Competition and structure of the mutual fund industry in Spain: The role of credit institutions

Cambón, Ma Isabel; Losada, Ramiro

doi:10.1016/j.srfe.2014.02.002

Cited by 10 publications

(3 citation statements)

References 15 publications

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“…Based on this result, our aim is to study whether the families with a higher learning level share any common characteristics. Following Cambon and Losada (2014), we study the learning process of the fund families through two main dimensions: the family size and the dependence of the fund family on banking and insurance groups.…”

Section: Learning In the Mutual Fund Industry: An Approach Using The ...mentioning

confidence: 99%

“…The relatively high importance of fund families controlled by banks and insurance groups is another defining feature of the Spanish market. Cambon and Losada (2014) study the structure of the mutual fund industry in Spain and demonstrate that most fund assets are managed by families belonging to credit institutions, emphasizing the universal banking model as a distinguishing characteristic of this market. In fact, in Spain, approximately 90% of families belong to a banking or insurance group, a figure that is significantly higher than in other European markets such as Germany, Portugal, Italy, France, and the United Kingdom (EFAMA 2018).…”

Section: Panelmentioning

confidence: 99%

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You Learn When It Hurts: Evidence in the Mutual Fund Industry

Gimeno

Sarto

Vicente

2022

JRFM

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This paper aims to contribute to the lack of research on the learning process of mutual fund markets. The empirical design is focused on the ability of the Spanish equity mutual fund industry to learn from its important errors. The choice of this industry is justified by both its relevance in the European mutual fund markets and some specific characteristics, such as the concentration and the banking control of the industry, which may affect the learning process. Our main objectives are to identify important trading errors in mutual fund management by applying three independent filters based on the relative importance of each decision, and then testing the evolution of these errors both at the industry level and at the fund family level. We apply the dynamic model of generalized method of moments (GMM), and we find an overall significant decrease in the percentage of important trading errors over time, thereby providing evidence of the global learning process of the industry. In addition, we find that a large number of fund families drive this evidence. Finally, we obtain that the family size and its dependence on financial groups do not seem to play significant roles in explaining the learning process. Therefore, we conclude that fund managers have incentives to learn from their important trading errors, in order to avoid them in future decisions, due to their serious negative consequences on fund performance, regardless of the characteristics of the families to which they belong.

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Section: Learning In the Mutual Fund Industry: An Approach Using The ...mentioning

confidence: 99%

Section: Panelmentioning

confidence: 99%

You Learn When It Hurts: Evidence in the Mutual Fund Industry

Gimeno

Sarto

Vicente

2022

JRFM

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“…This information is retrieved at the end of each semester and it allows for the classification of funds depending on features like credit quality of their assets. 8 Also, the credit rating data are employed to build a liquidity index, i.e., the high-quality liquid assets that helps assess the resilience of investment funds to face 4 This study follows the approach employed by Cambon and Losada (2014) to define an investment fund as wholesale, i.e., those funds where investors holding more than €150,000 represent at least the 50% of the fund's AuM.…”

Section: Data Sources and Sample Constructionmentioning

confidence: 99%

Deconstructing Systemic Risk: A Reverse Stress Testing Approach

Ferreiro

2021

SSRN Journal

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The financial sector faces different systemic events. The early recognition of these events is a key step to monitor and track possible financial crises. Three main questions arise related to systemic risk, and they deal with their quantification, their probability of occurrence and the role of main contributors. This paper proposes a methodology based on a reverse stress test exercise to shed light on these questions. Time series and cross-section information regarding systemic risk are obtained. Further, we explore how these results of systemic assessment could change depending on key parameters in a Gaussian framework and, finally, a small empirical exercise is performed.

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Leaders and followers in mutual funds: A dynamic Bayesian approach

Andreu

Sarto

Gargallo

et al. 2020

Appl Stoch Models Bus & Ind

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This article proposes a dynamic Bayesian framework to analyze the leadership relationships between mutual funds. To this end, a two‐step procedure is proposed. First, a Bayesian rolling window based on the Capital Asset Pricing Model is used to estimate the evolution of mutual funds' market exposure over time. Then, a vector autoregressive (VAR) model is used to analyze the leader‐follower relationship between pair of mutual funds. Several leadership measures are studied. An application to Spanish mutual funds is carried out. In addition, the study examines the determining factors of mutual fund leadership.

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Competition and structure of the mutual fund industry in Spain: The role of credit institutions

Cited by 10 publications

References 15 publications

You Learn When It Hurts: Evidence in the Mutual Fund Industry

You Learn When It Hurts: Evidence in the Mutual Fund Industry

Deconstructing Systemic Risk: A Reverse Stress Testing Approach

Leaders and followers in mutual funds: A dynamic Bayesian approach

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