“学海拾珠”系列之二百三十六：基于层级动量的投资组合构建

Core Insights - The report presents a novel investment portfolio construction method that combines stock price momentum with hierarchical clustering (HC) to address the instability and concentration issues of Markowitz mean-variance (MV) portfolio weights [2][22] - The proposed Hierarchical Momentum (HM) strategy shows potential applicability in various domains such as stock portfolio construction, ETF portfolio construction, and asset allocation in the domestic market [2][22] Hierarchical Momentum Strategy - The HM strategy derives a distance function from the Pearson correlation coefficients between asset returns, using a bottom-up recursive approach to cluster assets based on proximity, resulting in a dendrogram [3][24] - At a certain height in the dendrogram, a horizontal cut is made to divide the tree into n clusters, identifying the assets with the highest momentum scores within each cluster while assigning zero weight to those with negative momentum scores [3][24] Empirical Results - The backtesting period spans from June 1997 to August 2022, utilizing a high-dimensional dataset from the MSCI All Country World Index (ACWI), which includes large-cap and mid-cap stocks from 23 developed and 24 emerging markets [5][43] - After accounting for transaction costs, the HM strategy outperforms all other strategies in terms of cumulative returns, average returns, risk-adjusted returns (Sharpe and Sortino ratios), and risk metrics (volatility and maximum drawdown) [5][55] - The HM strategy demonstrates improved stability in industry allocation compared to the Maximum Momentum (MM) and Threshold Momentum (TM) strategies, which are known for their potential large drawdown issues [5][56] Methodology - The HM portfolio construction method does not require the inversion of the covariance matrix, instead relying on a hierarchical clustering approach to reduce dimensionality and ensure sparse diversification [24][68] - The method involves two main steps: applying hierarchical clustering to create a distance matrix and then constructing portfolio weights based on the hierarchical structure and momentum scores [24][38] Conclusion - The report emphasizes the importance of sparse diversification in constructing superior investment portfolios, particularly in high-dimensional environments where traditional methods may underperform [68][69] - The HM strategy effectively captures momentum premiums while mitigating risks associated with traditional momentum strategies, demonstrating its robustness across different economic conditions [68][69]