Performance Evaluation Of Funds Research Articles

Performance Evaluation and Risk Analysis of Mutual Funds: Insights from Recent Trends and Technological Advancements

Mutual funds, as a popular investment vehicle, pool resources from multiple investors to create diversified portfolios managed by professionals. This study explores the performance of mutual funds by analyzing various types, including equity, bond, and balanced funds, and their associated risks. Utilizing both primary and secondary data, the research evaluates mutual funds based on returns, investment patterns, and risk factors. It also examines the impact of recent technological advancements and regulatory changes on fund performance. The study highlights the benefits of mutual funds, such as diversification and professional management, while addressing potential risks including market, credit, and interest rate risks. By assessing the effectiveness of different mutual funds, the research aims to guide investors and improve capital allocation. The findings provide insights into how mutual funds contribute to individual financial goals and broader economic stability

The Importance of Risk Preference Parameters in Prospect Theory: Evidence from Mutual Fund Flows

In this paper, we use the well-documented mutual fund flow-performance relationship to infer information about investors’ preferences. We show that applying preference parameter values from experimental settings to market data can significantly understate the role of prospect theory in explaining investor behavior. We find evidence that mutual fund investors exhibit loss aversion and differential attitudes toward risk over losses (risk-seeking) and gains (risk-averse) but no significant probability weighting when evaluating fund performance. Our results apply more strongly to retail funds compared to institutional funds, consistent with the view that prospect theory is more relevant for retail investors. Finally, we show that, for parameter values that best explain fund flows, prospect theory outperforms the global risk aversion framework and widely-used asset pricing models in explaining investors’ responses to fund performance.

Optimizing Fund Performance: A Communication Systems Approach to Data Mining in Large- Cap Equity Mutual Funds

Mutual funds represent a secure and technologically driven conduit for Indian investors to engage with the dynamic Indian financial markets. These professionally managed funds strategically allocate investments across a spectrum of securities, including equities, bonds, government securities, and gold, leveraging cutting-edge information technology infrastructure for seamless operation and optimization. Within this landscape, performance emerges as a pivotal metric, driving the flow of savings into these digitally enabled funds, indicative of investors' confidence and expectations in the realm of data-driven decision-making. The core objective of this paper is to construct a robust mutual fund performance evaluation model utilizing the Statistical Package for the Social Sciences (SPSS), a sophisticated software platform renowned for its advanced analytics and predictive modeling capabilities in the information technology domain. The work focused specifically on equity mutual funds, this study meticulously examines top-rated funds within the large-cap category, drawing insights from a comprehensive validation period spanning the last fifteen years from April 2007 to March 2021. Through the systematic evaluation of various performance metrics within the context of information technology-driven analysis, this model aims to deliver actionable insights and strategic foresight, benefiting researchers, society, and financial analysts alike, while catalyzing innovation and driving positive impacts in the intersection of technology and finance.

Performance Evaluation Disagreement

This paper studies investor disagreement in the performance evaluation of equity mutual funds by comparing two existing approaches and estimating its relations with fund characteristics, active management level and fund flows. We find that investors disagree more about the performance of funds that have higher expense ratio and turnover, lower manager tenure and dividend yield, and that are older, smaller and part of a larger family. Disagreement is also higher for funds that follow riskier investment style strategies and deviate more from their benchmarks. Finally, larger disagreement leads to more net fund flows. These findings suggest that heterogeneous investors do not value funds with aggressive active trading strategies similarly, and that favorable valuations by some clienteles result in positive demands for this type of management.

Interface-Based Loan Fund Performance Monitoring And Evaluation System At BKM Ngesrep Semarang

The monitoring and evaluation system is a routine process of collecting data and measuring progress on program objectives/monitoring changes, which focuses on processes and outputs. Monitoring involves accounting for what is done. Monitoring involves observing the quality of the services provided while evaluation is the use of social research methods to systematically investigate program effectiveness/assess the program's contribution to change (goal/objective) and assess the need for improvement, continuation or expansion of the program (recommendations). The first aim of this system is to be able to process data efficiently and accurately, the second aim is to assist the financial management unit (UPK) in inputting loan fund installments to make it easier to process data so as not to make calculation errors and record errors and to improve services to Community Self-Help Groups (KSM) better as borrowers, the third objective is to facilitate monitoring of loan fund evaluation which can be monitored and evaluated at any time, both the rate of return of loan funds and the level of loan fund congestion. In this system, the interface-based monitoring and evaluation model is one of the services provided by the operating system as a means of interaction between the user and the operating system. The interface is an operating system component that comes into direct contact with the user. This application was created using Microsoft Visual Basic 6.0 and a Client Server-based MySQL database.

Multiple strategies based Grey Wolf Optimizer for feature selection in performance evaluation of open-ended funds

The methods for selecting the features in evaluating fund performance rely heavily on traditional statistics, which can potentially lead to excessive data dimensions in a multi-dimensional context. Grey Wolf Optimizer (GWO), a swarm intelligence optimization algorithm with its simple structure and few parameters, is widely used in feature selection. However, the algorithm suffers from local optimality and the imbalance in exploration and exploitation. This paper proposes a Multi-Strategy Grey Wolf Optimizer (MSGWO) to address the limitations, and identify the relevant features for evaluating fund performance. Random Opposition-based Learning is applied to enhance population quality during the initialization phase. Moreover, the convergence factor is nonlinearized to coordinate the global exploration and local exploitation capabilities. Finally, a two-stage hybrid mutation operator is applied to modify the updating mechanism, so as to increase population diversity and balance the exploration and exploitation abilities of GWO. The proposed algorithm is compared against 6 related algorithms and verified by the Wilcoxon signed-rank test on 12 quarterly datasets (2020-2022) of Chinese open-ended funds. The results inform that MSGWO reduces the feature size as well as the classification error rate.

Style Drift and Performance Evaluation of Green Funds in China

Based on data of China's open equity and partial equity hybrid green funds from 2018 to 2022, this paper conducts the sharp style analysis model to construct green fund style drift indicator, and apply the TM model to construct stock selection and timing indicators. Moreover, this paper constructs a panel fixed-effect model to empirically analyze the impact of green fund style drift, stock selection and timing on green fund performance. This research finds that there is a drift of investment style in green funds. Such style drift and timing have a negative impact on the performance of green funds. Stock selection has a significant positive impact on green funds. Furthermore, this research introduces style drift, stock selection and timing indicators into green fund performance evaluation, and use principal component analysis method to build a green fund performance-evaluation system. Then, this paper applies the rating system to the existing green fund market and effectively supplements the existing rating system.

Research on Performance Evaluation of Special Financial Funds for Higher Vocational Colleges

Research on Performance Evaluation of Special Financial Funds for Higher Vocational Colleges

Systematic Review and Meta-Analysis of Mutual Fund Performance Evaluation Studies: A Bibliometric Analysis and Clustering

Objective: The objective of this study is to conduct a systematic review and meta-analysis of mutual fund performance evaluation studies, focusing on the historical evolution of performance assessment methods based on fund style. Methodology: This research is divided into two main sections. The first section involves a quantitative analysis of prominent ISI-listed studies on mutual fund performance from 1900 to 2023, using bibliometric software such as HistCite™ and VOSviewer. This bibliometric analysis identifies and categorizes key studies based on citation counts. The second section reviews the evolution of mutual fund performance measurement criteria and various approaches used in the literature, critically analyzing the strengths and limitations of these methods. Findings: The bibliometric analysis revealed significant trends in mutual fund performance evaluation, with a clear evolution in methodologies over time. The study identified two primary approaches: asset-based analysis and return-based analysis. Key findings indicate that while both approaches have their merits, asset-based analysis offers a more accurate assessment of managerial skill by considering the composition of the fund’s holdings. Additionally, the analysis highlighted the most cited studies and influential journals in the field, providing a comprehensive overview of the research landscape. Conclusion: The study concludes that mutual fund performance evaluation has significantly evolved, with increasing complexity and sophistication in methodologies. The findings underscore the importance of selecting appropriate performance measurement criteria based on the specific characteristics of the mutual fund.

Performance Evaluation of Special Fund for Chinese Private Education: Logic and Index System

Performance Evaluation of Special Fund for Chinese Private Education: Logic and Index System

Performance evaluation of financial special poverty alleviation development funds under the background of rural revitalization with 2-tuple linguistic Pythagorean fuzzy information

Performance evaluation of financial special poverty alleviation development funds under the background of rural revitalization with 2-tuple linguistic Pythagorean fuzzy information

Persistent Performance of Alpha in Evaluating and Predicting the Returns of Chinese Stock Mutual Funds

Alpha has been examined to be a significant performance indicator for mutual funds. It was developed in 1968 by Jensen and was widely applied as a measure in the evaluation of mutual funds managers. It quantitatively show the gap between the model-based expected returns and the actual fund returns. In my research, I wonder whether the persistence of alpha for different portfolios exist. I apply three mutual fund performance evaluation models in this paper and calculate the alpha of mutual funds under each model. Then I rank the alpha of each fund and group them into four portfolios. I keep tracking the alpha and performance of each portfolio from January 2008 to July 2020, and find that the portfolio with the highest historical alpha keeps beating the other three portfolios while having the highest alpha. Although there are still some parts of the experiment that could be improved, the empirical results of my research show that the alpha seems to be a persistent indicator of the performance of Chinese mutual funds.

The Performance Evaluation Model of Financial Special Rural Revitalization Funds from the Perspective of the Digital Economy

Digital village is the strategic direction of rural revitalization, and also an important part of building a digital China. At present, the construction of digital countryside is advancing, and a reasonable evaluation of the results of rural revitalization can effectively evaluate the use of funds. Therefore, in this study, firstly, based on the economic, social, and ecological perspectives, the fund performance evaluation index system of rural revitalization is constructed. Secondly, the correlation analysis method is used to select the evaluation index, and the combined weight method is employed to obtain the weight of the evaluation index. Finally, according to the extension cloud theory, the performance evaluation model of targeted poverty alleviation is implemented, and an empirical study is conducted on the performance evaluation of S Province with excellent rural revitalization. The results reveal that the income growth rate of the poor population, the incidence of rural poverty, and the rate of good air quality are the most vital indicators, with weights of 0.094, 0.092, and 0.07 respectively. From 2015 to 2021, S Province maintained a high level of environmental performance, while its economic performance and social performance needed to be further improved. The fund performance of rural revitalization experienced four levels: average, medium, good, and excellent, and showed a reverse trend in 2018 and 2021. This study makes a quantitative and qualitative evaluation of rural revitalization by using the extension cloud theory, which provides a reference for the effective use of special funds, and also provides a sufficient scientific basis for the macroeconomic layout.

EVALUASI KINERJA REKSA DANA SYARIAH: STUDI KASUS PASAR MODAL SYARIAH INDONESIA

This study examines the performance evaluation of Islamic mutual funds in the context of the Indonesian Sharia capital market. Islamic mutual funds are investment instruments that offer attractive alternatives for Muslim investors who wish to participate in the capital market while adhering to Islamic financial principles. In this study, a qualitative research methodology with a case study approach was employed to analyze the performance of Islamic mutual funds in the Indonesian Sharia capital market. The research involved an in-depth analysis of factors influencing the performance of Islamic mutual funds, such as historical performance, associated risks, portfolio characteristics, fund management, and compliance with Sharia principles. The findings of this study indicate that Islamic mutual funds in the Indonesian Sharia capital market have experienced significant growth during the research period from 2019 to May 2023. Although the growth in the number of Islamic mutual funds has been relatively slow, it reflects the increasing interest of investors in investment instruments that align with Sharia principles

Market crises and benchmark-adjusted fund alphas in a small market context

Most mutual fund performance evaluation studies interpret fund alphas as the incremental performance of managers in relation to passive benchmark indices, which should exhibit statistically insignificant alphas. However, if these indices present significant non-zero alphas, standard (non-adjusted) fund alphas are biased. This paper investigates the impact of using benchmark-adjusted alphas to assess the performance of Portuguese-based mutual funds, investing in domestic and European equities. For the period 2000-2020, our results show that fund benchmarks exhibit significantly negative alphas, which lead to an underestimation of mutual fund performance when employing standard models. As a result, benchmark-adjusted alphas are significantly higher than unadjusted alphas for both fund categories, though the differences are larger for domestic than for European funds. We have also found that the impact of the benchmark-adjustment procedure depends on the state of markets. The domestic (European) benchmark exhibits considerably lower (higher) alphas during crisis than during non-crisis periods. During market crises, the differences between pre- and post-adjustment alphas are statistically significant only for domestic funds, whereas during non-crisis periods, both fund categories exhibit significant performance improvements. Our findings suggest that the benchmark-adjustment procedure has a higher impact when benchmark indices exhibit higher concentration.

Performance Evaluation of Chinese Stock Mutual Funds

Based on a data from January 2003 to July 2020, I compare market index with mutual funds in Chinese stock market. First, I compare the cumulative return of market with that of mutual funds. Mutual funds have obvious advantages. Next, I compare their volatilities, Sharpe ratios, Sortino ratios, and maximum drawdowns. Based on these performance proxies, Chinese stock mutual funds still outperform the market index. Finally, I research the persistence of fund performance. Mutual funds with better performance in the past year tend to have higher returns in the next month.

Commercial Retirement FOFs in China: Investment and Persistence Performance Analysis

The number and size of China’s commercial retirement Fund of Funds (FOFs) have exploded since 2018, reflecting a dearth of Chinese retirement products and widespread retirement anxiety among individual investors. Therefore, the performance of retirement FOFs continues to garner widespread interest from academia and society. This study evaluates the performance and sustainability of the investment strategies employed by China’s retirement FOFs using standard relative and absolute measures. The Sharpe ratio, Treynor ratio, and Jensen’s alpha are used as performance measurement standards, and the sustainability of performance is evaluated using the performance dichotomy, cross-sectional regression, and Spearman rank correlation coefficient methods. Target-risk FOFs for retirement are categorized into four groups: conservative, stable, balanced, and aggressive, with each group assuming progressively greater levels of risk. In evaluating fund performance, it was determined that the aggressive and stable groups of funds generated greater excess returns (as indicated by the inflation-adjusted Sharpe ratio). Additionally, the stable group of funds generated greater investment returns than the other groups (as all statistically significant alpha values for Jensen were positive). When evaluating the sustainability of fund performance, it was determined that the stable and balanced group funds exhibited the least sustainable performance. During the economic recession caused by the COVID-19 pandemic between 2020 and 2021, there were multiple fund performance ranking reversals (with significantly negative cross-sectional regression coefficients and Spearman coefficients). In the second half of 2022, the fund’s performance exhibited signs of sustainability (as indicated by significant performance dichotomy test values and positively significant Spearman coefficients). Still, this trend did not persist into 2023. Summarizing the different performance indicator results reveals that the stable group is the most worthwhile fund group to purchase among the four groups. Also, given that the historical performance of a signal fund is not sustainable, the investors should diversify their investments in this group and try to obtain the average return of the stable strategy to achieve the goal of supplementing retirement.

Fund performance evaluation with explainable artificial intelligence

We apply explainable artificial intelligence (xAI) to a large dataset of global equity funds. Our approach combines the XGBoost model with Shapley values; the former is a machine learning framework that enhances model fitness while the latter is an xAI method that provides informed explanations regarding the direction and significance of predictors. Based on macro-finance and fund-level factors, our fund performance evaluation of G10 countries uncovers novel insights into the diversification of country portfolios: both over- and under-diversification are associated with poor performance. Our analysis establishes consistency through a benchmark linear regression model and robustness at country level.

Conventional or Shariah Compliant Investment: Performance Evaluation of Mutual Funds in Pakistan

The current study was initiated to compare the performance of conventional and Shariah-compliant mutual funds in Pakistan, keeping in view the contradictory opinions found in the literature in this regard. The data utilized to conduct the analysis covered the time span 2013-2021. Assessment of risk and return tradeoff was made with three ratios, namely Jenson’s alpha, Treynor ratio, and Sharpe ratio by evaluating the monthly returns of conventional and Shariah-compliant mutual funds. The findings revealed that Shariah-compliant mutual funds outperformed conventional funds in terms of absolute risk measure, higher Sharpe ratio, and low coefficient of variation. While, in terms of funds’ exposure to systematic risk, mixed results were obtained for both types of funds. The results produced sufficient information about the risks and returns associated with the two kinds of mutual funds which would enable fund managers and investors to make informed decisions while selecting the best mutual fund, thus generating maximum returns and with minimum risks.

Application of Nonparametric Stochastic Dominance Approach in the Performance Evaluation of Indian Mutual Funds

Application of Nonparametric Stochastic Dominance Approach in the Performance Evaluation of Indian Mutual Funds