Better Performance of Mutual Funds with Lower R2's Does Not Suggest that Active Management Pays

We found a negative relation between mutual funds’ past R2 and their abnormal performance, as did Amihud and Goyenko (2013), who proposed measuring active management of mutual funds by 1−R2. The interpretation of this relationship would be that active management pays. However the same evidence is uncovered for artificial investments, due only to the behavior of the types of stocks they are holding. Therefore, we introduce a new factor, ImS (idiosyncratic minus systematic), defined as the difference between the stocks’ returns with lower and higher past R2 which captures this behavior. After adjusting for this factor, the initial evidence vanishes and abnormal performance associated with past R2 diminishes, even taking negative values for mutual funds

Sincronización pasiva en la gestión de carteras

Accésit Premio Estudios Financieros 2000 El objetivo del presente trabajo es analizar la dimensión del efecto de la sincronización pasiva en la gestión de carteras. Este efecto se produce cuando una cartera no gestionada activamente presenta inestabilidad en el nivel de riesgo sistemático. En contraposición a ésta, la sincronización activa o market-timing implica una gestión activa de la cartera y, por lo tanto, cambios en el nivel de riesgo sistemático al objeto de anticipar adecuadamente los movimientos del mercado. En el trabajo se propone un modelo de beta dinámica que recoge el efecto de la sincronización pasiva atribuible a la evolución acumulada de las ponderaciones de los activos que forman la cartera. Los resultados muestran la importancia de este efecto en la aplicación de las medidas de performance y sincronización activa, que evalúan los resultados de carteras institucionalmente gestionadas como es el caso de los fondos de inversión

Asimetrías en el mercado de renta variable: evidencia para el caso español

The objective of this paper is to analyze the variation in the systematic risk of stocks when comparing bearish and bullish periods. Applying Matallín-Sáez, Moreno and Rodríguez (2015) model, risk variation is disaggregated into four components, the most relevant one being linked to the covariances of stocks. The mechanism that causes asymmetry in the systematic risk is essentially due to the fact that stocks with lower (higher) covariances and therefore lower (higher) beta in bullish moments show greater potential to increase (decrease) their covariances in bearish periods and therefore increase (decrease) their beta. The empirical analysis is performed on several databases of Spanish stocks for the period 12/31/2000 to 12/29/2017. Results show how stocks move more closely together in bearish markets, which significantly increases average covariance. Significant evidence of asymmetry is found in the systematic risk of stocks. In general, stocks with lower (higher) beta in bullish periods and smaller (larger) stocks tend to increase (decrease) beta in bearish periods. The cross analysis of upside beta and size reveals a greater association between the upside beta and the variation of the beta. These results are of interest to investors and professional managers of mutual fund and pension plan portfolios.El objetivo de este trabajo es analizar la variación del riesgo sistemático de las acciones al comparar momentos bajistas y alcistas. Se aplica el modelo de Matallín-Sáez, Moreno y Rodríguez (2015), que desagrega la variación del riesgo en cuatro componentes, de los que el más relevante es el vinculado a las covarianzas del activo. El mecanismo que causa la asimetría en el riesgo sistemático es debido, fundamentalmente, a que los activos con menores (mayores) covarianzas y, por tanto, menor (mayor) beta en momentos alcistas, muestran un mayor potencial para incrementar (disminuir) sus covarianzas en momentos bajistas y, por tanto, aumentar (disminuir) su beta. El análisis empírico se realiza sobre diferentes bases de datos de acciones del mercado bursátil español para el periodo del 31 de diciembre de 2000 al 29 de diciembre de 2017. Se evidencia cómo en los mercados bajistas los activos se mueven más conjuntamente, incrementando de forma notable la covarianza media. Los resultados muestran una evidencia significativa de asimetría en el riesgo sistemático de las acciones. En general, las acciones con menor (mayor) beta en momentos alcistas y aquellas con menor (mayor) tamaño tienden a incrementar (disminuir) la beta en momentos bajistas. Del análisis cruzado entre beta alcista y tamaño se desprende una mayor asociación entre la beta estimada en momentos alcistas y la variación de la beta. Estos resultados son de interés para inversores y gestores profesionales de carteras como fondos de inversión y planes de pensiones

Análisis de los resultados de los fondos de inversión

El objetivo del presente trabajo es analizar el valor añadido de la gestión activa de los fondos de inversión en España. Con este objetivo, se evalúan los resultados obtenidos por una muestra de Fondos de Inversión Mobiliaria (FIM). En esta evaluación se compara la gestión realizada en los fondos con los resultados obtenidos por una gestión pasiva ajustada al riesgo soportado por el fondo evaluado. Los resultados muestran cómo, en agregado, el conjunto de los fondos no obtiene una evaluación o performance distinta de cero. Sin embargo, la distribución de la performance de los fondos presenta determinada variabilidad, existiendo fondos que superan al mercado y otros por debajo de éste. El riesgo de gestión resulta asimétrico, sesgado hacia valores de performance más negativos que positivos. Al aplicar medidas de evaluación que ajustan a distintos niveles de riesgo, los resultados obtenidos son muy similares, las principales diferencias se producen en fondos con porcentajes significativos de riesgo específico

Cost and performance of carbon risk in socially responsible mutual funds

Investors and other financial actors are attracted by the role of socially responsible (SR) mutual funds in the transition to a low-carbon economy. In response to the demand for more information, Morningstar reported the level of carbon risk of funds by using the following indicators: Carbon Risk, Carbon Management, Carbon Operations risk and Carbon Exposure. Dealing with a sample of 3370 equity SR mutual funds worldwide from 2017 to 2021, this study analyzes the relationships between these indicators and the expense ratio and performance of the funds. In general, the results point to funds with lower carbon scores that have lower fees and perform better than those with higher scores. Considering the effects of the COVID-19 crisis, this evidence holds true for most of the sample period analyzed. With a spatial analysis, although the evidence generally holds, regional differences are found. Thus, funds that invest in the USA and Canada are on average cheaper and show lower carbon scores, while funds that are oriented to other areas, such as emerging markets, are more expensive and show higher scores. In summary, there is good news for the utility function of the investor and the planet: Green investing is cheaper and better

Investing in mutual funds: the determinants of implied and actual net cash flows

Estimating the fund investors’ demand plays an important role in the mutual fund management. In this line, mutual fund demand can be measured as the total net cash flows experienced by the fund during a period. Due to a lack of the data for inflows and outflows in some countries and databases, many authors estimate the net cash flows using fund size and return information. This rough measure, although being a good approximation, implicitly assumes an error in its calculation. For a sample of 2985 US open-end funds, we find evidence that estimating this implied fund flows, the error generated is higher for smaller funds, funds with higher returns, and for those experiencing higher levels of inflows or outflows. This lack of precision leads to a distortion in the estimation of the effect of some determinants on the mutual fund demand, especially when longer periods are considered when constructing the net cash flows

La elección del inversor entre fondos activos y fondos índice

This study compares the performance of actively-managed mutual funds and index funds. For a large sample of US domestic equity share-class funds, we analyze the relation between portfolio turnover and fund risk-adjusted return. Using gross returns, results indicate that before (after) the onset of the recent financial crisis, low-turnover active funds reach higher (similar) results than those obtained by index funds, whilst high-turnover active funds have similar (worse) returns to index funds. The same evidence is found when net returns are considered, but index funds perform comparatively better due to their lower costs. From an investors’ perspective, investing in previous high-turnover funds could lead to lower overall risk-adjusted returns.Este estudio compara el rendimiento de los fondos de inversión gestionados activamente y los fondos que replican a índice de referencia. Para una amplia muestra de fondos estadounidenses que invierten en acciones de EE. UU., se analiza la relación entre la rotación de la cartera y el rendimiento ajustado al riesgo de los fondos considerados. En términos de rentabilidades brutas, se muestra que antes (después) del inicio de la reciente crisis financiera, los fondos activos que presentan una baja rotación alcanzan resultados más altos (similares) que los obtenidos por fondos índice, mientras que los fondos activos de alta rotación tienen rendimientos similares o incluso peores. La misma evidencia se encuentra al considerar rendimientos netos, aunque los fondos índice tienen un desempeño comparativamente mejor debido a los menores gastos asociados que soportan. Desde la perspectiva de los inversores, invertir en fondos previos de alta rotación podría conducir, en promedio, a peores resultados financieros

Institutional investment management: An investor's perspective on the relation between turnover and performance

The main aim of this study is to analyse the relationship between turnover and performance in institutional investment management. For a sample of US equity mutual funds during the period January 1999–December 2014, we show that high-turnover funds do not beat low-turnover funds, since their performances are no different, or even significantly lower. Moreover, we show that investing in past high-turnover mutual funds provides investors with significantly worse results than investing in previously low-turnover funds. Investors aiming to enhance their risk-adjusted returns should therefore consider the turnover ratio level in their fund investment decisions

Mutual fund performance: dividends do matter

This article studies the bias in mutual fund performance when a nondividend-reinvesting benchmark is used. Our empirical findings show how performance worsens when using a benchmark that includes reinvestment dividends. We also find that inferences about managers’ ability related to economic states are biased by the effect of omitting dividends when selecting a benchmark.This study is part of the research projects P11B2012-07 supported by the Universitat Jaume I and ECO2011-27227 supported by the Spanish Ministerio de Ciencia e Innovación

Does active management add value? New evidence from a quantile regression approach

While it has long been recognised that active management is an important issue in the area of mutual fund performance, little consensus has been reached about the value managers’ abilities can add. This study examines funds’ and managers’ characteristics in an attempt to understand their influence on mutual fund efficiency. We explore these issues in a twostage approach, considering partial frontier estimators (order-m, order-α) to assess performance in the first stage, and quantile regression in the second stage to isolate the determinants of efficiency. This combination of methodologies has barely been considered to date in the field of operations research. Our findings are of interest to both academics and practitioners as they shed light on the differences among funds as well as among managers. Our analysis provides some arguments to guide fund selection and points to some managerial features investors might consider taking into account. In addition, some of the differences in performance among funds are rather intricate because both the magnitude of the estimated regression coefficients and their significance varies depending on the quantile of the distribution of fund performance, suggesting that some relevant trends might be concealed by conditional-mean models such as Tobit or OLS