita, H., Stochastic Flows and Stochastic Differential Equations, Cambridge University Press, Cambridge, New York, Melbourne, Sydney (1990). Malliaris, A. G., Itô s calculus in financial decision making, SIAM Review, Vol 25, 4, October (1983). A Delayed OptionPricing Formula p.72/79

147 References Cont d Man Me 1 Me 2 Mo 1 Mania, M., Derivation of a Generalized Black-Scholes Formula, Proceedings of A. Razmadze Mathematical Institute, Vol. 115 (1997), Merton, R. C., Theory of rational option pricing, Bell Journal of Economics and Management Science 4, Spring (1973), Merton, R. C., Continuous-Time Finance, Basil Blackwell, Oxford (1990). Mohammed, S.-E. A., Stochastic Differential Systems with Memory (in preparation). A Delayed OptionPricing Formula p.73/79

148 References Cont d Mo 2 Ø R Mohammed, S.-E. A., Stochastic differential systems with memory: Theory, examples and applications. In Stochastic Analysis", Decreusefond L. Gjerde J., Øksendal B., Ustunel A.S., edit., Progress in Probability 42, Birkhauser (1998), Øksendal, B., Stochastic Differential Equations, Springer, fifth edition (1998). Rubinstein, M., Implied binomial trees, Journal of Finance 49, no. 2, (1994), A Delayed OptionPricing Formula p.74/79

149 References Cont d S.K Sc St Schoenmakers, J. and Kloeden, P., Robust option replication for a Black and Scholes model extended with nondeterministic trends, Journal of Applied Mathematics and Stochastic Analysis 12, no. 2, (1999), Scott, L., Option pricing when the variance changes randomly: theory, estimation and an application, Journal of Financial and Quantitative Analysis 22, no. 4, (1987), Stoica, G., A stochastic delay financial model, Proceedings of the American Mathematical Society (2004). A Delayed OptionPricing Formula p.75/79

150 Stock Dynamics-Simulation A Delayed OptionPricing Formula p.76/79

151 Stock Dynamics-Simulation stock price DM BS data time Stock prices when h = constant, b = 2, T = 365 Stock data: DJX Index at CBOE. A Delayed OptionPricing Formula p.76/79

152 AFRICAN CENTER OF EXCELLENCE A Delayed OptionPricing Formula p.77/79

153 AFRICAN CENTER OF EXCELLENCE Graduate Center of Excellence in Mathematics in Africa A Delayed OptionPricing Formula p.77/79

154 AFRICAN CENTER OF EXCELLENCE Graduate Center of Excellence in Mathematics in Africa A Delayed OptionPricing Formula p.77/79

155 AFRICAN CENTER OF EXCELLENCE Graduate Center of Excellence in Mathematics in Africa An idea whose time has come! A Delayed OptionPricing Formula p.77/79

156 AFRICAN CENTER OF EXCELLENCE Graduate Center of Excellence in Mathematics in Africa An idea whose time has come! Please contact with suggestions and/or ideas. A Delayed OptionPricing Formula p.77/79

157 THANK YOU! A Delayed OptionPricing Formula p.78/79