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Conditional Expectation Manifolds Description
, 2013
"... Description Conditional expectation manifolds are an approach to ..."
Conditional expectation
"... Goal of the lecture. The goal of this lecture is to introduce the mathematics of derivative hedging. The first part is devoted to option pricing in a discrete setting. ..."
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Goal of the lecture. The goal of this lecture is to introduce the mathematics of derivative hedging. The first part is devoted to option pricing in a discrete setting.
Conditional Expectation as . . .
, 2000
"... For a linear combination ... of random variables, we are interested in the partial derivatives of its ffquantile Q ff (u) regarded as a function of the weight vector u = (u j ..."
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For a linear combination ... of random variables, we are interested in the partial derivatives of its ffquantile Q ff (u) regarded as a function of the weight vector u = (u j
On conditional expectations of finite index
 J. Operator Theory
, 1998
"... For a conditional expectation E on a (unital) C*algebra A there exists a real number K ≥ 1 such that the mapping K · E − idA is positive if and only if there exists a real number L ≥ 1 such that the mapping L ·E −idA is completely positive, among other equivalent conditions. The estimate (min K) ≤ ..."
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Cited by 21 (5 self)
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For a conditional expectation E on a (unital) C*algebra A there exists a real number K ≥ 1 such that the mapping K · E − idA is positive if and only if there exists a real number L ≥ 1 such that the mapping L ·E −idA is completely positive, among other equivalent conditions. The estimate (min K
ON THE WORST CONDITIONAL EXPECTATION
"... Abstract. We study continuous coherent risk measures on Lp, in particular, the worst conditional expectations. We show some representation theorems for them, extending the results of Artzner, Delbaen, Eber, Heath, and Kusuoka. 1. ..."
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Abstract. We study continuous coherent risk measures on Lp, in particular, the worst conditional expectations. We show some representation theorems for them, extending the results of Artzner, Delbaen, Eber, Heath, and Kusuoka. 1.
Conditional expectation as quantile derivative
, 2000
"... For a linear combination ∑ uj Xj of random variables, we are interested in the partial derivatives of its αquantile Qα(u) regarded as a function of the weight vector u = (uj). It turns out that under suitable conditions on the joint distribution of (Xj) the derivatives exist and coincide with the c ..."
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Cited by 11 (2 self)
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with the conditional expectations of the Xi given that ∑ uj Xj takes the value Qα(u). Moreover, using this result, we deduce [ formulas for the derivatives with respect to the ui for the socalled expected shortfall E uj Xj − Qα(u) ∣ δ ∣ ∑] uj Xj ≤ Qα(u) , with δ ≥ 1 fixed. Finally, we study in some more detail
Information and the Dispersion of Conditional Expectations by
, 2013
"... We explore the intuitive idea that more information leads to greater dispersion of posterior beliefs about the expected state of the world. We consider three nested dispersion orders that are widely used in the literature, and derive the weakest information concept compatible with each order. Our ..."
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results illustrate both the potential and the limitations of using dispersion orders as information concepts: while dispersion orders on conditional expectations of the state do not qualify as information concepts, strengthening the orders to include the conditional expectations of state utilities un
Tail conditional expectations for elliptical distributions
 North American Actuarial Journal
, 2003
"... Significant changes in the insurance and financial markets are giving increasing attention to the need for developing a standard framework for risk measurement. Recently, there has been growing interest among insurance and investment experts to focus on the use of a tail conditional expectation be ..."
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Cited by 74 (18 self)
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Significant changes in the insurance and financial markets are giving increasing attention to the need for developing a standard framework for risk measurement. Recently, there has been growing interest among insurance and investment experts to focus on the use of a tail conditional expectation be
Conditional expectations and renormalization
 Multiscale Model. Simul
"... In optimal prediction methods one estimates the future behavior of underresolved systems by solving reduced systems of equations for expectations conditioned by partial data; renormalization group methods reduce the number of variables in complex systems through integration of unwanted scales. We es ..."
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Cited by 7 (0 self)
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In optimal prediction methods one estimates the future behavior of underresolved systems by solving reduced systems of equations for expectations conditioned by partial data; renormalization group methods reduce the number of variables in complex systems through integration of unwanted scales. We
ON CONVERGENCE OF CONDITIONAL EXPECTATION OPERATORS
, 1994
"... Abstract. Given an operator T: UX(Σ) → Y or T: C(H, X) → Y, one may consider the net of conditional expectation operators (Tπ) directed by refinement of the partitions π. It has been shown previously that (Tπ) does not always converge to T. This paper gives several conditions under which this conv ..."
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Abstract. Given an operator T: UX(Σ) → Y or T: C(H, X) → Y, one may consider the net of conditional expectation operators (Tπ) directed by refinement of the partitions π. It has been shown previously that (Tπ) does not always converge to T. This paper gives several conditions under which
Results 1  10
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2,905,169