Scholarlink

<p>This paper examines whether volatility management and factor-based mean–variance optimization improve out-of-sample portfolio performance relative to simple diversification benchmarks. Using nine equity factors from 1976 to 2025, the analysis compares recursive mean–variance portfolios, volatility-managed factors, equal-weight 1/N portfolios, and volatility-managed 1/N portfolios across multiple rolling windows, subperiods, and VIX regimes. Although volatility management improves the Sharpe ratios of several individual factors, these gains do not translate into robust portfolio-level outperformance once estimation risk and recursive implementation are considered. Optimized portfolios generally fail to be outperformed simple diversified benchmarks, while dynamic factor-selection strategies suffer from instability and look-ahead bias. Overall, the evidence suggests that simple diversification remains remarkably difficult to outperform in risk-adjusted terms, even when sophisticated volatility-management and optimization techniques are employed.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

When simplicity beats optimization: evidence from factor timing, volatility management, and the 1/N benchmark

  • 期刊论文

  • 发表日期：

    2026年7月18日

查看全文
  • Xuan Feng

摘要

This paper examines whether volatility management and factor-based mean–variance optimization improve out-of-sample portfolio performance relative to simple diversification benchmarks. Using nine equity factors from 1976 to 2025, the analysis compares recursive mean–variance portfolios, volatility-managed factors, equal-weight 1/N portfolios, and volatility-managed 1/N portfolios across multiple rolling windows, subperiods, and VIX regimes. Although volatility management improves the Sharpe ratios of several individual factors, these gains do not translate into robust portfolio-level outperformance once estimation risk and recursive implementation are considered. Optimized portfolios generally fail to be outperformed simple diversified benchmarks, while dynamic factor-selection strategies suffer from instability and look-ahead bias. Overall, the evidence suggests that simple diversification remains remarkably difficult to outperform in risk-adjusted terms, even when sophisticated volatility-management and optimization techniques are employed.