Preprint
Article

This version is not peer-reviewed.

The Flow-Performance Relationship and Behavioral Biases: Evidence from Spanish Mutual Fund Flows

Submitted:

05 March 2026

Posted:

09 March 2026

You are already at the latest version

Abstract
This study analyzes the relationship between stock market returns and investment flows in investment funds in Spain. Through a quantitative analysis covering the pe-riod from December 2001 to June 2025, it examines not only the existence of a correla-tion but also its temporal structure, functional form, and heterogeneity across different geographical areas (U.S., Europe, Japan, and Spain). Using monthly data on net flows from INVERCO and market indices, the study employs Ordinary Least Squares (OLS) regression models, segmented regressions, and fixed-effects panel models to obtain robust estimates. The results confirm a positive and statistically significant relation-ship between past returns and subsequent investment flows, with a temporal lag ranging from one to three months. This delay varies notably by geographical region, suggesting the existence of different investor profiles and information channels. The study also finds evidence of a convex relationship, indicating that investors react asymmetrically, aggressively pursuing high returns more than penalizing low ones. These findings, interpreted through the lens of behavioral finance, point to pro-cyclical and reactive behavior of Spanish investors, driven by biases such as loss aversion, trend-following, and delays in information processing. The study contributes to the academic literature by providing updated and methodologically robust evidence on Spain, a market that has traditionally been underexplored, and offers practical impli-cations for investors, fund managers, and regulators in terms of financial education and risk management.
Keywords: 
;  ;  ;  ;  ;  
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

Disclaimer

Terms of Use

Privacy Policy

Privacy Settings

© 2026 MDPI (Basel, Switzerland) unless otherwise stated