Global Allocation Research Report
Helps You Manage Drawdowns Without Losing Upside Potential
Adapt Your ETF Allocations using Advanced Machine Learning
Benefit from Unique, Actionable Insights
Augment and Sharpen your Decisions
Adapt Your ETF Allocations to Market Realities
Our Global Allocation Research report uses the Laplace Advanced Machine Learning (ML) platform to help you shift to safe assets during turbulent markets and to growth assets when all is clear. Allocation recommendations are 100% transparent, consisting entirely of low-cost, highly liquid ETFs.
Published on the last trading day of the month, our report analyzes the expected volatility and returns for each of the world’s major asset classes and ranks the relative attractiveness of all eleven S&P 500 sectors for the upcoming month. The report also discusses the key factors driving the platform’s allocation recommendations, providing you with unique, emotion-free insights to help sharpen your investment decisions and refine your discussions with clients.
Research Report Contents
Global ETF Allocation Strategy
- Recommends allocations within a set of 15 low cost ETFs, each representing an asset class.
- Gain intelligence on the most relevant market forces currently at play.
- Augment your existing research and use the insights to adjust the tactical portion of client portfolios.
S&P 500 Sector Insights
- Predicts relative attractiveness for the next month for all 11 sectors of the S&P 500 using advanced machine learning.
- Use it to overweight or underweight sectors and improve performance relative to the S&P 500.
" I've been very impressed by the comprehensive approach used to ensure the algorithm is robust under a wide range of market situations. The depth of analysis and statistical rigor gives me the confidence I need to use it with my clients. "