New Risk Management Study Findings Have Been Reported from Indiana University of Pennsylvania (Predicting Mutual Fund Stress Levels Utilizing SEBI’s Stress Test Parameters in MidCap and SmallCap Funds Using Deep Learning Models): Insurance – Risk Management

2024 DEC 05 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Researchers detail new data in risk management. According to news reporting from Indiana, Pennsylvania, by NewsRx journalists, research stated, “The Association of Mutual Funds of India (AMFI), under the direction of the Securities and Exchange Board of India (SEBI), provided open access to various risk parameters with respect to MidCap and SmallCap funds for the first time from February 2024.”

Our news editors obtained a quote from the research from Indiana University of Pennsylvania: “Our study utilizes AMFI datasets from February 2024 to September 2024 which consisted of 14 variables. Among these, the primary variable identified in grading mutual funds is the stress test parameter, expressed as number of days required to liquidate between 50% and 25% of the portfolio, respectively, on a pro-rata basis under stress conditions as a response variable. The objective of our paper is to build and test various neural network models which can help in predicting stress levels with the highest accuracy and specificity in MidCap and SmallCap mutual funds based on AMFI’s 14 parameters as predictors. The results suggest that the simpler neural network model architectures show higher accuracy. We used Artificial Neural Networks (ANN) over other machine learning methods due to its ability to analyze the impact of dynamic interrelationships among 14 variables on the dependent variable, independent of the statistical distribution of parameters considered. Predicting stress levels with the highest accuracy in MidCap and SmallCap mutual funds will benefit investors by reducing information asymmetry while allocating investments based on their risk tolerance.”

According to the news editors, the research concluded: “It will help policy makers in designing controls to protect smaller investors and provide warnings for funds with unusually high risk.”

For more information on this research see: Predicting Mutual Fund Stress Levels Utilizing SEBI’s Stress Test Parameters in MidCap and SmallCap Funds Using Deep Learning Models. Risks, 2024,12(11):179. (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks12110179.

Our news journalists report that additional information may be obtained by contacting Suneel Maheshwari, Department of Accounting and Information Systems, Indiana University of Pennsylvania, Indiana, PA 15705, United States. Additional authors for this research include Deepak Raghava Naik.

(Our reports deliver fact-based news of research and discoveries from around the world.)