A white noise approach to insider trading
Bernt {\O}ksendal, Elin R{\o}se
TL;DR
This paper introduces a novel mathematical framework using white noise theory and advanced stochastic calculus to solve the optimal portfolio problem for insiders with logarithmic utility.
Contribution
It develops a new approach leveraging white noise theory, stochastic forward integrals, and Donsker delta functions for insider trading models.
Findings
Provides explicit solutions for insider portfolio optimization.
Demonstrates the effectiveness of white noise methods in financial mathematics.
Extends the mathematical tools available for insider trading analysis.
Abstract
We present a new approach to the optimal portfolio problem for an insider with logarithmic utility. Our method is based on white noise theory, stochastic forward integrals, Hida-Malliavin calculus and the Donsker delta function.
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Taxonomy
TopicsStochastic processes and financial applications · Financial Markets and Investment Strategies · Financial Risk and Volatility Modeling