Acceptance set

In financial mathematics, acceptance set is a set of acceptable future net worth which is acceptable to the regulator. It is related to risk measures.

Mathematical Definition
Given a probability space $$(\Omega,\mathcal{F},\mathbb{P})$$, and letting $$L^p = L^p(\Omega,\mathcal{F},\mathbb{P})$$ be the Lp space in the scalar case and $$L_d^p = L_d^p(\Omega,\mathcal{F},\mathbb{P})$$ in d-dimensions, then we can define acceptance sets as below.

Scalar Case
An acceptance set is a set $$A$$ satisfying:
 * 1) $$A \supseteq L^p_+$$
 * 2) $$A \cap L^p_{--} = \emptyset$$ such that $$L^p_{--} = \{X \in L^p: \forall \omega \in \Omega, X(\omega) < 0\}$$
 * 3) $$ A \cap L^p_- = \{0\}$$
 * 4) Additionally if $$A$$ is convex then it is a convex acceptance set
 * 5) And if $$A$$ is a positively homogeneous cone then it is a coherent acceptance set

Set-valued Case
An acceptance set (in a space with $$d$$ assets) is a set $$A \subseteq L^p_d$$ satisfying: Additionally, if $$A$$ is convex (a convex cone) then it is called a convex (coherent) acceptance set.
 * 1) $$u \in K_M \Rightarrow u1 \in A$$ with $$1$$ denoting the random variable that is constantly 1 $\mathbb{P}$-a.s.
 * 2) $$ u \in -\mathrm{int}K_M \Rightarrow u1 \not\in A$$
 * 3) $$A$$ is directionally closed in $$M$$ with $$A + u1 \subseteq A \; \forall u \in K_M$$
 * 4) $$A + L^p_d(K) \subseteq A$$

Note that $$K_M = K \cap M$$ where $$K$$ is a constant solvency cone and $$M$$ is the set of portfolios of the $$m$$ reference assets.

Relation to Risk Measures
An acceptance set is convex (coherent) if and only if the corresponding risk measure is convex (coherent). As defined below it can be shown that $$R_{A_R}(X) = R(X)$$ and $$A_{R_A} = A$$.

Risk Measure to Acceptance Set

 * If $$\rho$$ is a (scalar) risk measure then $$A_{\rho} = \{X \in L^p: \rho(X) \leq 0\}$$ is an acceptance set.
 * If $$R$$ is a set-valued risk measure then $$A_R = \{X \in L^p_d: 0 \in R(X)\}$$ is an acceptance set.

Acceptance Set to Risk Measure

 * If $$A$$ is an acceptance set (in 1-d) then $$\rho_A(X) = \inf\{u \in \mathbb{R}: X + u1 \in A\}$$ defines a (scalar) risk measure.
 * If $$A$$ is an acceptance set then $$R_A(X) = \{u \in M: X + u1 \in A\}$$ is a set-valued risk measure.

Superhedging price
The acceptance set associated with the superhedging price is the negative of the set of values of a self-financing portfolio at the terminal time. That is
 * $$A = \{-V_T: (V_t)_{t=0}^T \text{ is the price of a self-financing portfolio at each time}\}$$.

Entropic risk measure
The acceptance set associated with the entropic risk measure is the set of payoffs with positive expected utility. That is
 * $$A = \{X \in L^p(\mathcal{F}): E[u(X)] \geq 0\} = \{X \in L^p(\mathcal{F}): E\left[e^{-\theta X}\right] \leq 1\}$$

where $$u(X)$$ is the exponential utility function.