The article explores how to optimize volatility positions by treating the process as a linear problem with constraints. By using investor expectations and risk parameters, the researchers show how to manage position risk effectively. They use FDA events to model implied volatility drops, which can help investors make better decisions. The study demonstrates that using interior-point solvers can lead to optimal positions with improved payoff structures compared to traditional trading methods. This approach can also be applied dynamically to manage risk in portfolios with multiple options and stock hedges.