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Weak Dynamic Programming for ViscositySolutions
B. Bouchard
Ceremade, Univ. Paris-Dauphine, and, Crest, Ensae
May 2009
Joint work with Nizar Touzi, CMAP, Ecole Polytechnique
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X ν
t = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X ν
t = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.
J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X ν
t = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X ν
t = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.
J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X ν
t = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X ν
t = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.
J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X ν
t = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X ν
t = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.
J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X ν
t = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X ν
t = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.
J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X ν
t = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X ν
t = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.
J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
Framework
• (Ω,F ,F := (Ft)t≤T ,P), T > 0.
• Controls :
U0, a collection of Rd -valued progressively measurable processes.
• Controlled process :
(τ, ξ; ν) ∈ S × U0 7−→ X ντ,ξ ∈ H0
rcll(Rd )
with [0,T ]× Rd ⊂ S ⊂
(τ, ξ) : τ ∈ T[0,T ] and ξ ∈ L0τ (Rd )
.
Framework
• (Ω,F ,F := (Ft)t≤T ,P), T > 0.
• Controls :
U0, a collection of Rd -valued progressively measurable processes.
• Controlled process :
(τ, ξ; ν) ∈ S × U0 7−→ X ντ,ξ ∈ H0
rcll(Rd )
with [0,T ]× Rd ⊂ S ⊂
(τ, ξ) : τ ∈ T[0,T ] and ξ ∈ L0τ (Rd )
.
Framework
• (Ω,F ,F := (Ft)t≤T ,P), T > 0.
• Controls :
U0, a collection of Rd -valued progressively measurable processes.
• Controlled process :
(τ, ξ; ν) ∈ S × U0 7−→ X ντ,ξ ∈ H0
rcll(Rd )
with [0,T ]× Rd ⊂ S ⊂
(τ, ξ) : τ ∈ T[0,T ] and ξ ∈ L0τ (Rd )
.
Reward and Value functions
• Reward function
J(t, x ; ν) := E[f(X ν
t,x(T ))]
defined for controls ν in
U :=ν ∈ U0 : E
[|f (X ν
t,x(T ))|]<∞ ∀ (t, x) ∈ [0,T ]× Rd
.
• Admissibility : a control ν ∈ U is t-admissible if it isindependent of Ft . We denote by Ut the collection of suchprocesses.
• Value function :
V (t, x) := supν∈Ut
J(t, x ; ν) for (t, x) ∈ [0,T ]× Rd .
Reward and Value functions
• Reward function
J(t, x ; ν) := E[f(X ν
t,x(T ))]
defined for controls ν in
U :=ν ∈ U0 : E
[|f (X ν
t,x(T ))|]<∞ ∀ (t, x) ∈ [0,T ]× Rd
.
• Admissibility : a control ν ∈ U is t-admissible if it isindependent of Ft . We denote by Ut the collection of suchprocesses.
• Value function :
V (t, x) := supν∈Ut
J(t, x ; ν) for (t, x) ∈ [0,T ]× Rd .
Reward and Value functions
• Reward function
J(t, x ; ν) := E[f(X ν
t,x(T ))]
defined for controls ν in
U :=ν ∈ U0 : E
[|f (X ν
t,x(T ))|]<∞ ∀ (t, x) ∈ [0,T ]× Rd
.
• Admissibility : a control ν ∈ U is t-admissible if it isindependent of Ft . We denote by Ut the collection of suchprocesses.
• Value function :
V (t, x) := supν∈Ut
J(t, x ; ν) for (t, x) ∈ [0,T ]× Rd .
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality : V (t, x) ≤ supν∈Ut E[V (τ,X ν
t,x(τ))]
Proof :
V (t, x) = supν∈Ut
E[E[f (X ν
t,x(T ))|Fτ]]
where for some νω ∈ Uτ(ω)
E[f (X ν
t,x(T ))|Fτ]
(ω) ≤ J(τ(ω),X νt,x(τ)(ω); νω)
≤ V (τ(ω),X νt,x(τ)(ω))
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality : V (t, x) ≤ supν∈Ut E[V (τ,X ν
t,x(τ))]
Proof :
V (t, x) = supν∈Ut
E[E[f (X ν
t,x(T ))|Fτ]]
where for some νω ∈ Uτ(ω)
E[f (X ν
t,x(T ))|Fτ]
(ω) ≤ J(τ(ω),X νt,x(τ)(ω); νω)
≤ V (τ(ω),X νt,x(τ)(ω))
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality : V (t, x) ≤ supν∈Ut E[V (τ,X ν
t,x(τ))]
Proof :
V (t, x) = supν∈Ut
E[E[f (X ν
t,x(T ))|Fτ]]
where for some νω ∈ Uτ(ω)
E[f (X ν
t,x(T ))|Fτ]
(ω) ≤ J(τ(ω),X νt,x(τ)(ω); νω)
≤ V (τ(ω),X νt,x(τ)(ω))
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality : V (t, x) ≤ supν∈Ut E[V (τ,X ν
t,x(τ))]
Proof :
V (t, x) = supν∈Ut
E[E[f (X ν
t,x(T ))|Fτ]]
where for some νω ∈ Uτ(ω)
E[f (X ν
t,x(T ))|Fτ]
(ω) ≤ J(τ(ω),X νt,x(τ)(ω); νω)
≤ V (τ(ω),X νt,x(τ)(ω))
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality : V (t, x) ≤ supν∈Ut E[V (τ,X ν
t,x(τ))]
Proof :
V (t, x) = supν∈Ut
E[E[f (X ν
t,x(T ))|Fτ]]
where for some νω ∈ Uτ(ω)
E[f (X ν
t,x(T ))|Fτ]
(ω) ≤ J(τ(ω),X νt,x(τ)(ω); νω)
≤ V (τ(ω),X νt,x(τ)(ω))
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality :
V (t, x) ≤ supν∈Ut
E[V (τ,X ν
t,x(τ))]
• More difficult one :
V (t, x) ≥ supν∈Ut
E[V (τ,X ν
t,x(τ))]
The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X ν
t,x(τ))]′′
• Easy inequality :
V (t, x) ≤ supν∈Ut
E[V (τ,X ν
t,x(τ))]
• More difficult one :
V (t, x) ≥ supν∈Ut
E[V (τ,X ν
t,x(τ))]
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi ) and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]
∑i≥1
1Ai (τ,Xνt,x(τ))ν i .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi )
and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]
∑i≥1
1Ai (τ,Xνt,x(τ))ν i .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi ) and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .
Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]
∑i≥1
1Ai (τ,Xνt,x(τ))ν i .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi ) and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]
∑i≥1
1Ai (τ,Xνt,x(τ))ν i .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X νε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); ν i )1Ai
(τ,X ν
t,x(τ))
≥∑i≥1
(V (τ,X ν
t,x(τ))− 3ε)1Ai
(τ,X ν
t,x(τ))
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fτ]]
≥ E[V(τ,X ν
t,x(τ))]− 3ε .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X νε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); ν i )1Ai
(τ,X ν
t,x(τ))
≥∑i≥1
(V (τ,X ν
t,x(τ))− 3ε)1Ai
(τ,X ν
t,x(τ))
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fτ]]
≥ E[V(τ,X ν
t,x(τ))]− 3ε .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X νε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); ν i )1Ai
(τ,X ν
t,x(τ))
≥∑i≥1
(V (τ,X ν
t,x(τ))− 3ε)1Ai
(τ,X ν
t,x(τ))
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fτ]]
≥ E[V(τ,X ν
t,x(τ))]− 3ε .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X νε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); ν i )1Ai
(τ,X ν
t,x(τ))
≥∑i≥1
(V (τ,X ν
t,x(τ))− 3ε)1Ai
(τ,X ν
t,x(τ))
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fτ]]
≥ E[V(τ,X ν
t,x(τ))]− 3ε .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X νε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); ν i )1Ai
(τ,X ν
t,x(τ))
≥∑i≥1
(V (τ,X ν
t,x(τ))− 3ε)1Ai
(τ,X ν
t,x(τ))
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fτ]]
≥ E[V(τ,X ν
t,x(τ))]− 3ε .
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X νε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); ν i )1Ai
(τ,X ν
t,x(τ))
≥∑i≥1
(V (τ,X ν
t,x(τ))− 3ε)1Ai
(τ,X ν
t,x(τ))
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fτ]]
≥ E[V(τ,X ν
t,x(τ))]− 3ε .
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof
: It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important
: It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof : It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important
: It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof : It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important
: It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof : It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important : It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
Observation
To derive the PDE in the viscosity sense, try to obtain :
V (t, x) ≥ supν∈Ut
E[V (τ,X ν
t,x(τ)]
but one only needs :
V (t, x) ≥ supν∈Ut
E[ϕ(τ,X ν
t,x(τ)]
for all smooth function such that (t, x) achieves a minimum ofV − ϕ.ϕ being smooth it should be much easier to prove ! !
Observation
To derive the PDE in the viscosity sense, try to obtain :
V (t, x) ≥ supν∈Ut
E[V (τ,X ν
t,x(τ)]
but one only needs :
V (t, x) ≥ supν∈Ut
E[ϕ(τ,X ν
t,x(τ)]
for all smooth function such that (t, x) achieves a minimum ofV − ϕ.
ϕ being smooth it should be much easier to prove ! !
Observation
To derive the PDE in the viscosity sense, try to obtain :
V (t, x) ≥ supν∈Ut
E[V (τ,X ν
t,x(τ)]
but one only needs :
V (t, x) ≥ supν∈Ut
E[ϕ(τ,X ν
t,x(τ)]
for all smooth function such that (t, x) achieves a minimum ofV − ϕ.ϕ being smooth it should be much easier to prove ! !
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix θν , ν ∈ Ut ⊂ T t[t,T ] a family of stopping times.
Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))],
where Uϕt =ν ∈ Ut : E
[ϕ(θν ,X ν
t,x(θν))+]<∞ or E
[ϕ(θν ,X ν
t,x(θν))−]<∞
.
Remark : The minimum can be taken to be local if(θν ,X ν
t,x(θν)), ν ∈ Ut is bounded in L∞. In practice ϕ is takento be C 1,2.
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix θν , ν ∈ Ut ⊂ T t[t,T ] a family of stopping times.
Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))],
where Uϕt =ν ∈ Ut : E
[ϕ(θν ,X ν
t,x(θν))+]<∞ or E
[ϕ(θν ,X ν
t,x(θν))−]<∞
.
Remark : The minimum can be taken to be local if(θν ,X ν
t,x(θν)), ν ∈ Ut is bounded in L∞. In practice ϕ is takento be C 1,2.
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix θν , ν ∈ Ut ⊂ T t[t,T ] a family of stopping times.
Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))],
where Uϕt =ν ∈ Ut : E
[ϕ(θν ,X ν
t,x(θν))+]<∞ or E
[ϕ(θν ,X ν
t,x(θν))−]<∞
.
Remark : The minimum can be taken to be local if(θν ,X ν
t,x(θν)), ν ∈ Ut is bounded in L∞.
In practice ϕ is takento be C 1,2.
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix θν , ν ∈ Ut ⊂ T t[t,T ] a family of stopping times.
Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))],
where Uϕt =ν ∈ Ut : E
[ϕ(θν ,X ν
t,x(θν))+]<∞ or E
[ϕ(θν ,X ν
t,x(θν))−]<∞
.
Remark : The minimum can be taken to be local if(θν ,X ν
t,x(θν)), ν ∈ Ut is bounded in L∞. In practice ϕ is takento be C 1,2.
The weak DPPProof.
For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
Then,
E[f(X νε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X ν
t,x(θν))
≥∑i≥1
(ϕ(θν ,X ν
t,x(θν))− 3ε)1Ai
(θν ,X ν
t,x(θν))
= ϕ(θν ,X νt,x(θν))− 3ε
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .
Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
Then,
E[f(X νε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X ν
t,x(θν))
≥∑i≥1
(ϕ(θν ,X ν
t,x(θν))− 3ε)1Ai
(θν ,X ν
t,x(θν))
= ϕ(θν ,X νt,x(θν))− 3ε
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
Then,
E[f(X νε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X ν
t,x(θν))
≥∑i≥1
(ϕ(θν ,X ν
t,x(θν))− 3ε)1Ai
(θν ,X ν
t,x(θν))
= ϕ(θν ,X νt,x(θν))− 3ε
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
Then,
E[f(X νε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X ν
t,x(θν))
≥∑i≥1
(ϕ(θν ,X ν
t,x(θν))− 3ε)1Ai
(θν ,X ν
t,x(θν))
= ϕ(θν ,X νt,x(θν))− 3ε
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
Then,
E[f(X νε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X ν
t,x(θν))
≥∑i≥1
(ϕ(θν ,X ν
t,x(θν))− 3ε)1Ai
(θν ,X ν
t,x(θν))
= ϕ(θν ,X νt,x(θν))− 3ε
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; νi ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
Then,
E[f(X νε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X ν
t,x(θν))
≥∑i≥1
(ϕ(θν ,X ν
t,x(θν))− 3ε)1Ai
(θν ,X ν
t,x(θν))
= ϕ(θν ,X νt,x(θν))− 3ε
The weak DPP
Proof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that onAi := (ti − ri , ti ]× Bi , disjoint sets that cover [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]
∑i≥1
1Ai (θν ,X ν
t,x(θν))ν i .
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X νε
t,x(T ))|Fνθ]]
≥ E[ϕ(θν ,X ν
t,x(θν))]− 3ε .
The weak DPP
Using test functions makes the proof straightforward :
supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))]≤ V (t, x)
≤ supν∈Ut
E[V ∗(θν ,X ν
t,x(θν))]
Remark : If X νt,x(θν), ν ∈ Ut is bounded in L∞, one can
approximate V∗ from below by smooth functions and obtain :
supν∈Ut
E[V∗(θν ,X ν
t,x(θν))]≤ V (t, x) ≤ sup
ν∈Ut
E[V ∗(θν ,X ν
t,x(θν))]
The weak DPP
Using test functions makes the proof straightforward :
supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))]≤ V (t, x) ≤ sup
ν∈Ut
E[V ∗(θν ,X ν
t,x(θν))]
Remark : If X νt,x(θν), ν ∈ Ut is bounded in L∞, one can
approximate V∗ from below by smooth functions and obtain :
supν∈Ut
E[V∗(θν ,X ν
t,x(θν))]≤ V (t, x) ≤ sup
ν∈Ut
E[V ∗(θν ,X ν
t,x(θν))]
The weak DPP
Using test functions makes the proof straightforward :
supν∈Uϕt
E[ϕ(θν ,X ν
t,x(θν))]≤ V (t, x) ≤ sup
ν∈Ut
E[V ∗(θν ,X ν
t,x(θν))]
Remark : If X νt,x(θν), ν ∈ Ut is bounded in L∞, one can
approximate V∗ from below by smooth functions and obtain :
supν∈Ut
E[V∗(θν ,X ν
t,x(θν))]≤ V (t, x) ≤ sup
ν∈Ut
E[V ∗(θν ,X ν
t,x(θν))]
Example : Framework
• Controlled process
dX (r) = µ (X (r), νr ) dr + σ (X (r), νr ) dWr
• U = square integrable progressively measurable processes withvalues in U ⊂ Rd
• f is l.s.c with f − with linear growth, µ and σ Lipschitzcontinuous.
Example : Framework
• Controlled process
dX (r) = µ (X (r), νr ) dr + σ (X (r), νr ) dWr
• U = square integrable progressively measurable processes withvalues in U ⊂ Rd
• f is l.s.c with f − with linear growth, µ and σ Lipschitzcontinuous.
Example : Framework
• Controlled process
dX (r) = µ (X (r), νr ) dr + σ (X (r), νr ) dWr
• U = square integrable progressively measurable processes withvalues in U ⊂ Rd
• f is l.s.c with f − with linear growth, µ and σ Lipschitzcontinuous.
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X ν
t,x(T ) in L2
⇒ lim inf E[f (X ν
t′,x ′(T ))]≥ E
[f (X ν
t,x(T ))].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X ν
t,x(T ) in L2
⇒ lim inf E[f (X ν
t′,x ′(T ))]≥ E
[f (X ν
t,x(T ))].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X ν
t,x(T ) in L2
⇒ lim inf E[f (X ν
t′,x ′(T ))]≥ E
[f (X ν
t,x(T ))].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X ν
t,x(T ) in L2
⇒ lim inf E[f (X ν
t′,x ′(T ))]≥ E
[f (X ν
t,x(T ))].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν ∈ Ut : ν = ν on A ⊂ F ⇒ X νt,x = X ν
t,x on A.
A3 (Stability under concatenation) ∀ ν ∈ Ut , θ ∈ T t[t,T ] :
ν1[0,θ] + ν1(θ,T ] ∈ Ut .
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
Proof. Canonical space : W (ω) = ω. Set Ts(ω) := (ωr − ωs)r≥s andωs := (ωr∧s)r≥0.
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(Tθ(ω)(ω)) .
=
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(ω)
= J(θ(ω),X νt,x(θ)(ω); νω)
where, νω(ω) := ν(ωθ(ω) + Tθ(ω)(ω)) ∈ Uθ(ω).
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
Proof. Canonical space : W (ω) = ω. Set Ts(ω) := (ωr − ωs)r≥s andωs := (ωr∧s)r≥0.
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(Tθ(ω)(ω)) .
=
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(ω)
= J(θ(ω),X νt,x(θ)(ω); νω)
where, νω(ω) := ν(ωθ(ω) + Tθ(ω)(ω)) ∈ Uθ(ω).
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ νω ∈ Uθ(ω) s.t.
E[f(X ν
t,x(T ))|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); νω)
Proof. Canonical space : W (ω) = ω. Set Ts(ω) := (ωr − ωs)r≥s andωs := (ωr∧s)r≥0.
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(Tθ(ω)(ω)) .
=
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(ω)
= J(θ(ω),X νt,x(θ)(ω); νω)
where, νω(ω) := ν(ωθ(ω) + Tθ(ω)(ω)) ∈ Uθ(ω).
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
Proof.
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(ω),
and therefore
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf“X ν(Ts (ω))θ(ω),Xνt,x (θ)(ω)(T )(Tθ(ω)(ω))
”dP(ω)
= J(θ(ω),X νt,x(θ)(ω); ν) .
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
Proof.
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(ω),
and therefore
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf“X ν(Ts (ω))θ(ω),Xνt,x (θ)(ω)(T )(Tθ(ω)(ω))
”dP(ω)
= J(θ(ω),X νt,x(θ)(ω); ν) .
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν ∈ Us , and ν := ν1[0,θ] + ν1(θ,T ] :
E[f(X ν
t,x(T ))|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν) for P− a.e. ω ∈ Ω.
Proof.
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))
θ(ω),Xνt,x (θ)(ω) (T )(Tθ(ω)(ω))
«dP(ω),
and therefore
Eˆf`X ν
t,x(T )´|Fθ˜(ω) =
Zf“X ν(Ts (ω))θ(ω),Xνt,x (θ)(ω)(T )(Tθ(ω)(ω))
”dP(ω)
= J(θ(ω),X νt,x(θ)(ω); ν) .
Example : Super-solution property
• Want to prove that V∗ is a viscosity super-solution of
infu∈U
(−LuV∗) ≥ 0
• By usingV (t, x) ≥ sup
ν∈UϕtE[ϕ(θν ,X ν
t,x(θν))]
Example : Super-solution property
• Want to prove that V∗ is a viscosity super-solution of
infu∈U
(−LuV∗) ≥ 0
• By usingV (t, x) ≥ sup
ν∈UϕtE[ϕ(θν ,X ν
t,x(θν))]
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ(t, x) ≤ 0 on Br := |t − t0| ≤ r , |x − x0| ≤ r.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := infs ≥ tn : (s,X u
tn,xn(s)) /∈ Brso that
V (tn, xn) + ιn = ϕ(tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]
≤ E[ϕ(θn,X u
tn,xn(θn))]− r4
for some ιn → 0, i.e. V (tn, xn) ≤ E[ϕ(θn,X u
tn,xn(θn))]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X u
tn,xn(θn))]by the weak DPP.
Extensions
• Optimal control with running gain
• Optimal stopping
• Mixed optimal control/stopping, impulse control, ...
Extensions
• Optimal control with running gain
• Optimal stopping
• Mixed optimal control/stopping, impulse control, ...
Extensions
• Optimal control with running gain
• Optimal stopping
• Mixed optimal control/stopping, impulse control, ...