Maximal inequality for the Itō integral
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Let $W$ be a Brownian motion and $X$ be a predictable process with $$operatorname Eleft[int_0^t|X_s|^2:{rm d}sright]<infty;;;text{for all }tge0.$$ Now, let $pge2$.
How can we show that $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le Coperatorname Eleft[left|int_0^tleft|X_sright|^2:{rm d}sright|^{frac p2}right]tag1$$ for some $Cge0$.
Let $$q:=frac p{p-1}.$$ Clearly, we somehow need to apply Doob's inequality and the Itō formula. Doob's inequality yields $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le q^poperatorname Eleft[left(left|int_0^tX_s:{rm d}W_sright|^2right)^{frac p2}right]tag2.$$ How do we need to proceed from here?
probability-theory stochastic-processes stochastic-calculus stochastic-integrals stochastic-analysis
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$begingroup$
Let $W$ be a Brownian motion and $X$ be a predictable process with $$operatorname Eleft[int_0^t|X_s|^2:{rm d}sright]<infty;;;text{for all }tge0.$$ Now, let $pge2$.
How can we show that $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le Coperatorname Eleft[left|int_0^tleft|X_sright|^2:{rm d}sright|^{frac p2}right]tag1$$ for some $Cge0$.
Let $$q:=frac p{p-1}.$$ Clearly, we somehow need to apply Doob's inequality and the Itō formula. Doob's inequality yields $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le q^poperatorname Eleft[left(left|int_0^tX_s:{rm d}W_sright|^2right)^{frac p2}right]tag2.$$ How do we need to proceed from here?
probability-theory stochastic-processes stochastic-calculus stochastic-integrals stochastic-analysis
$endgroup$
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$begingroup$
Let $W$ be a Brownian motion and $X$ be a predictable process with $$operatorname Eleft[int_0^t|X_s|^2:{rm d}sright]<infty;;;text{for all }tge0.$$ Now, let $pge2$.
How can we show that $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le Coperatorname Eleft[left|int_0^tleft|X_sright|^2:{rm d}sright|^{frac p2}right]tag1$$ for some $Cge0$.
Let $$q:=frac p{p-1}.$$ Clearly, we somehow need to apply Doob's inequality and the Itō formula. Doob's inequality yields $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le q^poperatorname Eleft[left(left|int_0^tX_s:{rm d}W_sright|^2right)^{frac p2}right]tag2.$$ How do we need to proceed from here?
probability-theory stochastic-processes stochastic-calculus stochastic-integrals stochastic-analysis
$endgroup$
Let $W$ be a Brownian motion and $X$ be a predictable process with $$operatorname Eleft[int_0^t|X_s|^2:{rm d}sright]<infty;;;text{for all }tge0.$$ Now, let $pge2$.
How can we show that $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le Coperatorname Eleft[left|int_0^tleft|X_sright|^2:{rm d}sright|^{frac p2}right]tag1$$ for some $Cge0$.
Let $$q:=frac p{p-1}.$$ Clearly, we somehow need to apply Doob's inequality and the Itō formula. Doob's inequality yields $$operatorname Eleft[sup_{sin[0,:t]}left|int_0^sX_r:{rm d}W_rright|^pright]le q^poperatorname Eleft[left(left|int_0^tX_s:{rm d}W_sright|^2right)^{frac p2}right]tag2.$$ How do we need to proceed from here?
probability-theory stochastic-processes stochastic-calculus stochastic-integrals stochastic-analysis
probability-theory stochastic-processes stochastic-calculus stochastic-integrals stochastic-analysis
asked Dec 22 '18 at 0:29
0xbadf00d0xbadf00d
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$begingroup$
If $p=2$ then the assertion is a direct consequence of Itô's isometry. From now on I will assume that $p>2$. Moreover, by using a standard stopping technique, we may assume without loss of generality that $$M_t := int_0^t X_s , dW_s$$ and its quadratic variation $$langle M rangle_t = int_0^t X_s^2 , ds$$ are bounded processes. As $p > 2$ the mapping $x mapsto |x|^p$ is twice continuously differentiable, and therefore an application of Itô's formula gives
$$|M_t|^p = p int_0^t |M_s|^{p-1} dM_s + frac{p(p-1)}{2} int_0^t |M_s|^{p-2} , dlangle M rangle_s.$$
Since $M$ is bounded, the first term on the right-hand side is a martingale; thus
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p mathbb{E}(|M_t|^p) = q^p frac{p (p-1)}{2} mathbb{E} int_0^t |M_s|^{p-2} , dlangle M rangle_s$$
and so
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2} mathbb{E} left( langle M rangle_t sup_{s leq t} |M_s|^{p-2} right).$$
Now an application of Hölder's inequality yields
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2}left( mathbb{E} left[ sup_{s leq t} |M_s|^p right] right)^{1-2/p} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}.$$
Hence,
$$left(mathbb{E}left[ sup_{s leq t} |M_s|^p right] right)^{2/p}leq q^p frac{p(p-1)}{2} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}$$
and this proves the assertion.
Remark: The Burkholder-Davis-Gundy inequality states that $$mathbb{E} left( sup_{s leq t} left| int_0^s X_s , dW_s right|^p right)$$ is comparable with $$mathbb{E} left( left| int_0^t X_s^2 , ds right|^{p/2} right),$$
see e.g. Brownian Motion - An Introduction to Stochastic Processes by Schilling & Partzsch for a proof.
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1 Answer
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$begingroup$
If $p=2$ then the assertion is a direct consequence of Itô's isometry. From now on I will assume that $p>2$. Moreover, by using a standard stopping technique, we may assume without loss of generality that $$M_t := int_0^t X_s , dW_s$$ and its quadratic variation $$langle M rangle_t = int_0^t X_s^2 , ds$$ are bounded processes. As $p > 2$ the mapping $x mapsto |x|^p$ is twice continuously differentiable, and therefore an application of Itô's formula gives
$$|M_t|^p = p int_0^t |M_s|^{p-1} dM_s + frac{p(p-1)}{2} int_0^t |M_s|^{p-2} , dlangle M rangle_s.$$
Since $M$ is bounded, the first term on the right-hand side is a martingale; thus
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p mathbb{E}(|M_t|^p) = q^p frac{p (p-1)}{2} mathbb{E} int_0^t |M_s|^{p-2} , dlangle M rangle_s$$
and so
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2} mathbb{E} left( langle M rangle_t sup_{s leq t} |M_s|^{p-2} right).$$
Now an application of Hölder's inequality yields
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2}left( mathbb{E} left[ sup_{s leq t} |M_s|^p right] right)^{1-2/p} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}.$$
Hence,
$$left(mathbb{E}left[ sup_{s leq t} |M_s|^p right] right)^{2/p}leq q^p frac{p(p-1)}{2} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}$$
and this proves the assertion.
Remark: The Burkholder-Davis-Gundy inequality states that $$mathbb{E} left( sup_{s leq t} left| int_0^s X_s , dW_s right|^p right)$$ is comparable with $$mathbb{E} left( left| int_0^t X_s^2 , ds right|^{p/2} right),$$
see e.g. Brownian Motion - An Introduction to Stochastic Processes by Schilling & Partzsch for a proof.
$endgroup$
add a comment |
$begingroup$
If $p=2$ then the assertion is a direct consequence of Itô's isometry. From now on I will assume that $p>2$. Moreover, by using a standard stopping technique, we may assume without loss of generality that $$M_t := int_0^t X_s , dW_s$$ and its quadratic variation $$langle M rangle_t = int_0^t X_s^2 , ds$$ are bounded processes. As $p > 2$ the mapping $x mapsto |x|^p$ is twice continuously differentiable, and therefore an application of Itô's formula gives
$$|M_t|^p = p int_0^t |M_s|^{p-1} dM_s + frac{p(p-1)}{2} int_0^t |M_s|^{p-2} , dlangle M rangle_s.$$
Since $M$ is bounded, the first term on the right-hand side is a martingale; thus
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p mathbb{E}(|M_t|^p) = q^p frac{p (p-1)}{2} mathbb{E} int_0^t |M_s|^{p-2} , dlangle M rangle_s$$
and so
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2} mathbb{E} left( langle M rangle_t sup_{s leq t} |M_s|^{p-2} right).$$
Now an application of Hölder's inequality yields
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2}left( mathbb{E} left[ sup_{s leq t} |M_s|^p right] right)^{1-2/p} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}.$$
Hence,
$$left(mathbb{E}left[ sup_{s leq t} |M_s|^p right] right)^{2/p}leq q^p frac{p(p-1)}{2} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}$$
and this proves the assertion.
Remark: The Burkholder-Davis-Gundy inequality states that $$mathbb{E} left( sup_{s leq t} left| int_0^s X_s , dW_s right|^p right)$$ is comparable with $$mathbb{E} left( left| int_0^t X_s^2 , ds right|^{p/2} right),$$
see e.g. Brownian Motion - An Introduction to Stochastic Processes by Schilling & Partzsch for a proof.
$endgroup$
add a comment |
$begingroup$
If $p=2$ then the assertion is a direct consequence of Itô's isometry. From now on I will assume that $p>2$. Moreover, by using a standard stopping technique, we may assume without loss of generality that $$M_t := int_0^t X_s , dW_s$$ and its quadratic variation $$langle M rangle_t = int_0^t X_s^2 , ds$$ are bounded processes. As $p > 2$ the mapping $x mapsto |x|^p$ is twice continuously differentiable, and therefore an application of Itô's formula gives
$$|M_t|^p = p int_0^t |M_s|^{p-1} dM_s + frac{p(p-1)}{2} int_0^t |M_s|^{p-2} , dlangle M rangle_s.$$
Since $M$ is bounded, the first term on the right-hand side is a martingale; thus
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p mathbb{E}(|M_t|^p) = q^p frac{p (p-1)}{2} mathbb{E} int_0^t |M_s|^{p-2} , dlangle M rangle_s$$
and so
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2} mathbb{E} left( langle M rangle_t sup_{s leq t} |M_s|^{p-2} right).$$
Now an application of Hölder's inequality yields
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2}left( mathbb{E} left[ sup_{s leq t} |M_s|^p right] right)^{1-2/p} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}.$$
Hence,
$$left(mathbb{E}left[ sup_{s leq t} |M_s|^p right] right)^{2/p}leq q^p frac{p(p-1)}{2} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}$$
and this proves the assertion.
Remark: The Burkholder-Davis-Gundy inequality states that $$mathbb{E} left( sup_{s leq t} left| int_0^s X_s , dW_s right|^p right)$$ is comparable with $$mathbb{E} left( left| int_0^t X_s^2 , ds right|^{p/2} right),$$
see e.g. Brownian Motion - An Introduction to Stochastic Processes by Schilling & Partzsch for a proof.
$endgroup$
If $p=2$ then the assertion is a direct consequence of Itô's isometry. From now on I will assume that $p>2$. Moreover, by using a standard stopping technique, we may assume without loss of generality that $$M_t := int_0^t X_s , dW_s$$ and its quadratic variation $$langle M rangle_t = int_0^t X_s^2 , ds$$ are bounded processes. As $p > 2$ the mapping $x mapsto |x|^p$ is twice continuously differentiable, and therefore an application of Itô's formula gives
$$|M_t|^p = p int_0^t |M_s|^{p-1} dM_s + frac{p(p-1)}{2} int_0^t |M_s|^{p-2} , dlangle M rangle_s.$$
Since $M$ is bounded, the first term on the right-hand side is a martingale; thus
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p mathbb{E}(|M_t|^p) = q^p frac{p (p-1)}{2} mathbb{E} int_0^t |M_s|^{p-2} , dlangle M rangle_s$$
and so
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2} mathbb{E} left( langle M rangle_t sup_{s leq t} |M_s|^{p-2} right).$$
Now an application of Hölder's inequality yields
$$mathbb{E}left( sup_{s leq t} |M_s|^p right) leq q^p frac{p(p-1)}{2}left( mathbb{E} left[ sup_{s leq t} |M_s|^p right] right)^{1-2/p} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}.$$
Hence,
$$left(mathbb{E}left[ sup_{s leq t} |M_s|^p right] right)^{2/p}leq q^p frac{p(p-1)}{2} (mathbb{E}[langle M rangle_t^{p/2}]^{2/p}$$
and this proves the assertion.
Remark: The Burkholder-Davis-Gundy inequality states that $$mathbb{E} left( sup_{s leq t} left| int_0^s X_s , dW_s right|^p right)$$ is comparable with $$mathbb{E} left( left| int_0^t X_s^2 , ds right|^{p/2} right),$$
see e.g. Brownian Motion - An Introduction to Stochastic Processes by Schilling & Partzsch for a proof.
edited Dec 30 '18 at 11:14
answered Dec 22 '18 at 8:22
sazsaz
81.9k862131
81.9k862131
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