Adaptive Asset Allocation (1)

This research paper by Sefirot Financial Research explores the principles and practical applications of Adaptive Asset Allocation - a dynamic portfolio management framework designed to adjust asset weights in response to evolving market conditions. Drawing on a dataset of 10 diversified ETFs across equities and bonds from 2009 to 2019, the study rigorously backtests five core strategies and three hybrid combinations, benchmarked against an Equally Weighted portfolio. The analysis provides investors with a structured comparison of risk-adjusted performance metrics, offering actionable insights into how dynamic rebalancing can - and cannot - enhance portfolio efficiency relative to a passive approach.

Key topics covered:

• Portfolio construction methodologies: Equally Weighted, Momentum, Minimum Variance, Volatility Parity, and Risk Parity

• Risk-adjusted performance analysis using Sharpe Ratio, standard deviation, and maximum drawdown

• Hybrid strategy evaluation: Momentum combined with Minimum Variance, Volatility Parity, and Risk Parity

• Comparative backtesting across a decade of multi-asset ETF data

• Insights into the trade-offs between return generation and downside risk management