ﻻ يوجد ملخص باللغة العربية
We consider the problem of optimal inside portfolio $pi(t)$ in a financial market with a corresponding wealth process $X(t)=X^{pi}(t)$ modelled by begin{align}label{eq0.1} begin{cases} dX(t)&=pi(t)X(t)[alpha(t)dt+beta(t)dB(t)]; quad tin[0, T] X(0)&=x_0>0, end{cases} end{align} where $B(cdot)$ is a Brownian motion. We assume that the insider at time $t$ has access to market information $varepsilon_t>0$ units ahead of time, in addition to the history of the market up to time $t$. The problem is to find an insider portfolio $pi^{*}$ which maximizes the expected logarithmic utility $J(pi)$ of the terminal wealth, i.e. such that $$sup_{pi}J(pi)= J(pi^{*}), text {where } J(pi)= mathbb{E}[log(X^{pi}(T))].$$ The insider market is called emph{viable} if this value is finite. We study under what inside information flow $mathbb{H}$ the insider market is viable or not. For example, assume that for all $t<T$ the insider knows the value of $B(t+epsilon_t)$, where $t + epsilon_t geq T$ converges monotonically to $T$ from above as $t$ goes to $T$ from below. Then (assuming that the insider has a perfect memory) at time $t$ she has the inside information $mathcal{H}_t$, consisting of the history $mathcal{F}_t$ of $B(s); 0 leq s leq t$ plus all the values of Brownian motion in the interval $[t+epsilon_t, epsilon_0]$, i.e. we have the enlarged filtration begin{equation}label{eq0.2} mathbb{H}={mathcal{H}_t}_{tin[0.T]},quad mathcal{H}_t=mathcal{F}_tveesigma(B(t+epsilon_t+r),0leq r leq epsilon_0-t-epsilon_t), forall tin [0,T]. end{equation} Using forward integrals, Hida-Malliavin calculus and Donsker delta functionals we show that if $$int_0^Tfrac{1}{varepsilon_t}dt=infty,$$ then the insider market is not viable.
An open market is a subset of an entire equity market composed of a certain fixed number of top capitalization stocks. Though the number of stocks in the open market is fixed, the constituents of the market change over time as each companys rank by i
In this paper, the Kyle model of insider trading is extended by characterizing the trading volume with long memory and allowing the noise trading volatility to follow a general stochastic process. Under this newly revised model, the equilibrium condi
The objective of this paper is to introduce the theory of option pricing for markets with informed traders within the framework of dynamic asset pricing theory. We introduce new models for option pricing for informed traders in complete markets where
Using agent-based modelling, empirical evidence and physical ideas, such as the energy function and the fact that the phase space must have twice the dimension of the configuration space, we argue that the stochastic differential equations which desc
We consider thin incomplete financial markets, where traders with heterogeneous preferences and risk exposures have motive to behave strategically regarding the demand schedules they submit, thereby impacting prices and allocations. We argue that tra