:: Modelling Real World Using Stochastic Processes and Filtration
:: by Peter Jaeger
::
:: Received December 30, 2015
:: Copyright (c) 2015-2018 Association of Mizar Users
:: (Stowarzyszenie Uzytkownikow Mizara, Bialystok, Poland).
:: This code can be distributed under the GNU General Public Licence
:: version 3.0 or later, or the Creative Commons Attribution-ShareAlike
:: License version 3.0 or later, subject to the binding interpretation
:: detailed in file COPYING.interpretation.
:: See COPYING.GPL and COPYING.CC-BY-SA for the full text of these
:: licenses, or see http://www.gnu.org/licenses/gpl.html and
:: http://creativecommons.org/licenses/by-sa/3.0/.
environ
vocabularies FINANCE1, SERIES_1, SEQ_1, RANDOM_3, FINANCE2, NUMBERS, XBOOLE_0,
PROB_1, SUBSET_1, REAL_1, TARSKI, RELAT_1, FUNCT_1, ARYTM_3, XXREAL_0,
VALUED_1, ARYTM_1, NAT_1, CARD_1, ZFMISC_1, RPR_1, SETFAM_1, FINANCE3,
EQREL_1, FUNCOP_1, KOLMOG01, FUNCT_7, MEMBERED, RANDOM_1;
notations TARSKI, SUBSET_1, XBOOLE_0, SERIES_1, SEQ_1, SETFAM_1, ENUMSET1,
RELAT_1, FINANCE1, RANDOM_3, NUMBERS, XREAL_0, XXREAL_0, XCMPLX_0,
MEMBERED, FUNCT_1, VALUED_1, NAT_1, FUNCT_2, PROB_1, SEQ_4, FINANCE2,
RELSET_1, FUNCOP_1, KOLMOG01, RANDOM_1;
constructors SERIES_1, REAL_1, RELSET_1, SEQ_4, FINANCE2, ENUMSET1, RANDOM_2,
KOLMOG01, RANDOM_1, RANDOM_3;
registrations PROB_1, FINANCE1, SUBSET_1, NAT_1, XREAL_0, MEMBERED, ORDINAL1,
FUNCT_2, NUMBERS, VALUED_0, VALUED_1, RELSET_1, INT_1, XBOOLE_0;
requirements NUMERALS, REAL, BOOLE, SUBSET, ARITHM;
begin
theorem :: FINANCE3:1
for a, b being object st a <> b holds
{a} c< {a,b};
registration let I be non empty Subset of NAT;
cluster In(I,bool REAL) -> non empty;
end;
theorem :: FINANCE3:2
for T being Nat holds
{w where w is Element of NAT: w>0 & w<=T} c=
{w where w is Element of NAT: w<=T};
theorem :: FINANCE3:3
for T being Nat holds
{w where w is Element of NAT: w <= T} is non empty Subset of NAT;
theorem :: FINANCE3:4
for T being Nat st T>0 holds
{w where w is Element of NAT: w>0 & w <= T} is non empty Subset of NAT;
:: Special Random-Variables
theorem :: FINANCE3:5
for d being Nat,
phi being Real_Sequence,
Omega being non empty set,
F being SigmaField of Omega,
X being non empty set,
G being sequence of X,
w being Element of Omega holds
{PortfolioValueFutExt(d,phi,F,G,w)} is Event of Borel_Sets;
definition
let d be Nat;
let phi be Real_Sequence;
let Omega be non empty set;
let F be SigmaField of Omega;
let X be non empty set;
let G be sequence of X;
let w be Element of Omega;
redefine func PortfolioValueFutExt(d,phi,F,G,w) -> Element of REAL;
end;
definition
let Omega be non empty set;
let F be SigmaField of Omega;
let X be non empty set;
let G be sequence of X;
let phi be Real_Sequence;
let d be Nat;
func RVPortfolioValueFutExt(phi,F,G,d) -> Function of Omega,REAL
means
:: FINANCE3:def 1
for w being Element of Omega holds
it.w = PortfolioValueFutExt(d,phi,F,G,w);
end;
theorem :: FINANCE3:6
for Omega be non empty set
for F be SigmaField of Omega
for G be sequence of set_of_random_variables_on(F,Borel_Sets)
for phi be Real_Sequence
for d be Nat holds
RVPortfolioValueFutExt(phi,F,G,d) is random_variable of F,Borel_Sets;
definition
let d be Nat;
let phi be Real_Sequence;
let Omega be non empty set;
let F be SigmaField of Omega;
let X be non empty set;
let G be sequence of X;
let w be Element of Omega;
redefine func PortfolioValueFut(d,phi,F,G,w) -> Real equals
:: FINANCE3:def 2
Partial_Sums((RVPortfolioValueFutExt_El(phi,F,G,w))^\1).(d-1);
end;
definition
let d be Nat;
let phi be Real_Sequence;
let Omega be non empty set;
let F be SigmaField of Omega;
let X be non empty set;
let G be sequence of X;
let w be Element of Omega;
redefine func PortfolioValueFut(d,phi,F,G,w) -> Element of REAL;
end;
definition
let Omega be non empty set;
let F be SigmaField of Omega;
let X be non empty set;
let G be sequence of X;
let phi be Real_Sequence;
let d be Nat;
func RVPortfolioValueFut(phi,F,G,d) -> Function of Omega,REAL means
:: FINANCE3:def 3
for w being Element of Omega holds
it.w = PortfolioValueFut(d+1,phi,F,G,w);
end;
theorem :: FINANCE3:7
for Omega be non empty set
for F be SigmaField of Omega
for G be sequence of set_of_random_variables_on(F,Borel_Sets)
for phi be Real_Sequence
for d be Nat holds
RVPortfolioValueFut(phi,F,G,d) is random_variable of F,Borel_Sets;
theorem :: FINANCE3:8
for d being Nat,
phi be Real_Sequence,
Omega be non empty set,
F be SigmaField of Omega,
X be non empty set,
G be sequence of X,
w be Element of Omega holds
PortfolioValueFut(d+1,phi,F,G,w) = RVPortfolioValueFut(phi,F,G,d).w &
{PortfolioValueFut(d+1,phi,F,G,w)} is Event of Borel_Sets;
theorem :: FINANCE3:9
for Omega being non empty set,
F being SigmaField of Omega,
X being non empty set,
G being sequence of X,
phi being Real_Sequence,
d being Nat holds
RVPortfolioValueFutExt(phi,F,G,d+1) = RVPortfolioValueFut(phi,F,G,d) +
RVElementsOfPortfolioValue_fut(phi,F,G,0);
theorem :: FINANCE3:10
for Omega, Omega2 being non empty set,
Sigma being SigmaField of Omega,
Sigma2 being SigmaField of Omega2,
s being Element of Omega2 holds
Omega --> s is_random_variable_on Sigma,Sigma2;
theorem :: FINANCE3:11
for Omega being non empty set,
Sigma being SigmaField of Omega,
RV being random_variable of Sigma,Borel_Sets,
K being Real holds
RV-(Omega-->K) is random_variable of Sigma,Borel_Sets;
definition
let Omega be non empty set;
let RV be Function of Omega,REAL;
let w be Element of Omega;
func SetForCall-Option(RV,w) -> Element of REAL equals
:: FINANCE3:def 4
RV.w if RV.w>=0 otherwise 0;
end;
definition
let Omega be non empty set;
let Sigma be SigmaField of Omega;
let RV be random_variable of Sigma,Borel_Sets;
let K be Real;
func Call-Option(RV,K) -> Function of Omega,REAL means
:: FINANCE3:def 5
for w being Element of Omega holds
((RV-(Omega-->K)).w>=0 implies it.w=(RV-(Omega-->K)).w) &
((RV-(Omega-->K)).w<0 implies it.w=0);
end;
:: Special sigma-Fields
theorem :: FINANCE3:12
for A1 being SetSequence of {1,2,3,4},
w being Real st w = 1 or w = 3 holds
(for n being Nat holds
A1.n = {} or A1.n = {1,2} or A1.n = {3,4} or A1.n = {1,2,3,4})
implies {w}<>Intersection A1;
theorem :: FINANCE3:13
for A1 being SetSequence of {1,2,3,4},
w being Real st w = 2 or w = 4 holds
(for n being Nat holds
A1.n = {} or A1.n = {1,2} or A1.n = {3,4} or A1.n = {1,2,3,4})
implies {w}<>Intersection A1;
theorem :: FINANCE3:14
for MySigmaField, A1, A2 being set st
MySigmaField={{},{1,2,3,4}} & A1 in MySigmaField & A2 in MySigmaField
holds
A1 /\ A2 in MySigmaField;
theorem :: FINANCE3:15
for A1 being SetSequence of {1,2,3,4} st
(for n being Nat,k being Nat holds not (A1.n /\ A1.k = {})) &
rng A1 c= {{},{1,2},{3,4},{1,2,3,4}} holds
(Intersection A1 = {} or
Intersection A1 = {1,2} or Intersection A1 = {3,4} or
Intersection A1 = {1,2,3,4});
theorem :: FINANCE3:16
for A1 being SetSequence of {1,2,3,4},
MyOmega being set st
MyOmega = {{},{1,2},{3,4},{1,2,3,4}} & Intersection A1={1,2,3,4} holds
Intersection A1 in MyOmega;
theorem :: FINANCE3:17
for A1 being SetSequence of {1,2,3,4},
MyOmega being set st
MyOmega = {{},{1,2},{3,4},{1,2,3,4}} & Intersection A1={3,4} holds
Intersection A1 in MyOmega;
theorem :: FINANCE3:18
for A1 being SetSequence of {1,2,3,4},
MyOmega being set st
MyOmega = {{},{1,2},{3,4},{1,2,3,4}} & Intersection A1={1,2} holds
Intersection A1 in MyOmega;
theorem :: FINANCE3:19
for A1 being SetSequence of {1,2,3,4},
MyOmega being set st
MyOmega = {{},{1,2},{3,4},{1,2,3,4}} & Intersection A1={} holds
Intersection A1 in MyOmega;
theorem :: FINANCE3:20
for MyOmega being set,
A1 being SetSequence of {1,2,3,4} st
rng A1 c= MyOmega &
MyOmega = {{},{1,2},{3,4},{1,2,3,4}}
holds Intersection A1 in MyOmega;
theorem :: FINANCE3:21
for MySigmaField, MySet being set,
A1 being SetSequence of MySet st MySet={1,2,3,4} &
rng A1 c= MySigmaField & MySigmaField = {{},{1,2,3,4}} holds
Intersection A1 <> {} implies Intersection A1 in MySigmaField;
theorem :: FINANCE3:22
for MySigmaField, MySet being set,
A1 being SetSequence of MySet st
MySet={1,2,3,4} &
rng A1 c= MySigmaField & MySigmaField = {{},{1,2,3,4}} holds
for k1 being Nat, k2 being Nat holds A1.k1 /\ A1.k2 in MySigmaField;
definition
func Special_SigmaField1 -> SigmaField of {1,2,3,4} equals
:: FINANCE3:def 6
{{},{1,2,3,4}};
end;
definition
func Special_SigmaField2 -> SigmaField of {1,2,3,4} equals
:: FINANCE3:def 7
{{},{1,2},{3,4},{1,2,3,4}};
end;
definition
::$CD
end;
theorem :: FINANCE3:23
for Omega being set st Omega = {1,2,3,4} holds
{1} c= Omega &
{2} c= Omega &
{3} c= Omega &
{4} c= Omega &
{1,2} c= Omega &
{3,4} c= Omega &
{} c= Omega &
Omega c= Omega;
theorem :: FINANCE3:24
for Omega being set st
Omega={1,2,3,4} holds
Omega in Special_SigmaField1 &
{} in Special_SigmaField1 &
{1,2} in Special_SigmaField2 &
{3,4} in Special_SigmaField2 &
Omega in Special_SigmaField2 &
{} in Special_SigmaField2 &
Omega in Trivial-SigmaField {1,2,3,4} &
{} in Trivial-SigmaField {1,2,3,4} &
{1} in Trivial-SigmaField {1,2,3,4} &
{2} in Trivial-SigmaField {1,2,3,4} &
{3} in Trivial-SigmaField {1,2,3,4} &
{4} in Trivial-SigmaField {1,2,3,4};
theorem :: FINANCE3:25
Special_SigmaField1 c< Special_SigmaField2 &
Special_SigmaField2 c< Trivial-SigmaField {1,2,3,4};
:: Construction of Filtration and Examples
theorem :: FINANCE3:26
ex Omega being non empty set st
ex F1,F2,F3 being SigmaField of Omega st
F1 c< F2 & F2 c< F3;
theorem :: FINANCE3:27
ex Omega1,Omega2,Omega3,Omega4 being non empty set st
Omega1 c< Omega2 & Omega2 c< Omega3 & Omega3 c< Omega4 &
(ex F1 being SigmaField of Omega1,
F2 being SigmaField of Omega2,
F3 being SigmaField of Omega3,
F4 being SigmaField of Omega4 st
F1 c= F2 & F2 c= F3 & F3 c= F4);
definition
let Omega be non empty set;
let Sigma be SigmaField of Omega;
let I be non empty real-membered set;
mode Filtration of I,Sigma -> ManySortedSigmaField of I,Sigma means
:: FINANCE3:def 9
for s,t being Element of I st s<=t holds it.s is Subset of it.t;
end;
definition
let I, Omega be non empty set;
let Sigma be SigmaField of Omega;
let Filt be ManySortedSigmaField of I, Sigma;
let i be Element of I;
func El_Filtration(i,Filt) -> SigmaField of Omega equals
:: FINANCE3:def 10
Filt.i;
end;
definition
let k be Element of {1,2,3};
func Set1_of_SigmaField3(k) -> Subset of bool {1,2,3,4} equals
:: FINANCE3:def 11
Special_SigmaField1 if k=1 otherwise
Special_SigmaField2;
end;
definition
let k be Element of {1,2,3};
func Set2_of_SigmaField3(k) -> Subset of bool {1,2,3,4} equals
:: FINANCE3:def 12
Set1_of_SigmaField3(k) if k<=2 otherwise
Trivial-SigmaField {1,2,3,4};
end;
theorem :: FINANCE3:28
for Omega being non empty set,
Sigma being SigmaField of Omega,
I being non empty real-membered set st
I={1,2,3} & Sigma=bool {1,2,3,4} & Omega = {1,2,3,4} holds
ex MyFunc being Filtration of I,Sigma st
MyFunc.1=Special_SigmaField1 &
MyFunc.2=Special_SigmaField2 &
MyFunc.3=Trivial-SigmaField {1,2,3,4};
theorem :: FINANCE3:29
for Omega being non empty set,
Sigma being SigmaField of Omega,
Sigma2 being SigmaField of {1} st
Omega={1,2,3,4} holds
ex X1 being Function of Omega,{1} st
X1 is random_variable of Special_SigmaField1,Sigma2 &
X1 is random_variable of Special_SigmaField2,Sigma2 &
X1 is random_variable of Trivial-SigmaField {1,2,3,4},Sigma2;
:: The first example of the existence of a random-variable depends
:: on a special underlying sigma-field and given Filtration
theorem :: FINANCE3:30
ex Omega, Omega2 be non empty set,
Sigma be SigmaField of Omega,
Sigma2 be SigmaField of Omega2,
I be non empty real-membered set,
Q be Filtration of I,Sigma st
ex rv being Function of Omega,Omega2 st
for i being Element of I holds
rv is random_variable of El_Filtration(i,Q),Sigma2;
:: Next theorem gives also the existence of random_variables
:: depending on arbitrary sigma-fields and filtrations
theorem :: FINANCE3:31
for Omega, Omega2 being non empty set,
Sigma being SigmaField of Omega,
Sigma2 being SigmaField of Omega2,
I being non empty real-membered set,
Q being ManySortedSigmaField of I,Sigma holds
ex rv being Function of Omega,Omega2 st
for i being Element of I holds
rv is random_variable of El_Filtration(i,Q),Sigma2;
:: Stochastic Process: adapted and predictable
:: The next statement is important for the usage of a probability measure
:: with Events depending on SigmaFields in a given filtration.
theorem :: FINANCE3:32
for Omega being non empty set,
Sigma being SigmaField of Omega,
Sigma2 being SigmaField of Omega st Sigma2 c= Sigma holds
for E2 being Event of Sigma2 holds E2 is Event of Sigma;
:: Next we define the stochastic process
definition
let Omega,Omega2 be non empty set,
Sigma be SigmaField of Omega,
Sigma2 be SigmaField of Omega2,
I be non empty real-membered set;
mode Stochastic_Process of I,Sigma,Sigma2 ->
Function of I,set_of_random_variables_on(Sigma,Sigma2) means
:: FINANCE3:def 13
for k being Element of I holds
ex RV being Function of Omega,Omega2 st
it.k=RV & RV is_random_variable_on Sigma,Sigma2;
end;
:: Because adapted and predicted stochastic processes are very important for
:: Stochastic finance, we implement them now:
definition
let Omega,Omega2 be non empty set,
Sigma be SigmaField of Omega,
Sigma2 be SigmaField of Omega2,
I be non empty real-membered set,
Stoch be Stochastic_Process of I,Sigma,Sigma2,
k be Element of I;
func RVProcess(Stoch,k) -> random_variable of Sigma,Sigma2 equals
:: FINANCE3:def 14
Stoch.k;
end;
definition
let Omega,Omega2 be non empty set,
Sigma be SigmaField of Omega,
Sigma2 be SigmaField of Omega2,
I be non empty real-membered set,
Stoch be Stochastic_Process of I,Sigma,Sigma2;
mode Adapted_Stochastic_Process of Stoch ->
Function of I,set_of_random_variables_on(Sigma,Sigma2) means
:: FINANCE3:def 15
ex k being Filtration of I,Sigma st
for i being Element of I holds
RVProcess(Stoch,i) is_random_variable_on El_Filtration(i,k),Sigma2;
end;
definition
let Omega,Omega2 be non empty set;
let Sigma be SigmaField of Omega;
let Sigma2 be SigmaField of Omega2;
let I, J be non empty Subset of NAT;
let Stoch be Stochastic_Process of In(J,bool REAL),Sigma,Sigma2;
mode Predictable_Stochastic_Process of I,J,Sigma,Sigma2,Stoch ->
Function of J,set_of_random_variables_on(Sigma,Sigma2) means
:: FINANCE3:def 16
ex k being Filtration of In(I,bool REAL), Sigma st
for j being Element of In(J,bool REAL),
i being Element of In(I,bool REAL) st j-1=i holds
RVProcess(Stoch,j) is_random_variable_on El_Filtration(i,k),Sigma2;
end;
definition
let Omega,Omega2 be non empty set;
let Sigma be SigmaField of Omega;
let Sigma2 be SigmaField of Omega2;
let I be non empty real-membered set;
let MyFunc be ManySortedSigmaField of I,Sigma;
let Stoch be Stochastic_Process of I,Sigma,Sigma2;
attr Stoch is (MyFunc)-stoch_proc_wrt_to_Filtration means
:: FINANCE3:def 17
for i being Element of I holds
RVProcess(Stoch,i) is_random_variable_on El_Filtration(i,MyFunc),Sigma2;
end;
theorem :: FINANCE3:33
for Omega,Omega2 being non empty set,
Sigma being SigmaField of Omega,
Sigma2 being SigmaField of Omega2,
I being non empty real-membered set,
MyFunc being Filtration of I,Sigma,
Stoch being Stochastic_Process of I,Sigma,Sigma2 st
Stoch is (MyFunc)-stoch_proc_wrt_to_Filtration holds
Stoch is Adapted_Stochastic_Process of Stoch;
:: Example for a Stochastic Process
definition
let k1,k2 be Element of REAL;
let Omega be non empty set;
let k be Element of Omega;
func Set1_for_RandomVariable(k1,k2,k) -> Element of REAL equals
:: FINANCE3:def 18
k1 if (k=1 or k=2) otherwise k2;
func Set4_for_RandomVariable(k1,k2,k) -> Element of REAL equals
:: FINANCE3:def 19
k1 if k=3 otherwise k2;
end;
definition
let k2,k3,k4 be Element of REAL;
let Omega be non empty set;
let k be Element of Omega;
func Set3_for_RandomVariable(k2,k3,k4,k) -> Element of REAL equals
:: FINANCE3:def 20
k2 if k=2 otherwise Set4_for_RandomVariable(k3,k4,k);
end;
definition
let k1,k2,k3,k4 be Element of REAL;
let Omega be non empty set;
let k be Element of Omega;
func Set2_for_RandomVariable(k1,k2,k3,k4,k) -> Element of REAL equals
:: FINANCE3:def 21
k1 if k=1 otherwise Set3_for_RandomVariable(k2,k3,k4,k);
end;
theorem :: FINANCE3:34
for k1,k2,k3,k4 being Element of REAL holds
for Omega being set st Omega={1,2,3,4}
ex f being Function of Omega,REAL st
f.1=k1 & f.2=k2 & f.3=k3 & f.4=k4;
theorem :: FINANCE3:35
for k1,k2,k3,k4 be Element of REAL holds
for Omega being non empty set st Omega={1,2,3,4} holds
for Sigma being SigmaField of Omega,
I being non empty real-membered set,
MyFunc being ManySortedSigmaField of I,Sigma st
MyFunc.1=Special_SigmaField1 &
MyFunc.2=Special_SigmaField2 &
MyFunc.3=Trivial-SigmaField {1,2,3,4} holds
for eli being Element of I st eli=3 holds
ex f being Function of Omega,REAL st
f.1=k1 & f.2=k2 & f.3=k3 & f.4=k4 &
f is_random_variable_on El_Filtration(eli,MyFunc),Borel_Sets;
theorem :: FINANCE3:36
for k1,k2 being Element of REAL,
Omega being non empty set st Omega={1,2,3,4} holds
for Sigma being SigmaField of Omega,
I being non empty real-membered set,
MyFunc being ManySortedSigmaField of I,Sigma st
MyFunc.1=Special_SigmaField1 &
MyFunc.2=Special_SigmaField2 &
MyFunc.3=Trivial-SigmaField {1,2,3,4} holds
for eli being Element of I st eli=2 holds
ex f being Function of Omega,REAL st
f.1=k1 & f.2=k1 & f.3=k2 & f.4=k2 &
f is_random_variable_on El_Filtration(eli,MyFunc),Borel_Sets;
theorem :: FINANCE3:37
for k1 being Element of REAL,
Omega being non empty set st Omega={1,2,3,4} holds
for Sigma being SigmaField of Omega,
I being non empty real-membered set,
MyFunc being ManySortedSigmaField of I,Sigma st
MyFunc.1=Special_SigmaField1 &
MyFunc.2=Special_SigmaField2 &
MyFunc.3=Trivial-SigmaField {1,2,3,4} holds
for eli being Element of I st eli=1 holds
ex f being Function of Omega,REAL st
f.1=k1 & f.2=k1 & f.3=k1 & f.4=k1 &
f is_random_variable_on El_Filtration(eli,MyFunc),Borel_Sets;
theorem :: FINANCE3:38
for Omega being non empty set st Omega={1,2,3,4} holds
for Sigma being SigmaField of Omega,
I being non empty real-membered set
st I={1,2,3} & Sigma = bool {1,2,3,4} holds
for MyFunc being ManySortedSigmaField of I,Sigma st
MyFunc.1=Special_SigmaField1 &
MyFunc.2=Special_SigmaField2 &
MyFunc.3=Trivial-SigmaField {1,2,3,4} holds
for Prob being Function of Sigma, REAL holds
for i being Element of I holds
ex RV being Function of Omega,REAL st
RV is_random_variable_on El_Filtration(i,MyFunc),Borel_Sets;
definition
let I be non empty real-membered set such that I={1,2,3};
let i be Element of I such that i=2 or i=3;
let Omega be non empty set such that Omega={1,2,3,4};
let Sigma be SigmaField of Omega such that Sigma=bool Omega;
let f1 be Function of Omega,REAL such that
f1.1=60 & f1.2=80 & f1.3=100 & f1.4=120;
let f2 be Function of Omega,REAL such that
f2.1=80 & f2.2=80 & f2.3=120 & f2.4=120;
let f3 be Function of Omega,REAL;
func FunctionRV1(i,Sigma,f1,f2,f3) -> Element of
set_of_random_variables_on(Sigma,Borel_Sets) equals
:: FINANCE3:def 22
f2 if i=2 otherwise f1;
end;
definition
let I be non empty real-membered set such that I={1,2,3};
let i be Element of I;
let Omega be non empty set such that Omega={1,2,3,4};
let Sigma be SigmaField of Omega such that Sigma=bool Omega;
let f1,f2 be Function of Omega,REAL;
let f3 be Function of Omega,REAL such that
f3.1=100 & f3.2=100 & f3.3=100 & f3.4=100;
func FunctionRV2(i,Sigma,f1,f2,f3) ->
Element of set_of_random_variables_on(Sigma,Borel_Sets) equals
:: FINANCE3:def 23
FunctionRV1(i,Sigma,f1,f2,f3) if (i=2 or i=3) otherwise f3;
end;
theorem :: FINANCE3:39
for Omega, Omega2 being non empty set st Omega={1,2,3,4} holds
for Sigma being SigmaField of Omega,
I being non empty real-membered set st
I={1,2,3} & Sigma=bool{1,2,3,4} holds
for MyFunc being Filtration of I,Sigma st
MyFunc.1=Special_SigmaField1 &
MyFunc.2=Special_SigmaField2 &
MyFunc.3=Trivial-SigmaField {1,2,3,4}
ex Stoch being Stochastic_Process of I,Sigma,Borel_Sets st
(for k being Element of I holds
(ex RV being Function of Omega,REAL st
(Stoch.k=RV & RV is_random_variable_on Sigma,Borel_Sets &
RV is_random_variable_on El_Filtration(k,MyFunc),Borel_Sets)) &
(ex f being Function of Omega,REAL st
k=1 implies f.1=100 & f.2=100 & f.3=100 & f.4=100 & Stoch.k=f)&
(ex f being Function of Omega,REAL st
k=2 implies f.1=80 & f.2=80 & f.3=120 & f.4=120 & Stoch.k=f) &
(ex f being Function of Omega,REAL st
k=3 implies f.1=60 & f.2=80 & f.3=100 & f.4=120 & Stoch.k=f) &
Stoch is (MyFunc)-stoch_proc_wrt_to_Filtration) &
Stoch is Adapted_Stochastic_Process of Stoch;