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The complicated interplay between the Romanian BET index, monetary policy rate, inflation rate, and RON/USD currency rate is studied using a Vector Autoregression (VAR) approach in this article. The methodology is based on the VAR model's ability to explain the dynamic relationship between multiple time series, with Granger causality tests used to identify the directionality of influence, impulse response functions used to trace the effects of economic shocks and forecast error variance decomposition used to measure the extent of variable interdependence. The findings show results about the links of monetary policy rate, inflation rate, BET index and exchange rate, with the purpose to find if capital markets are sensitive to macroeconomic policy decisions. The study emphasizes the central bank's policy rate's significance in influencing market expectations, as well as the complex impact of inflationary trends on currency valuation. [ABSTRACT FROM AUTHOR]

The research study voyage commences with the foundational objective of fitting a suitable Generalized Autoregressive Conditional Heteroscedastic (GARCH) model to assess market volatility, a fundamental pillar of financial analysis. This research embarks on an ambitious quest to predict and understand stock market volatility within the realms of the DJIA and S&P 500 of USA and ATX index of Austria using different sophisticated GARCH models. The dataset used in this study comprises daily stock market data for two key indices: the S&P 500 Index, representing the USA stock market, and the ATX Index, representing the Austria stock market. Additionally, the DJIA Index, another representative of the USA stock market, was included. The dataset consists of 5967 daily observations over the specified time period from January 3, 2000, to September 21, 2023. The observation of results, analysis and discussion depicts that PARCH model shows most promising results and found suitable to model the volatility patterns of the selected indices. The findings and methodologies presented in this paper can be seen as a solid foundation upon which to build future investigations, refining our ability to anticipate market movements and make informed decisions in an uncertain financial landscape. In closing, this research not only contributes to the body of knowledge in financial econometrics but also underscores the importance of modeling long-term stock market behavior with precision and diligence. [ABSTRACT FROM AUTHOR]

The best customer refers to the potential interaction of customers with the company during certain time periods. When companies understand the best customer and realize that the best customer can provide customized services for different customers, then they will achieve effective customer relationship management. This research is focused on the banking industry and systematically integrates data mining techniques and management topics to analyze the best customers. This study first uses the fuzzy hierarchical analysis method to weight the existing variables and then examines the DFMT model as an input to the k-means technique for clustering customers based on the desired criteria in the DFMT model. By using the proposed scoring model, it starts forming a customer value pyramid and categorizes customers into 4 value spectrums. Finally, in order to analyze the classes obtained from the customer value pyramid and implement the learning process from the available data, it uses the tenor classification techniques of decision tree, support vector machines and random forest along with the six characteristics and among They introduce the most appropriate model-characteristic based on available criteria. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

IN THE STOCK MARKET, VOLATILITY IS A TERM USED TO DESCRIBE THE DEGREE TO WHICH THE PRICES OF ASSETS FLUCTUATE AND DETERMINES THE DEGREE OF RISK OR UNCERTAINTY. THE MAIN AIM OF THE PRESENT STUDY IS TO MODELING THE BEHAVIOR OF THE SWITZERLAND STOCK MARKET USING DATA FROM 4TH JANUARY, 2000 TO 9TH NOVEMBER, 2023. THROUGH THE APPLICATION OF GARCH FAMILY MODELS WHICH, INCLUDE GARCH/TARCH, EGARCH, COMPONENT ARCH (1,1), AND PARCH. THE STUDY USED A SAMPLE NUMBER OF 5994 DAILY OBSERVATIONS FOR SWISS STOCK INDEX REPRESENTING THE SWITZERLAND STOCK MARKET. WE USED SOME STATISTICAL TECHNIQUES SUCH AS PHILLIPS-PERRON AND AUGMENTED DICKEY FULLER TESTS STATISTIC. THE ARCH LAGRANGE MULTIPLIER (LM) TEST, PARCH MODEL. WE UTILIZED THE EVIEWS 12 ECONOMETRICS PACKAGE. THIS STUDY HIGHLIGHTS THE SIGNIFICANCE OF ACCURATELY AND METICULOUSLY SIMULATING STOCK MARKET BEHAVIOR IN ADDITION TO ADDING TO THE CORPUS OF KNOWLEDGE IN FINANCIAL ECONOMETRICS. THE CONCLUSIONS AND METHODS DISCUSSED IN THIS STUDY PROVIDE A STRONG BASIS FOR FURTHER RESEARCH, ENHANCING OUR CAPACITY TO PREDICT MARKET MOVEMENTS AND MAKE WISE CHOICES IN A VOLATILE FINANCIAL ENVIRONMENT. [ABSTRACT FROM AUTHOR]

KHADI AND VILLAGE INDUSTRIES IS A MAJOR WING IN MSMES. THE PRESENT STUDY IS ANALYTICAL IN NATURE AND IS ENTIRELY BASED ON SECONDARY DATA. SECONDARY DATA RELATED TO THE PRODUCTION, SALES AND EMPLOYMENT OF KHADI& VILLAGE INDUSTRIES OF INDIA ARE COLLECTED FROM THE VARIOUS ANNUAL REPORTS OF MSMES GENERATED BY THE MINISTRY OF MSME, GOVERNMENT OF INDIA AND ANNUAL REPORTS OF KHADI AND VILLAGE INDUSTRIES COMMISSION (KVIC). THE ANNUAL REPORTS OF THE MSME SECTOR FROM 2010-11 TO 2020-21 HAS BEEN ANALYZED AND EVALUATED TO DRAW THE CONCLUSION. THE PURPOSE OF THIS STUDY IS TO ANALYSE THE GROWTH AND DEVELOPMENT OF KHADI AND VILLAGE INDUSTRIAL SECTOR IN TERMS OF PRODUCTION, SALES AND EMPLOYMENT GENERATION. AS WELL AS IT STUDIES THE BUDGET SUPPORT TO THE KVIC SECTOR BY THE GOVERNMENT. DATA INDICATE THAT THE KVI SECTOR MADE A MAJOR CONTRIBUTION TO EMPLOYMENT. HOWEVER, THIS SECTOR IS PERFORMING WELL, WITH INCREASING PRODUCTION AND SALES. COMPARED TO OTHER INDUSTRIES, THE KVI GROWTH IS SLOWER THAN OTHER SECTOR INDUSTRIES. IN THE KHADI SECTOR, EMPLOYMENT IS LOWER THAN AVERAGE. IT IS REPORTED THAT ALMOST 95% OF THE YEARLY BUDGET'S MONEY HAVE BEEN DISBURSED. FOR CALCULATION OF RESULTS OF CORRELATION HAS BEEN USED AND CONCLUDED THAT PRODUCTION AND SALES KHADI SECTOR AND VILLAGE INDUSTRY IS POSITIVELY HIGHLY CORRELATED. TO IMPROVE THE RURAL ECONOMY AND CREATE JOBS IN RURAL REGIONS, THE GOVERNMENT HAS TAKEN A NUMBER OF STEPS IN THE DIRECTION OF THE KVI SECTOR. DESPITE THE FIERCE COMPETITION, THE ENTIRE PERFORMANCE OF KHADI AND VILLAGE INDUSTRIAL SECTOR HAS BEEN OUTSTANDING. SALES AND PRODUCTION ARE ENCOURAGED BY THE KHADI AND VILLAGE INDUSTRIAL COMMISSION THROUGH THE IMPLEMENTATION OF SEVERAL PLANS FOR THE KVI SECTOR. [ABSTRACT FROM AUTHOR]

AN "INVESTMENT" INCLUDES EVEN A SAVINGS ACCOUNT EARNING 1% INTEREST. MOST PEOPLE, HOWEVER, REFER TO HIGHER RETURN PRODUCTS LIKE MUTUAL FUNDS, ETFS, AND EQUITIES WHEN THEY TALK ABOUT INVESTING. INVESTING GUARANTEES LONG-TERM FINANCIAL SECURITY FOR THE PRESENT AND THE FUTURE. YOUR INVESTMENTS' INCOME AND FINANCIAL SECURITY ARE POSSIBLE THANKS TO THEM. A DIVIDEND IS ONE WAY THAT INVESTMENTS LIKE STOCKS, BONDS, AND ETFS CAN GENERATE INCOME. THIS SUM IS WHAT SHAREHOLDERS RECEIVE ONLY FOR KEEPING THEIR INVESTMENT. AS A RESULT OF THE MONTHLY, QUARTERLY, OR ANNUAL DISTRIBUTIONS PAID BY MANY INVESTMENTS, YOU CAN BENEFIT FROM PASSIVE INCOME THAT ONE DAY MIGHT TAKE THE PLACE OF YOUR PAYCHECK, SHOULD ALWAYS STRIVE TO INVEST 15% OF YOUR PRE-TAX INCOME, AS A GENERAL RULE OF THUMB. IF YOU BEGIN INVESTING BY THE AGE OF 30, GENERATE AN AVERAGE YEARLY RETURN OF 10%, AND MAKE A MINIMUM OF $21,500 PER YEAR, YOU WILL HAVE AMASSED A MILLION DOLLARS BY THE TIME YOU ARE 65. INVESTORS ARE MORE LIKELY TO BE MEN THAN WOMEN. THIS INVESTING DIFFERENCE, ALONG WITH THE SALARY DISPARITY AND OTHER FACTORS, OVER THE COURSE OF A 35-YEAR CAREER, MIGHT RESULT IN MISSING OUT ON $1 MILLION IN VALUE. IN A SIMILAR VEIN, MEN ARE FIVE TIMES MORE LIKELY THAN WOMEN, REGARDLESS OF AGE, TO REPORT THAT INVESTING IS THEIR TOP PRIORITY. [ABSTRACT FROM AUTHOR]