Multi-attribute Decision Making (MADM) is concerned with the elucidation of the levels of preference of decision alternatives, through judgments made over a number of criteria. Many complex MADM problems are characterized with both quantitative and qualitative-of preference of decision alternatives, through judgments made over a number of criteria. Many complex MADM problems are characterized with both quantitative and qualitative-attributes. In selection of its suppliers, an organization needs to take into account such attributes as quality, technical capability, supply chain management, financial soundness, environmental and so on. Many smart technologies are used in modern cities to improve society's well-being in many ways. The proposed research focuses on communication methods for data applications. Our main goal for this paper is to use little energy as possible while delivering as much data as possible by using multi-attribute decision-making.
The focus of this study is on time series inferential statistical projection and analysis for long-term multi-trending trajectory forecast modelling. Inferential statistics was used for projection and analysis of long-term multi-trending trajectory forecasting. The proposed model is trained, tested and validated on three different types of stocks viz. NVIDIA, UNG and IBM taken from the NASDAQ stock market index. In Phase I, the long-term deterministic multi-trending model is assessed and fitted. Model skewed residual series is assessed using the goodness of fit in Phase II. The future stock close prices and long-term multi-trending trajectory paths are simulated and analyzed in Phase III. Finally, in Phase IV, epsilon-skew-normal results and normal distribution assumptions are compared. The experimental result shows that an uptrend trajectory of historical close price simulates an uptrend trajectory in the forecasted close price, a downtrend trajectory of historical close price simulates a downtrend trajectory in the forecasted close price, a sideways or mixed trend trajectory of historical close price simulates a sideways or mixed trend trajectory in the forecasted close price.
Microfinance has risen significantly as a tool for assisting entrepreneurs from under-represented and disadvantaged groups in obtaining start-up capital. Credit, savings, insurance, remittances, and guarantees are all examples of financial services. The study's objective is to analyze the institutional credit facilities available to microcredit entrepreneurs in the Vellore district of Tamil Nadu. The primary data was gathered through the use of a standardized questionnaire. A suitable random sample of 220 microcredit entrepreneurs from the blocks was chosen. The Chi-square test, weighted average score, and percentages were employed to derive relevant conclusions from the study. Microcredit can have an economic impact by boosting an individual's income, lowering unemployment, elevating the standard of living, and promoting economic development. Furthermore, responders require guidance on using public, private, and natural resources and services. As a result, microcredit is insufficient in empowering the respondents in the research region, but it is one of the most significant elements in that process, together with non-credit factors.
This study empirically analysed the stock price reaction and the efficiency of Indian stock market of the Nifty 50 index around the budget announcements during covid periods from 2020 to 2022 by applying event study methodology. The market efficiency was tested by employing 61 days event study window including 30 days before and 30 days after the announcement date, and the event date of the budget, while the estimation window period comprises of 120 days of the pre-event period. The market model is employed to demonstrate abnormal returns near the event date and to assist in estimating expected returns. Abnormal returns, Average abnormal returns, Cumulative average abnormal returns, and t-tests were applied for analysing the market efficiency on Indian budget announcements. This research paper reveals that the efficiency level of the Indian stock market is high and the investors can not make an abnormal profit over the budget announcements during Covid periods.
Women currently make up a sizable portion of the active workforce across all sectors; therefore it only makes sense that they would represent a sizable potential market for all insurers. The financial independence of women and their loved ones is benefited by the many insurance companies' women-focused programmes. Women possess a lot of obligations when they are single parents and are responsible for a multiple tasks. Therefore, the importance of protecting their finances becomes even more crucial for them. In this situation, insurance is quite important. The objective of this study is to study the participants' level of awareness, association and to find the number of policies taken by the participants and the factors that prevents choosing of exclusive women insurance policies. This study employs a quantitative research methodology using Chennai residents as its target audience and data is collected from 118 respondents. The statistical techniques used for analyzing the data are Percentage, Cross Table, One-way ANOVA, Independent t-Test, and Chi-square. The findings shows that the respondents have less knowledge about exclusive women's insurance policies.
