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Prior research has documented inconclusive and/or mixed empirical evidence on the timing performance of hybrid funds. Their performance inferences generally do not efficiently control for fixed-income exposure, conditioning information, and cross-correlations in fund returns. This study examines the stock and bond timing performances of hybrid funds while controlling and accounting for these important issues. It also discusses the inferential implications of using alternative bootstrap resampling approaches.

We examine the stock and bond timing performances of hybrid funds using (un)conditional multi-factor benchmark models with robust estimation inferences. We also rely on the block bootstrap method to account for cross-correlations in fund returns and to separate the effects of luck or sampling variation from manager skill.

We find that the timing performance of portfolios of funds is neutral and sensitive to controlling for fixed-income exposures and choice of the timing measurement model. The block-bootstrap analyses of funds in the tails of the distributions of stock timing performances suggest that sampling variation explains the underperformance of extreme left tail funds and confirms the good and bad luck in the bond timing management of tail funds. We report inference changes based on whether the Kosowski et al. or the Fama and French bootstrap approach is used.

This study provides extensive and robust evidence on the stock and bond timing performances of hybrid funds and their sensitivity based on (un)conditional linear multi-factor benchmark models. It examines the timing performances in the extreme tails funds using the block bootstrap method to efficiently identify (un)skilled fund managers. It also highlights the sensitivity of inferences to the choice of testing methodology.

This paper aims to investigate not only the performance of Portuguese mutual funds investing in domestic and international equities but also which fund characteristics, such as age, size, family size, expense ratios and flows, influence future performance.

Fund performance is evaluated over the 2005–2022 period by a robust six-factor model, while the impact of fund characteristics on performance is assessed by a set of fixed-effects panel data regressions with two-way cluster-robust standard errors.

The results show that, while funds investing in domestic equities predominantly exhibit neutral performance, most international equity funds have significantly negative alphas. The authors document a negative and statistically significant relationship between fund age and performance for all fund categories. Total expense ratios have an inverse relationship with domestic equity fund performance but do not impact the performance of international equity funds significantly. Though fund flows have a neutral effect on performance across the overall period, they are important determinants of both domestic and international funds’ performance in more recent years.

The authors contribute to the literature by carrying out a comprehensive analysis, based on recent and robust methodologies, of the impact of mutual fund characteristics on the future performance of Portuguese equity funds. The research findings serve as a premise for advising investors on how to choose the top-performing funds.

The authors analyse the determinants of loan defaults in micro, small and medium enterprises (MSME) loans in India from the survival duration perspective to draw inferences that have implications for lenders and policymakers.

The authors use the Kaplan–Meier survivor function and the Cox Proportional Hazard model to analyse 4.29 lakhs MSME loan account data originated by a large bank having a national presence from 1st January 2016 to 31st December 2020.

The estimated Kaplan–Meier survival function by various categories of loan and socio-demographic characteristics reflects heterogeneity and identifies the trigger points for actions. The authors identify the key identified default drivers. The authors find that the subsidy amount is more effective at the lower level and its effectiveness diminishes significantly beyond an optimum level. The simulated values show that the effects of rising interest rates on survival rates vary across industries and types of loans.

The identified points of inflection in the default dynamics would help banks to initiate actions to prevent loan defaults. The default drivers identified would foster more nuanced lending decisions. The study estimation of the survival rate based on the simulated values of interest rate and subsidy provides insight for policymakers.

This study is the first to investigate default drivers in MSME loans in India using micro-data. The study findings will act as signposts for the planners to guide the direction of the interest rate to be charged by banks in MSME loans, interest subvention and tailoring subsidy levels to foster sustainable growth.

Malnutrition has a significant effect on the onset and progression of infective pathology. The malnutrition status in COVID-19 cases are not understood well. Prognostic Nutritional Index (PNI) is a new and detailed assessment of nutrition and inflammation cases. This study aims to investigate the effect of PNI on mortality in COVID-19 patients.

In total, 334 patients (males, 142; females, 192; 64.5 ± 12.3 years of age) with COVID-19 bronchopneumonia were enrolled in this investigation. Cases were divided into two groups with respect to survival (Group 1: survivor patients, Group 2: non-survivor patients). Demographic and laboratory variables of COVID-19 cases were recorded. Laboratory parameters were calculated from blood samples taken following hospital admission. PNI was calculated according to this formula: PNI = 5 * Lymphocyte count (10⁹/L) + Albumin value (g/L).

When the patients were assessed with respect to laboratory values, leukocytes, neutrophils, CRP, ferritin, creatinine and D-Dimer parameters were significantly lower in Group 1 patients than Group 2 patients. Nevertheless, serum potassium value, lymphocyte count, calcium and albumin values were significantly higher in Group 1 cases than in Group 2 cases. PNI value was significantly lower in Group 2 cases than in Group 1 cases (39.4 ± 3.7 vs 53.1 ± 4.6).

In this retrospective study of COVID-19 cases, it can be suggested that PNI may be a significant risk factor for mortality. In conclusion of this research, high-risk patients with COVID-19 can be determined early, and suitable medical therapy can be begun in the early duration.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.