Portfolio Optimization Meets AI
Over 1,500,000 existing data sets extracted from the current U.S. insurance market are analyzed by AI to define the efficient frontier line. Each point on the frontier represents a maximized expected return at the risk level selected. This method allows PWS to recommend optimal solution according to client’s risk preference.
Cloud Computing and Data Analysis
Using cloud computing, PWS simulates alternative financial vehicles’ performance according to past macro-economics trend and market record. The black lines in the graph represent PWS sample returns with different designs. With robust data analysis, PWS is able to present advance analytical metrics to clients.
Optimized Return Simulations
PWS financial experts use Monte Carlo simulations and Stochastic Modeling to simulate the risks that may arise under different economic conditions to maximize chances in achieving absolute return. This stress test methodology optimizes risk-adjusted return for protection during down-markets, rather than pretty numbers on paper.
