Active Portfolio Management in Concentrated Equity Markets
Abstract
The equal-weighted portfolio is a passive, rule-based strategy that has historically been difficult to outperform, delivering higher returns than the capitalization-weighted "market" benchmark across many markets and periods. Stochastic portfolio theory (SPT) reveals that this relative performance is regime dependent, with the equal-weighted portfolio underperforming during periods of increasing market concentration and high correlations, particularly market bubbles. These observations have motivated us to formulate and solve a stochastic control problem in which an investor actively allocates between the equal-weighted and market portfolios. The investor bases their allocation decisions on forecasts made under a flexible stochastic diversity--dispersion (SDD) model. Using a quadratic surrogate for implementation frictions, we characterize the optimal allocation through a linear forward--backward SDE and obtain an explicit "aiming in front of a moving target" representation of the optimal trading rate, in the spirit of Gârleanu and Pedersen. The penalty parameters are calibrated in sample to match the cumulative wealth effect of proportional transaction costs, while out-of-sample performance is evaluated with those costs deducted directly from portfolio wealth. Using historical S&P 500 data, we show that a mean-reverting SDD specification reproduces several empirical features of market diversity and dispersion. In out-of-sample backtests from 1995 to 2024, the resulting strategies deliver higher cumulative net returns than both the equal-weighted and market portfolios, and higher information ratios than the equal-weighted portfolio after 15-basis-point proportional transaction costs.
Related
- A nested factor model for equity markets: reconciling multifractal stock returns and rough index volatilities
- Dynamic Return Spillovers and Heterogeneous Responses Across Energy Equity Markets Under Demand–Supply Risks: A Mixed-Methods Analysis Using Chinese News Texts
- Cost-Sensitive Online Window Size Selection for Portfolio Management
- Fast, cheap and sustainable: armament portfolio arbitration under attrition, lead time and political discontinuity
- Weighted selection from elliptical distributions: a stochastic representation and an application to portfolio separation
BibTeX
@misc{ceco2026active,
title = {{Active Portfolio Management in Concentrated Equity Markets}},
author = {Brian Ceco and Xiaofei Shi and Ting-Kam Leonard Wong},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.27113},
eprint = {2609.27113},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.27113},
}
RIS
TY - UNPB
TI - Active Portfolio Management in Concentrated Equity Markets
AU - Brian Ceco
AU - Xiaofei Shi
AU - Ting-Kam Leonard Wong
PY - 2026
DA - 2026/10/14
PB - arXiv
DO - 10.48550/arxiv.2609.27113
UR - https://arxiv.org/abs/2609.27113
AB - The equal-weighted portfolio is a passive, rule-based strategy that has historically been difficult to outperform, delivering higher returns than the capitalization-weighted "market" benchmark across many markets and periods. Stochastic portfolio theory (SPT) reveals that this relative performance is regime dependent, with the equal-weighted portfolio underperforming during periods of increasing market concentration and high correlations, particularly market bubbles. These observations have motivated us to formulate and solve a stochastic control problem in which an investor actively allocates between the equal-weighted and market portfolios. The investor bases their allocation decisions on forecasts made under a flexible stochastic diversity--dispersion (SDD) model. Using a quadratic surrogate for implementation frictions, we characterize the optimal allocation through a linear forward--backward SDE and obtain an explicit "aiming in front of a moving target" representation of the optimal trading rate, in the spirit of Gârleanu and Pedersen. The penalty parameters are calibrated in sample to match the cumulative wealth effect of proportional transaction costs, while out-of-sample performance is evaluated with those costs deducted directly from portfolio wealth. Using historical S&P 500 data, we show that a mean-reverting SDD specification reproduces several empirical features of market diversity and dispersion. In out-of-sample backtests from 1995 to 2024, the resulting strategies deliver higher cumulative net returns than both the equal-weighted and market portfolios, and higher information ratios than the equal-weighted portfolio after 15-basis-point proportional transaction costs.
ER -