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Beyond the Monte Carlo: A New Approach to Unified, Total Wealth Strategies

Topic

Risk Management and Insurance Planning

Program ID

333279

Hours

1

Format

Live / Conference Session

Complexity

Intermediate

Description

A financial advisor's most important delivery is advice. While our industry has made strides in packaging ""risk tolerance portfolios"" and ""probability of success plans"" into sleek software, we haven't seen the same level of innovation applied to advice methodology itself. So, how can we deliver more robust advice to clients? As it turns out, risk questionnaires aren’t particularly useful for building personalized portfolios, and Monte Carlo simulations aren't a substitute for real risk management. We can do better, but we'll need to rethink some of the methods underlying traditional planning and investment advice. In this session, Jeff Coyle, founder of Libretto and former advisor with 25+ years of experience managing ultra-high-net-worth clients, will introduce a new framework for lifecycle advice that moves beyond the ""risk tolerance ecosystem"" in favor of an outcomes-oriented approach to planning and investing.

Learning Objectives

• Compare “liability-matching” methods with “risk tolerance portfolios” and “probability of success plans” to tailor client strategies effectively. • Analyze how to integrate homes, mortgages, alternatives, private assets, social security, human capital, and other resources into holistic portfolios. • Identify and apply risk management methods to mitigate the impact of stressful life events on clients’ financial well-being. • Analyze hedges, reserves, insurance, diversification, and life adjustments to meet clients’ evolving needs over their lifetimes. • Combine personalized asset allocation, risk management, and wealth management into cohesive client strategies. • Apply a decision-making framework and financial offsets to address client-specific risks in uncertain conditions. • Select rigorous, iterative, and engaging client experiences for effective financial planning.