- Source: Martingale representation theorem
In probability theory, the martingale representation theorem states that a random variable that is measurable with respect to the filtration generated by a Brownian motion can be written in terms of an Itô integral with respect to this Brownian motion.
The theorem only asserts the existence of the representation and does not help to find it explicitly; it is possible in many cases to determine the form of the representation using Malliavin calculus.
Similar theorems also exist for martingales on filtrations induced by jump processes, for example, by Markov chains.
Statement
Let
B
t
{\displaystyle B_{t}}
be a Brownian motion on a standard filtered probability space
(
Ω
,
F
,
F
t
,
P
)
{\displaystyle (\Omega ,{\mathcal {F}},{\mathcal {F}}_{t},P)}
and let
G
t
{\displaystyle {\mathcal {G}}_{t}}
be the augmented filtration generated by
B
{\displaystyle B}
. If X is a square integrable random variable measurable with respect to
G
∞
{\displaystyle {\mathcal {G}}_{\infty }}
, then there exists a predictable process C which is adapted with respect to
G
t
,
{\displaystyle {\mathcal {G}}_{t},}
such that
X
=
E
(
X
)
+
∫
0
∞
C
s
d
B
s
.
{\displaystyle X=E(X)+\int _{0}^{\infty }C_{s}\,dB_{s}.}
Consequently,
E
(
X
|
G
t
)
=
E
(
X
)
+
∫
0
t
C
s
d
B
s
.
{\displaystyle E(X|{\mathcal {G}}_{t})=E(X)+\int _{0}^{t}C_{s}\,dB_{s}.}
Application in finance
The martingale representation theorem can be used to establish the existence
of a hedging strategy.
Suppose that
(
M
t
)
0
≤
t
<
∞
{\displaystyle \left(M_{t}\right)_{0\leq t<\infty }}
is a Q-martingale process, whose volatility
σ
t
{\displaystyle \sigma _{t}}
is always non-zero.
Then, if
(
N
t
)
0
≤
t
<
∞
{\displaystyle \left(N_{t}\right)_{0\leq t<\infty }}
is any other Q-martingale, there exists an
F
{\displaystyle {\mathcal {F}}}
-previsible process
φ
{\displaystyle \varphi }
, unique up to sets of measure 0, such that
∫
0
T
φ
t
2
σ
t
2
d
t
<
∞
{\displaystyle \int _{0}^{T}\varphi _{t}^{2}\sigma _{t}^{2}\,dt<\infty }
with probability one, and N can be written as:
N
t
=
N
0
+
∫
0
t
φ
s
d
M
s
.
{\displaystyle N_{t}=N_{0}+\int _{0}^{t}\varphi _{s}\,dM_{s}.}
The replicating strategy is defined to be:
hold
φ
t
{\displaystyle \varphi _{t}}
units of the stock at the time t, and
hold
ψ
t
B
t
=
C
t
−
φ
t
Z
t
{\displaystyle \psi _{t}B_{t}=C_{t}-\varphi _{t}Z_{t}}
units of the bond.
where
Z
t
{\displaystyle Z_{t}}
is the stock price discounted by the bond price to time
t
{\displaystyle t}
and
C
t
{\displaystyle C_{t}}
is the expected payoff of the option at time
t
{\displaystyle t}
.
At the expiration day T, the value of the portfolio is:
V
T
=
φ
T
S
T
+
ψ
T
B
T
=
C
T
=
X
{\displaystyle V_{T}=\varphi _{T}S_{T}+\psi _{T}B_{T}=C_{T}=X}
and it is easy to check that the strategy is self-financing: the change in the value of the portfolio only depends on the change of the asset prices
(
d
V
t
=
φ
t
d
S
t
+
ψ
t
d
B
t
)
{\displaystyle \left(dV_{t}=\varphi _{t}\,dS_{t}+\psi _{t}\,dB_{t}\right)}
.
See also
Backward stochastic differential equation
References
Montin, Benoît. (2002) "Stochastic Processes Applied in Finance"
Elliott, Robert (1976) "Stochastic Integrals for Martingales of a Jump Process with Partially Accessible Jump Times", Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete, 36, 213–226
Kata Kunci Pencarian:
- Martingale representation theorem
- Martingale (probability theory)
- Itô calculus
- Optional stopping theorem
- Risk-neutral measure
- List of theorems
- Backward stochastic differential equation
- List of probability topics
- Mathematical finance
- Doob's martingale inequality
