Method and system for non-Gaussian pricing of options and other derivatives
AssigneeEvnine & Associates, Inc.
InventorLisa Marina Borland
Life of this patent
Estimating the term…
Abstract
In preferred embodiments, a method and system for pricing a derivative (e.g., a stock option) based on a non-Gaussian price model assuming statistical feedback. The dynamics of the underlying financial instrument (e.g., stock) are assumed to follow a stochastic process with anomalous nonlinear diffusion, phenomenologically modeled as a statistical feedback process within the framework of a generalized thermostatistics. Preferred embodiments implement solutions to a generalized form of the Black-Scholes differential equation, using risk-free asset valuation techniques in some cases.
Claims46
A method for determining price, f(S), of a derivative having an underlying financial instrument, said method including the steps of:
- (a) determining a non-Gaussian model of price, S, of the underlying financial instrument, said model assuming statistical feedback,
- where the price S is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return;
- and
- (b) by operating a computer system, determining as price f, a derivative price value consistent with the model determined in step (a), including by generating data indicative of the derivative price value.
A method for determining price, f(S), of a derivative having an underlying financial instrument, said method including the steps of:
- (a) determining price, S, of the underlying financial instrument at time t=T to be
- S
-
- (
- T
- )
- =
- S
-
- (
- 0
- )
-
- exp
-
- (
- Ω
-
- (
- T
- )
- +
- rT
- -
- σ
- 2
- 2
-
- α
-
- T
- 2
- 3
- -
- q
-
- (
- 1
- -
- (
- 1
- -
- q
- )
-
- β
-
-
- (
- T
- )
-
- Ω
- 2
-
- (
- T
- )
- )
- )
- ,
- where
- S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return,
- α
- =
- 1
- 2
-
- (
- 3
- -
- q
- )
-
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- c
- )
- q
- -
- 1
- 3
- -
- q
- ,
- q is an entropic index, q>1, Ω is drive noise, σ2 is a variance parameter of the logarithmic return of the underlying financial instrument,
- β
-
- (
- t
- )
- =
- c
- 1
- -
- q
- 3
- -
- q
-
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- t
- )
- -
- 2
- /
- (
- 3
- -
- q
- )
- ,
- and
-
-
- c
- =
- β
-
- N
- 2
- with
- N
- =
- ∫
- -
- ∞
- ∞
-
- (
- 1
- -
- (
- 1
- -
- q
- )
-
- βΩ
- 2
- )
- 1
- 1
- -
- q
-
- ⅆ
- Ω
- for any value of β,
- the drive noise Ω follows a statistical feedback process
- dΩ=Pq(Ω)(1−q)/2dω
- where ω is zero-mean Gaussian noise, Pq(Ω)≡Pq(Ω,t|Ω′,t0), t0=0 without loss of generality, and Pq is a conditional probability that evolves according to
- P
- q
-
- (
- Ω
- ,
- t
- |
- 0
- ,
- 0
- )
- =
- 1
- Z
-
- (
- t
- )
-
- (
- 1
- -
- β
-
- (
- t
- )
-
- (
- 1
- -
- q
- )
-
- (
- Ω
- )
- 2
- )
- 1
- 1
- -
- q
-
-
- where
-
-
- Z
-
- (
- t
- )
- =
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- ct
- )
- 1
- 3
- -
- q
- ,
- and
- (b) by operating a computer system, determining the price f from the price S determined in step (a) and from boundary conditions specific to the derivative, including by generating data indicative of said price f.
A method for determining price, f(S), of a derivative having an underlying financial instrument, said method including the steps of:
- (a) determining price, S, of the underlying financial instrument at time t=T to be
- S
-
- (
- T
- )
- =
- S
-
- (
- 0
- )
-
- exp
-
- (
- ∫
- 0
- T
-
- σ
-
-
- P
- q
- 1
- -
- q
- 2
-
- ⅆ
- z
- s
- +
- ∫
- 0
- T
-
- (
- r
- -
- σ
- 2
- 2
-
- P
- q
- 1
- -
- q
- )
-
- ⅆ
- s
- )
- ,
- where
- S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return;
- q is an entropic index, q>1, z is drive noise, σ2 is a variance parameter of the logarithmic return of the underlying financial instrument, r is a risk-free rate of return, Pq is a conditional probability that satisfies
- ⅆ
- (
- ln
-
-
- S
- -
- rt
- +
- σ
- 2
- 2
-
- P
- q
- 1
- -
- q
-
- (
- Ω
- )
- )
- σ
- =
- ⅆ
- Ω
- ,
- Ω is drive noise, and the drive noise z satisfies
- ⅆ
- z
- =
- (
- μ
- -
- r
- +
- σ
- 2
-
- P
- q
- 1
- -
- q
- 2
- σ
-
-
- P
- q
- 1
- -
- q
- 2
- )
-
- ⅆ
- t
- +
- ⅆ
- ω
- ,
- where ω is zero-mean Gaussian noise, and μ is the mean rate of return;
- and
- (b) by operating a computer system, determining the price f from the price S determined in step (a) and from boundary conditions specific to the derivative, including by generating data indicative of said price f.
A computer system, comprising:
- a processor programmed to generate data indicative of price, f(S), of a derivative having an underlying financial instrument whose price is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, T is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return, including by implementing a non-Gaussian model of the price S, said model assuming statistical feedback, and determining as the price, f, a value consistent with the model;
- and
- a display device coupled to the processor for displaying a result of the determination of the price, f(S), of the derivative.
A computer system, comprising:
- a processor programmed to generate data indicative of price, f(S), of a derivative having an underlying financial instrument whose price is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return, including by determining the price S at time t=T to be
- S
-
- (
- T
- )
- =
- S
-
- (
- 0
- )
-
- exp
-
- (
- Ω
-
- (
- T
- )
- +
- r
-
-
- T
- -
- σ
- 2
- 2
-
- α
-
-
- T
- 2
- 3
- -
- q
-
- (
- 1
- -
- (
- 1
- -
- q
- )
-
- β
-
- (
- T
- )
-
- Ω
- 2
-
- (
- T
- )
- )
- )
- ,
- where
- α
- =
- 1
- 2
-
- (
- 3
- -
- q
- )
-
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- c
- )
- q
- -
- 1
- 3
- -
- q
- ,
- q is an entropic index, q>1, Ω is drive noise, σ2 is a variance parameter of the logarithmic return of the underlying financial instrument, r is a risk-free rate of return,
- β
-
- (
- t
- )
- =
- c
- 1
- -
- q
- 3
- -
- q
-
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- t
- )
- -
- 2
- /
- (
- 3
- -
- q
- )
- and
- c
- =
- β
-
-
- N
- 2
-
-
- with
-
-
- N
- =
- ∫
- -
- ∞
- ∞
-
- (
- 1
- -
- (
- 1
- -
- q
- )
-
- βΩ
- 2
- )
- 1
- 1
- -
- q
-
- ⅆ
- Ω
- for any value of β,
- the drive noise Ω follows a statistical feedback process
- dΩ=Pq(Ω)(1−q)/2dω
- where ω is zero-mean Gaussian noise, Pq(Ω)≡Pq(Ω,t|Ω′,t0), t0=0 without loss of generality, and Pq is a conditional probability that evolves according to
- P
- q
-
- (
- Ω
- ,
- t
- |
- 0
- ,
- 0
- )
- =
- 1
- Z
-
- (
- t
- )
-
- (
- 1
- -
- β
-
- (
- t
- )
-
- (
- 1
- -
- q
- )
-
- (
- Ω
- )
- 2
- )
- 1
- 1
- -
- q
- ,
- where
- Z
-
- (
- t
- )
- =
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- ct
- )
- 1
- 3
- -
- q
- ,
- and determining the price f from said price S at time t=T;
- and
- a display device coupled to the processor for displaying a result of the determination of the price f.
A computer system, comprising:
- a processor programmed to generate data indicative of price, f(S), of a derivative having an underlying financial instrument whose price is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return, including by determining the price S at time t=T to be
- S
-
- (
- T
- )
- =
- S
-
- (
- 0
- )
-
- exp
-
- (
- ∫
- 0
- T
-
- σ
-
-
- P
- q
- 1
- -
- q
- 2
-
- ⅆ
- z
- s
- +
- ∫
- 0
- T
-
- (
- r
- -
- σ
- 2
-
- P
- q
- 1
- -
- q
- )
-
- ⅆ
- s
- )
- ,
- where
- q is an entropic index, q>1, z is drive noise, r is a risk-free rate of return, σ2 is a variance parameter of the logarithmic return of the underlying financial instrument, and Pq is a conditional probability that satisfies
- ⅆ
- (
- ln
-
-
- S
- -
- rt
- +
- σ
- 2
- 2
-
- P
- q
- 1
-
- (
- Ω
- )
- )
- σ
- =
- ⅆ
- Ω
- Ω is drive noise, and the drive noise z satisfies
- ⅆ
- z
- =
- (
- μ
- -
- r
- +
- σ
- 2
-
- P
- q
- 1
- -
- q
- 2
- σ
-
-
- P
- q
- 1
- -
- q
- 2
- )
-
- ⅆ
- t
- +
- ⅆ
-
- ω
- ,
- where ω is zero-mean Gaussian noise, and μ is the mean rate of return, and determining the price f from said price S at time t=T;
- and
- a display device coupled to the processor for displaying a result of the determination of the price f.
A computer readable medium which is a tangible object and which stores code for programming a processor to generate data indicative of the price, f(S), of a derivative having an underlying financial instrument whose price is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, T is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return, including by implementing a non-Gaussian model of the price, S, said model assuming statistical feedback, and determining, as the price f, a value consistent with the model.
A computer readable medium which is a tangible object and which stores code for programming a processor to generate data indicative of the price, f(S), of a derivative having an underlying financial instrument whose price is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return, including by determining the price S at time t=T to be
- S
-
- (
- T
- )
- =
- S
-
- (
- 0
- )
-
- exp
-
- (
- Ω
-
- (
- T
- )
- +
- rT
- -
- σ
- 2
- 2
-
- α
-
-
- T
- 2
- 3
- -
- q
-
- (
- 1
- -
- (
- 1
- -
- q
- )
-
- β
-
- (
- T
- )
-
- Ω
- 2
-
- (
- T
- )
- )
- )
- ,
- where
- α
- =
- 1
- 2
-
- (
- 3
- -
- q
- )
-
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- c
- )
- q
- -
- 1
- 3
- -
- q
- ,
- q is an entropic index, q>1, Ω is drive noise, σ2 is a variance parameter of the logarithmic return of the underlying financial instrument,
- β
-
- (
- t
- )
- =
- c
- 1
- -
- q
- 3
- -
- q
-
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- t
- )
- -
- 2
- /
- (
- 3
- -
- q
- )
- ,
- and c=βN2 with
- N
- =
- ∫
- -
- ∞
- ∞
-
- (
- 1
- -
- (
- 1
- -
- q
- )
-
- βΩ
- 2
- )
- 1
- 1
- -
- q
-
- ⅆ
- Ω
- for any value of β,
- the drive noise Ω follows a statistical feedback process
- dΩ=Pq(Ω)(1−q)/2dω
- where ω is zero-mean Gaussian noise, Pq(Ω)≡Pq(Ω,t|Ω′,t0), t0=0 without loss of generality, and Pq is a conditional probability that evolves according to
- P
- q
-
- (
- Ω
- ,
- t
- |
- 0
- ,
- 0
- )
- =
- 1
- Z
-
- (
- t
- )
-
- (
- 1
- -
- β
-
- (
- t
- )
-
- (
- 1
- -
- q
- )
-
- (
- Ω
- )
- 2
- )
- 1
- 1
- -
- q
- ,
- Z
-
- (
- t
- )
- =
- (
- (
- 2
- -
- q
- )
-
- (
- 3
- -
- q
- )
-
- ct
- )
- 1
- 3
- -
- q
- ,
- and determining the price, f, from said price S at time t=T.
A computer readable medium which is a tangible object and which stores code for programming a processor to generate data indicative of the price, f(S), of a derivative having an underlying financial instrument whose price is S=S(t+τ)=S(τ)eY(t), where t denotes a time delay, time interval, or timescale, τ is an initial time value, τ=0 without loss of generality, Y(t) is a value that evolves across timescale t, and the underlying financial instrument has a return, including by determining the price S at time t=T to be
- S
-
- (
- T
- )
- =
- S
-
- (
- 0
- )
-
- exp
-
- (
- ∫
- 0
- T
-
- σ
-
-
- P
- q
- 1
- -
- q
- 2
-
- ⅆ
- z
- s
- +
- ∫
- 0
- T
-
- (
- r
- -
- σ
- 2
- 2
-
- P
- q
- 1
- -
- q
- )
-
- ⅆ
- s
- )
- ,
- where
- q is an entropic index, q>1, z is drive noise, r is a risk-free rate of return, and σ2 is a variance parameter of the logarithmic return of the underlying financial instrument, Pq is a conditional probability that satisfies
- ⅆ
- (
- ln
-
-
- S
- -
- rt
- +
- σ
- 2
- 2
-
- P
- q
- 1
- -
- q
-
- (
- Ω
- )
- )
- σ
- =
- ⅆ
- Ω
- ,
- Ω is drive noise, and the drive noise z satisfies
- ⅆ
- z
- =
- (
- μ
- -
- r
- +
- σ
- 2
-
- P
- q
- 1
- -
- q
- 2
- σ
-
-
- P
- q
- 1
- -
- q
- 2
- )
-
- ⅆ
- t
- +
- ⅆ
- ω
- ,
- where ω is zero-mean Gaussian noise,
- and μ is the mean rate of return, and determining the price, f, from said price S at time t=T.
Dependencies are inferred from the claim text.