OBJECTIVE This systematic review and meta-analysis aimed to find the association between serum Krebs von den Lungen-6 (KL-6) and the severity of Coronavirus disease 2019 (COVID-19) infection. DATA SOURCES Databases of Embase, PubMed, Web of Science, Science Direct, and Google Scholar were searched for studies reporting KL-6 levels in COVID-19 patients, published between January 2020 and September 30 2022. DATA SYNTHESIS For comparison between the groups, standard mean difference (SMD) and 95% confidence intervals (CI) were computed as the effect sizes. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were measured to assess the diagnostic power of KL-6. In addition, the summary receiver operating characteristics curve (sROC) was constructed to summarize the true positive (TP), and false positive (FP) rates. To validate the findings of meta-analysis, Trial Sequential Analysis (TSA) was conducted. RESULTS Altogether 497 severe COVID-19 patients and 934 non-severe (mild to moderate) COVID-19 patients were included. Pooling of 12 studies indicated that the serum KL-6 level had significant association with severity of COVID-19 infection: standard mean difference = 1.18 (95% CI: 0.93-1.43), p = 0.01; I2: 58.56%]. Pooled diagnostic parameters calculated from eight studies were: sensitivity 0.53 (95% CI: 0.47-0.59); specificity 0.90 (95% CI: 0.88-0.93); positive likelihood ratio 4.80 (95% CI: 3.53-6.53); negative likelihood ratio 0.46 (95% CI: 0.32-0.68); and area under curve: 0.8841. Additionally, TSA verified the adequacy of sample size and robustness of the meta-analysis. CONCLUSION Serum KL-6 level has a moderate degree of correlation with the severity of COVID-19 infection but has low sensitivity. So, it is not recommended as a screening test for severe COVID-19 infection.

To evaluate the monsoon rain-fall volatility across Gwalior-Chambal region and check the feasibility of weather (rainfall) derivative products to hedge rainfall risk in Gwalior Chambal region. Methods: To check the rainfall volatility, the monthly rainfall data has been collected for 100 years (from 1917 to 2016) and have analysed the data by using various statistical tools like Standard deviation, Coefficient of variation, One way Anova etc. Findings: This study shows that there is variation in volatility amongst the various district of Gwalior-Chambal region and the volatility is increasing in recent years. The volatility in rainfall is major cause of increasing losses among the farmers. Novelty: This study is useful to understand the rainfall volatility among the Gwalior Chambal region. The finding of this study can be used to introduce weather(rainfall) derivatives in Gwalior-chambal region and in India.

Bombay stock exchange (BSE) is the major stock exchange of the country which further has different sectoral indices where healthcare is one of the major indexes. All the major pharmacy companies are listed on the healthcare index and any change in the index leads to the change in profit of healthcare companies. Inflation being one of the major macroeconomic variables may impact the healthcare index of BSE. The objective of the research paper is to find the impact of Inflation (Consumer Price Index) on BSE Healthcare Index. Very few studies have been done in this sector of BSE Healthcare Index and macroeconomic variable Inflation (CPI). The statistical tool used for deriving the results of the paper are linear regression and analysis of variance for finding the impact to Inflation on BSE Healthcare Index. It has been found that there is significant impact of Inflation CPI (Consumer price index) on the BSE Healthcare Index. The relationship is inverse as with the rise in inflation, there will be decrease in the BSE Healthcare Index. This research will help both pharmacy companies and investors to understand the volatility of healthcare index in relation with inflation. Inflation (CPI) has a negative impact on the Healthcare Index of Bombay Stock Exchange.

There is a great deal of disarray with respect to different scholars about the relationship between the volatility and the institutional holdings pattern. The deciding variable is very vague and the precedence pattern is also not known. This relationship is consistent with two stories that either riskier asset attracts the institutional investors or the increment in the institutional holding result in the increase in the volatility. This research is directed towards finding the precedence and the sector wise impact of the institutional holding pattern.

There are many studies found in the field of stock volatility and institutional investors. Most of the studies found an inconsistent relationship between volatility and institutional investors. It creates a curiosity in the mind of investor, whether riskier securities attract institutional investors or an increase in institutional holdings results in an increase in volatility. In this paper we tried to examine the impact of institutional ownership pattern on stock volatility. We have considered BSE-30 companies and taken 5 year data from 1st January 2009 to 1st January 2014. Our result shows that institutional ownership has positive and significant impact on stock volatility.

Most studies on price performance of Indian IPOs have strengthened international evidence that there would be a strong underpricing in the short run, but negative returns in the long-run. To solve the problem of mispricing and include more transparency, SEBI mandated the grading of IPOs by recognized credit rating agencies from May 1, 2007. The mandatory grading process is expected to give an independent assessment of the fundamentals of the issue. In this research paper, we tried to ascertain the impact of grading on the performance of IPO firms. We attempted to understand the efficacy of the grading mechanism in place to address the problems associated with adverse selection and improve pricing efficiency.

This Report investigated the integration of Asian stock exchanges and indicated the diversification opportunities for potential investors they provide in the long-term. This study examines the stock market co-integration between India and south Asian countries, whether they are co integrated to each other or not which will eventually be helpful for the individual investors along with corporate investors in selecting their investment area and portfolio diversification. If the stock markets have any co-integration than diversification may not be profitable. This Report empirically analyzes the phenomenon of co-integration amongst selected South Asian stock markets. Augmented Dickey Fuller (ADF), Co-integration and Granger Causality tests are applied on the data.

Banking sector has undergone several major transformations during the past few years. Numerous reformations, liberalizations, progressions in technology etc. has made the sector exclusively lucrative. This paper tries to assess the impact of these revolutions on the sector. Efficiency serves as one of the crucial indicator of the performance. The paper appraises by taking into consideration various efficiency factors to determine the efficiency of 18 different private and public sector banks against the independent output variables assets, profits and deposits. This study employed Data Envelopment Analysis model, a non-parametric technique to examine the efficiency score. Input oriented efficiency with constant return model has been operated. The results acquainted that SBI, IDBI, Canara and ICICI have sustained high efficiency score from the past 10 years, 2002-2011.

Due to the advancement of Information Technology it has been easier for investors to invest valuable money in portfolios. There has been availability of tools & data all the time to predict the market in decision-making, for which some models have been developed. With the rigorous research in this attractive topic some mathematical models have been developed & some models from other industries have been considered. Models like Sharpe, Genetic Algorithm, and Monte-Carlo are very helpful in investment decision making. DEA model, originated from production industry, helps in selecting securities for portfolio. In this paper we have exquisitely tried to find out the best method for selection of efficient securities using historical data of BSE-30 industries & compared DEA, Sharpe’s model with Market, which gives some exciting results for future investment.