---
title: Misallocated, Not Mispriced: The Resolution Limit of Local Strength in the Factor Zoo
url: https://www.ml-quant.com/papers/ssrn/7607684/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-16
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7607684
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7607684
featured: 2026-10-16
citations: unknown
topic: Asset Pricing & Factors
---


# Misallocated, Not Mispriced: The Resolution Limit of Local Strength in the Factor Zoo

Rejected factors earn 1.30 Sharpe in their home market versus 0.85 overall, yielding 3.8% six-factor alpha per year through venue reallocation constrained by signal-to-noise limits.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7607684
- Identifier: SSRN 7607684
- Released: 2026-10-14
- First featured: Quant Letter No. 135 (2026-10-16): https://www.ml-quant.com/issues/2026-10-16/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Asset Pricing & Factors
- Authors: Huannian Jin

## Related

- [Optimal Investment and Consumption in a Stochastic Factor Model](https://www.ml-quant.com/papers/arxiv/2509.09452/): The article discusses optimal investment and consumption in an incomplete stochastic factor model, offering a comprehensive characterization of the problem's well-posedness and an efficient numerical algorithm for computing the value function.
- [Dynamic Factor Correlation Model](https://www.ml-quant.com/papers/arxiv/2503.01080/): A new model with a unique variation-free parameterization of factor loadings shows adaptability and scalability in both small and large asset return environments.
- [Unveiling True Talent: The Soccer Factor Model for Skill Evaluation](https://www.ml-quant.com/papers/arxiv/2412.05911/): The Soccer Factor Model (SFM) is a new method for evaluating soccer players' performance independently from their team's influence, allowing for more accurate comparisons.
- [Block-diagonal idiosyncratic covariance estimation in high-dimensional factor models for financial time series](https://www.ml-quant.com/papers/doi/10-1016-j-jocs-2024-102348/): The research proposes a method for estimating high-dimensional covariance matrices in latent factor models by clustering residual series, focusing on the idiosyncratic component.
- [When can weak latent factors be statistically inferred?](https://www.ml-quant.com/papers/arxiv/2407.03616/): The article introduces a new theory for principal component analysis (PCA) under the weak factor model. This theory accounts for cross-sectional dependent components and provides finite-sample characterizations for estimation error and statistical inference uncertainty level, improving upon previous research.
- [Commodity Futures Characteristics and Asset Pricing Models](https://www.ml-quant.com/papers/ssrn/4746258/): The article shows that a latent-factor model using the Instrumented Principal Component Analysis methodology surpasses existing models in explaining variations in commodity futures returns, with momentum, expected shortfall, and idiosyncratic volatility as key factors.
