Journal articles: 'Financial statistics'

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International Monetary Fund. "Burundi: Financial Statistics." IMF Staff Country Reports 96, no. 43 (1996): 1. http://dx.doi.org/10.5089/9781451802771.002.

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Bossaerts, Peter. "The Econometrics of Learning in Financial Markets." Econometric Theory 11, no. 1 (February 1995): 151–89. http://dx.doi.org/10.1017/s0266466600009075.

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The asymptotic behavior of the sample paths of two popular statistics that test market efficiency are investigated when markets learn to have rational expectations. Two cases are investigated, where, should markets start out at a rational expectations equilibrium, both statistics would asymptotically generate standard Brownian motions. In a first case, where agents are Bayesian and payoffs exogenous, the statistics have identical sample paths, but they are not standard Brownian motions. Whereas the finite-dimensional distributions are Gaussian, there may be a bias if agents' initial beliefs differ. A second case is considered, where payoffs are in part endogenous, yet agents consider them to be drawn from a stationary, exogenous distribution, which they attempt to learn in a frequentist way. In that case, one statistic behaves as if the economy were at a rational expectations equilibrium from the beginning on. The other statistic has sample paths with substantially non-Gaussian finite-dimensional distributions. Moreover, there is a negative bias. The behavior of the two statistics in the second case matches remarkably well the empirical results in an investigation of the prices of six foreign currency contracts over the period 1973–1990.

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Ralph, William J. "Warp statistics and financial returns." Journal of Statistical Computation and Simulation 87, no. 2 (July 18, 2016): 390–405. http://dx.doi.org/10.1080/00949655.2016.1209201.

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El-Khoury, Gabi. "Financial statistics of Arab countries." Contemporary Arab Affairs 5, no. 4 (October 1, 2012): 600–608. http://dx.doi.org/10.1080/17550912.2012.714574.

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Nolde, Natalia, and Chen Zhou. "Extreme Value Analysis for Financial Risk Management." Annual Review of Statistics and Its Application 8, no. 1 (March 7, 2021): 217–40. http://dx.doi.org/10.1146/annurev-statistics-042720-015705.

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This article reviews methods from extreme value analysis with applications to risk assessment in finance. It covers three main methodological paradigms: the classical framework for independent and identically distributed data with application to risk estimation for market and operational loss data, the multivariate framework for cross-sectional dependent data with application to systemic risk, and the methods for stationary serially dependent data applied to dynamic risk management. The article is addressed to statisticians with interest and possibly experience in financial risk management who are not familiar with extreme value analysis.

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Lee, Cheng Few. "Financial econometrics, mathematics, statistics, and financial technology: an overall view." Review of Quantitative Finance and Accounting 54, no. 4 (April 22, 2020): 1529–78. http://dx.doi.org/10.1007/s11156-020-00883-z.

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Lethepa, Alicia, Reon Matemane, and Nyasha Dhlembeu. "Bankers and financial advisers in an emerging economy: are they financially literate?" Banks and Bank Systems 15, no. 2 (April 13, 2020): 16–27. http://dx.doi.org/10.21511/bbs.15(2).2020.02.

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Financial literacy is important for employees in the banking sector, as they are required to advise and administer the savings and investments of their clients. This study aims to establish financial literacy levels for banking employees and socio-demographic variables that influence their financial literacy levels. When collecting the necessary data for analysis, a survey was used for the total final sample of 120 employees of the banking sector. Descriptive statistics, the two-sample T-test and a simple ANOVA were used to determine the actual financial literacy levels and the socio-demographic factors influencing them. Overall, the employees were found to have moderately high levels of financial literacy. Only gender, race and education level were found to have an influence on financial literacy levels. This study informs the banking sector about how well employees are involved in financial literacy and which socio-demographic groups of their employees they need to focus on when exploring financial education programs.

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Deng, Xiaochuan, and Fei Sun. "Regulator-Based Risk Statistics for Portfolios." Discrete Dynamics in Nature and Society 2020 (July 9, 2020): 1–6. http://dx.doi.org/10.1155/2020/7015267.

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Risk statistic is a critical factor not only for risk analysis but also for financial application. However, the traditional risk statistics may fail to describe the characteristics of regulator-based risk. In this paper, we consider the regulator-based risk statistics for portfolios. By further developing the properties related to regulator-based risk statistics, we are able to derive dual representation for such risk.

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Dicle, Mehmet F., and John Levendis. "Importing Financial Data." Stata Journal: Promoting communications on statistics and Stata 11, no. 4 (December 2011): 620–26. http://dx.doi.org/10.1177/1536867x1201100408.

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Anderson, Marvin S. "INCOME TAX DATA AND FARM FINANCIAL STATISTICS." Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie 23, no. 1 (November 13, 2008): 41–51. http://dx.doi.org/10.1111/j.1744-7976.1975.tb00942.x.

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Chen, Rong, Per Mykland, and Qiwei Yao. "Financial Statistics and Risk Management: An Overview." Journal of Econometrics 194, no. 2 (October 2016): 203–4. http://dx.doi.org/10.1016/j.jeconom.2016.05.001.

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Budhathoki, Prem Bahadur. "Impact of Financial and Non-financial Benefit on Employees’ Job Satisfaction." Journal of Management 3, no. 1 (August 28, 2020): 85–94. http://dx.doi.org/10.3126/jom.v3i1.30916.

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This study examines the impact of financial benefit, training, reward, and career development opportunity on employees’ job satisfaction. This study is based on Likert scale data. There are forty questions included in the questionnaires excluding demographic variables. Each attribute contains eight questions. The primary data are obtained through the survey method. These collected data are analyzed by using descriptive statistics, Pearson correlation coefficient, and ordinary least squares regression model. The Statistics Package for Social Sciences (SPSS) is used for the analysis of data. The results indicate that the independent variables (financial benefit, training, reward, and career development opportunity) positively impact on job satisfaction.

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Giudici, Paolo. "Financial data science." Statistics & Probability Letters 136 (May 2018): 160–64. http://dx.doi.org/10.1016/j.spl.2018.02.024.

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Salin, V. N., M. V. Vakhrameeva, and O. Yu Sitnikova. "Presentation of Financial Assets in Russian Macroeconomic Statistics." Statistics and Economics 18, no. 5 (October 22, 2021): 14–25. http://dx.doi.org/10.21686/2500-3925-2021-5-14-25.

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The purpose of the study. Currently, much attention is paid to the collection, presentation and analysis of data on the volume, structure and dynamics of economic assets. The value of economic assets, their composition, and effective asset management determine the trajectory of the development of the national economy and its individual sectors. Financial assets are an integral part of economic assets, their importance in the activities of economic entities is steadily increasing. The purpose of the work is to systematize theoretical and practical developments on the presentation of data on financial assets in modern macroeconomic statistics of Russia, to determine the directions for improving the methods of evaluating financial assets, the system of indicators characterizing their condition and movement.Materials and methods. The authors considered the classification of financial assets, applied structural and dynamic data analysis, as well as methods of theoretical research in the form of generalization, comparison and special analytical procedures.Results. The paper defines the main directions of studying financial assets based on existing international standards, taking into account national statistical practice. The current issues of the theory and practice of statistical observation and presentation of data on financial assets, the adaptation of concepts and classifications of international standards to the Russian system of statistical accounting are considered. The features of the presentation of data on financial assets at the macro level are formulated, which are reflected in the national accounts, the system of indicators of monetary statistics and statistics of foreign economic relations, statistical indicators of the Bank of Russia. The authors conducted a quantitative assessment of the structure and dynamics of indicators characterizing the state and movement of financial assets.Conclusion. Statistical analysis of economic transactions with financial assets at the level of institutional units and sectors of the economy allows us to identify not only the main trends in the development of the financial sector of the economy, but also makes it possible to comprehensively consider changes in the value and composition of financial assets at the macro level. The change in the value of financial assets is determined on a balance basis, that is, as the difference between the value of acquired and disposed financial assets.The authors examined in detail the methodological basis for forming a financial account in the context of financial instruments and sectors of the national economy. The financial account provides comprehensive information in the sectoral context on transactions with financial assets and liabilities for the reporting period, allows you to reflect the change in their value as a result of economic operations performed by institutional units, as well as to identify sectors of the economy that did not perform transactions with financial assets. The analysis of the financial account data makes it possible to analyze in detail the change in the value of financial assets at the macro level, to assess the share of the impact of each sector of the economy and the type of asset. A similar approach is applied in analytical procedures with respect to the net obligations assumed.Macroeconomic statistics reflect the movement of financial assets and liabilities by sectors of the national economy and characterize Russia’s relations with the “rest of the world” by determining the volume of net lending by Russia to other countries or determining its status as a net borrower.The issues of the theory and practice of presenting data on financial assets and their use are relevant and promising areas for improving national statistical accounting. Work in this direction continues, although the process of active implementation of international standards in statistical practice has been going on for quite a long time. The quality of primary accounting data on financial sector operations has improved significantly recently, but there are still problems with obtaining data in terms of the full coverage of the statistical aggregate under study, as well as the timing of obtaining reporting data. In addition, the appearance of a large number of new financial instruments and transactions, including modified ones, in the business turnover of institutional units makes it difficult to identify and classify them.The authors of the article have repeatedly addressed the issues of macroeconomic calculations in their publications, which allowed them to consider in more detail topical issues related to the processes of reflecting financial assets.

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Salin, V. N., O. Y. Sitnikova, and L. Y. Arhangelskaya. "Presentation of Financial Assets in the Monetary Statistics." Statistics and Economics 19, no. 1 (March 3, 2022): 4–17. http://dx.doi.org/10.21686/2500-3925-2022-1-4-17.

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The purpose of the study. Currently, the issues of determining, presenting and analyzing indicators of economic assets, in particular, financial ones, are relevant, since financial assets, along with nonfinancial ones, constitute the most important characteristic of national wealth as a level of development of the country and are the basis for constructing national accounts, indicators of monetary statistics and other sections of macroeconomic statistics. In modern conditions, the role of these constructions in making effective management decisions at the macro level, individual sectors, economic entities, on the development of the national economy as a whole is increasing. The aim of the work is to systematize theoretical and practical developments on the definition and presentation of data on financial assets in modern monetary statistics of Russia, to identify areas for improving methods for assessing financial assets, a system of indicators characterizing their presence, structure and dynamics.Materials and methods. In the paper, the authors considered the essence, functions, classifications of financial assets and liabilities, applied structural and dynamic data analysis, as well as methods of theoretical research in the form of generalization, comparison and special analytical procedures based on official statistics from Rosstat, the Bank of Russia, the Ministry of Finance and international statistical organizations.Results. The work formulates the main directions of the study of financial assets, based on modern international statistical standards, taking into account domestic practice. Topical issues of the theory and practice of statistical collection and presentation of data on financial assets in monetary statistics, the application of definitions and classifications of international standards to Russian official statistics are considered. The features of the reflection of data on financial assets at the macro level, in the system of indicators of monetary statistics, have been formulated. The authors carried out a quantitative assessment of the structure and dynamics of indicators of monetary statistics in Russia, which characterize the state and movement of financial assets and liabilities.Conclusion. A statistical study of transactions with financial assets and in connection with the formation of monetary aggregates makes it possible to identify not only the main trends in the development of these processes, but also makes it possible to characterize the contribution of a particular subsector to the total value of financial intermediation, to analyze the relationship between the financial corporations’ sector and other sectors, and also a comprehensive change in the volume and composition of stocks and flows of financial assets as a result of exchanges between residents and non-residents.The authors comprehensively reviewed the methodological framework for constructing money aggregates and reviews of the financial corporations’ sector, incl. in the context of financial instruments. Statistical information on financial assets in monetary statistics is presented in terms of the formation of the money supply, other aggregates, the base, as well as the interaction between the institutional subsectors of the financial sector. A comprehensive description of the presence and movement of financial assets in the composition of monetary statistics can be obtained from the monetary surveys, containing data on the flows and stocks of financial assets and liabilities of financial corporations (residents) in relation to all other sectors (residents), as well as non-residents.All considered data are comparable [17,18] since basically, one classification of financial instruments is applied, a different degree of detail can be applied in practice for different constructions, but the base is the same. Questions of the theory and practice of presenting indicators of financial assets in the considered sections of macrostatistics and their analysis are a relevant and promising direction for improving national statistical accounting. Work in this direction continues, and the process of actively introducing international standards into domestic statistics has been going on for quite a long time. In addition, telecommuting, collecting information via the Internet, the emergence of a large number of new financial instruments and transactions, including modified ones, in the business turnover of institutional units complicate their identification and classification.The authors of the presented study have previously considered in their articles the problems of macroeconomic calculations, which allowed them in their work to consider in more detail the topical issues related to the processes of reflection of financial assets in monetary statistics.

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Majani, Dinah, Margaret Atieno, and Sylvester Mackton. "Is Use of IFMIS in Financial Reporting the Solution to Financial Accountability? Answers from County Governments in Western Kenya." American Journal of Accounting 4, no. 2 (October 2, 2022): 1–16. http://dx.doi.org/10.47672/ajacc.1210.

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Purpose: The implementation of Integrated Financial Management Information System (IFMIS) is aimed at increasing the effectiveness and efficiency of state financial management and facilitate the adoption of modern public expenditure practices in keeping with international standards and benchmarks. Despite IFMIS being implemented, many county governments’ still face accountability challenges. The purpose of this study was to evaluate the influence of financial reporting on financial accountability of county Governments in western Kenya. Methodology: The study was guided by Agency theory, Accountability theory and Technological Acceptance model. The study adopted correlational research design. Primary data was collected using questionnaires. The study target population was 1110 county staffs comprising of Cabinet executive officers, IFMIS directors, finance staff, revenue officers, planning and procurement staffs. Simple random sampling was used to select 294 respondents. Reliability was tested through Cronbach Alpha, validity was tested through expert analysis and principal component factor analysis. SPSS was used to analyze descriptive and inferential statistics. Descriptive statistics consisted of frequencies. Inferential statistics consisted of Binary logistic regression analysis. Findings: Cox & Snell R Square was established as 0.699. Wald statistic was significant with p values of 0.00, and 0.022 for financial reporting. Correlation analysis for financial reporting and internal controls was r = 0.944. The binary logistic regression coefficient was β of 6.17, p value .000 and Exp (β) = 479.88 for financial reporting. Data was presented using tables. Recommendation: It was recommended that implementation of IFMIS should be strengthened and regularly reviewed to identify loop holes that still exist that reduce effectiveness. This would improve fiscal discipline by a very high percentage as shown by the odds ratio of budgetary controls, financial reporting and internal controls which are all greater than one. There will be improved adherence to statutory regulations, unsupported expenditures would reduce and Misappropriations and budget variances will be minimal.

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Bastos, João A., and Jorge Caiado. "Clustering financial time series with variance ratio statistics." Quantitative Finance 14, no. 12 (October 23, 2012): 2121–33. http://dx.doi.org/10.1080/14697688.2012.726736.

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Stander, Julian, and John Eales. "Using R for teaching financial mathematics and statistics." MSOR Connections 11, no. 1 (March 2011): 7–11. http://dx.doi.org/10.11120/msor.2011.11010007.

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Feldmann, Louise. "The International Monetary Fund's International Financial Statistics Database." Journal of Business & Finance Librarianship 16, no. 3 (July 2011): 243–46. http://dx.doi.org/10.1080/08963568.2011.581577.

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Podgórski, Krzysztof. "Probability, Statistics, & Financial Math by Peter Caithamer." International Statistical Review 79, no. 1 (April 2011): 124–25. http://dx.doi.org/10.1111/j.1751-5823.2011.00134_11.x.

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Varghese, George, and Lakshmi Viswanathan. "Normative perspectives on financial inclusion: Facts beyond statistics." Journal of Public Affairs 18, no. 4 (May 27, 2018): e1829. http://dx.doi.org/10.1002/pa.1829.

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Buik, David. "Financial spread betting." Significance 3, no. 1 (March 2006): 26–27. http://dx.doi.org/10.1111/j.1740-9713.2006.00148.x.

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Politis, Dimitris N. "Financial time series." Wiley Interdisciplinary Reviews: Computational Statistics 1, no. 2 (August 19, 2009): 157–66. http://dx.doi.org/10.1002/wics.24.

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ابراهيم الصديق محمد, د. بابكر, and د. عاصم إبراهيم محمد يوسف. "دور نظام إحصاءات مالية الحكومة في تحسين كفاءة نظام الرقابة الداخلية في المؤسسات العامة." Omdurman Islamic University Journal 14, no. 1 (May 9, 2018): 228–66. http://dx.doi.org/10.52981/oiuj.v14i1.1627.

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This study focuses on the role of Government Financial Statistics Systems in developing the efficiency of Internal Control System. The statement of the problem presented that, Government Financial Statistics Systems have not been applied in the center and states. The researcher raised the following questions: Dose application of Government Financial Statistics Systems has an impact on the efficiency of Internal Control System. Is there any administrative constrains in the Ministry of Finance affecting the G.F.S, Do Internal Control System regulations established in the Ministry have an impact on the application of the Government Financial Statistics System? The importance of study is derived from the absence of scientific studies on the role of significance of Government Financial Statistics. The efficiency of organization is based on the strength and weakness of internal control system on the public institution. The study concluded with very important results that, centre and states accountants training on the Government Financial Statistics System will increase the efficiency of internal control system, and introducing the G.F.S as a syllabus in the universities will increase students’ capabilities when joining the employment, and the provision of computers will help the application of the Government Financial Statistics System. The Study recommended that, Government Financial Statistics System should be studied at Universities so that; students who are joining the service can easy understand their function. And application of F.F.S will help in transparency and wealth and wealth distribution.

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Yuliani, Yuliani, Taufik Taufik, Mukhtaruddin Mukhtaruddin, and Nyimas Dewi Murnila Saputri. "Assessing Model of Financial Satisfaction Predictors: the Mediating Effect of Financial Risk Tolerance and Financial Behavior." Journal of Accounting Research, Organization and Economics 4, no. 2 (August 10, 2021): 140–52. http://dx.doi.org/10.24815/jaroe.v4i2.20150.

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Objective – This study aims to prove empirically about the prediction of financial satisfaction models based on financial knowledge and socio-economic factors of finance by taking into account financial risk tolerance and financial behavior. Design/methodology – The primary data source in the form of a questionnaire and non-probability purposive sampling technique were used with 107 responses collected during July-August 2020. The unit of analysis was an individual, namely the people in Palembang City in the age range of 20-55 years. Data analysis comprise of descriptive statistics index number method and inferential statistics SEM method by converting ordinal data into intervals. Results – It was found that direct financial knowledge, socio-economic financial had not significant on financial risk tolerance. Financial knowledge, socio economic financial significantly and positively influence financial behavior. Furthermore, direct financial knowledge, socio-economic financial, financial risk tolerance, financial behavior had a significant positive effect on financial satisfaction. The indirect effect found that finance risk tolerance is not a mediation of the influence of financial knowledge and socio-economic financial on financial satisfaction. The indirect effect of financial behavior on the influence of financial knowledge and financial socio-economic were significant. Limitation/Suggestion – This study implies that the role of financial behavior as a partial mediation on the relationship between financial knowledge and financial satisfaction. The role of perfect mediation itself is for socio-economic financial relationships and financial satisfaction.

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Rahmalia, Nisa Riski, Elit Eriyanti, Najunda Dewa Yani, and Nur Kabib. "Deteksi Pengaruh Financial Stabilty, External Pressure, dan Financial Targets terhadap Financial Statement Fraud." Jurnal Akuntansi dan Audit Syariah (JAAiS) 3, no. 2 (December 6, 2022): 113–29. http://dx.doi.org/10.28918/jaais.v3i2.5645.

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The purpose of this study was to determine the effect of financial stability, external pressure and financial targets on fraudulent financial statements in manufacturing companies. In this study, the population of manufacturing companies listed on the Jakarta Islamic Index 70 (JII 70) for the 2019-2021 period is used. In the sampling process, the technique used is purposive sampling by producing 16 samples of companies. This study uses data analysis in the form of descriptive statistics, classical assumption test, and hypothesis testing. The results showed that partially the financial stability variable had an influence on financial statement fraud. Meanwhile, external pressure variables and financial targets have no effect on financial statement fraud. Simultaneously, the variables of financial stability, external pressure, and financial targets have an effect on fraudulent financial statements.

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Audrino, Francesco, and Peter Bühlmann. "Splines for financial volatility." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 71, no. 3 (June 2009): 655–70. http://dx.doi.org/10.1111/j.1467-9868.2009.00696.x.

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MTW and G. Ottaviani. "Financial Risk in Insurance." Journal of the American Statistical Association 94, no. 445 (March 1999): 351. http://dx.doi.org/10.2307/2669731.

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He, Xue Dong, Steven Kou, and Xianhua Peng. "Risk Measures: Robustness, Elicitability, and Backtesting." Annual Review of Statistics and Its Application 9, no. 1 (March 7, 2022): 141–66. http://dx.doi.org/10.1146/annurev-statistics-030718-105122.

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Risk measures are used not only for financial institutions’ internal risk management but also for external regulation (e.g., in the Basel Accord for calculating the regulatory capital requirements for financial institutions). Though fundamental in risk management, how to select a good risk measure is a controversial issue. We review the literature on risk measures, particularly on issues such as subadditivity, robustness, elicitability, and backtesting. We also aim to clarify some misconceptions and confusions in the literature. In particular, we argue that, despite lacking some mathematical convenience, the median shortfall—that is, the median of the tail loss distribution—is a better option than the expected shortfall for setting the Basel Accords capital requirements due to statistical and economic considerations such as capturing tail risk, robustness, elicitability, backtesting, and surplus invariance.

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Baudoin, Fabrice, and Laurent Nguyen-Ngoc. "The financial value of a weak information on a financial market." Finance and Stochastics 8, no. 3 (August 1, 2004): 415–35. http://dx.doi.org/10.1007/s00780-003-0116-1.

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ORZEŁ, Bartosz. "Non-financial value creation due to non-financial data reporting quality." Scientific Papers of Silesian University of Technology – Organization and Management Series 2020, no. 148 (2020): 605–17. http://dx.doi.org/10.29119/1641-3466.2020.148.44.

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Purpose:The main purpose of this article is to show non-financial value creation due to CSR 6reporting processes, a study on reports standards, types of reports submit by Polish enterprises 7and the statistics of the usage of these standards.8Design/methodology/approach:In this paper,GRI guideline requirements werepresented as 9a path to good-quality report creation. Additionally, anexample of quality assurance in CSR 10reporting in accordance withGRI guideline requirements was presented. The paper is based on 11the case study method. 12Findings:The result of the literature analysis is to show an approach to reportingnon-financial 13data in a comprehensive manner and in accordance with GRI guidelines.The other aspect is to 14show theinfluence of CSR reporting quality onnon-financial value.15Social implications:Reporting ofcorporate social responsibility by business organisations and 16entities is an example of improving the quality of human life, in particular in economic, social 17and environmental issues. The constant improvement of non-financial data reporting has 18significant impact on safety and sustainability in business and social development.19Originality/value: The paper shows specific view on non-financial value in connectionwith20stakeholders and organisations’ interest groups. 21Keywords:Non-financial value, CSR report quality, CSR reports, CSR reporting statistics, 22GRI guidelines.23Category of the paper: Case study, literature review.

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Mykland, Per Aslak. "Financial options and statistical prediction intervals." Annals of Statistics 31, no. 5 (October 2003): 1413–38. http://dx.doi.org/10.1214/aos/1065705113.

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Rydberg, Tina Hviid. "Realistic Statistical Modelling of Financial Data." International Statistical Review 68, no. 3 (December 2000): 233–58. http://dx.doi.org/10.1111/j.1751-5823.2000.tb00329.x.

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Yussuf, Ali Abdi, and Farida Abdul. "Public Financial Management Practices and Financial Performance of Mandera County Government, Kenya." International Journal of Current Aspects in Finance, Banking and Accounting 4, no. 2 (May 28, 2022): 22–36. http://dx.doi.org/10.35942/ijcfa.v4i2.252.

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According to the auditor general’s report, despite the huge sums of money counties receive, Mandera county government has not been able to meet their recurrent expenditures and revenue collection targets from 2015 to 2020. Past studies indicate that where there are prudent public financial management practices, county governments have been able to meet their mandates. It was therefore vital to empirically test public finance management practices in the Mandera county to establish whether they have a significant role in financial performance. The general objective of the study was to examine the influence of public financial management practices on financial performance of Mandera County Government, Kenya. Specifically, the study assessed the influence of budgeting process, resource management, financial policies and internal audit on financial performance in Mandera County. The study was based on systems theory, new public management theory and allocative efficiency theory. Cross-sectional research survey was applied in this study. Target population was all the 145 county government officers working in the revenue department. Stratified sampling method was used to arrive at a sample size of 95. The study used both primary and secondary data. A questionnaire was used to collect primary data whereas data collection sheet was used to collect secondary data from audited financial reports. Drop and pick later method was applied to administer the questionnaire. The study applied descriptive statistics, correlation and regression analyses to analyze the data collected. SPSS was used to conduct the analysis. Quantitative data analysis entailed computing descriptive statistics including frequency and percentage; measures of central tendency including the mean and the mode; and inferential statistics is including coefficient of determination, analysis of variance and regression analysis. The findings indicate that budgeting process, resource management, financial policies and internal auditing had positive significant effect on revenue collection. The study recommended that the county governments should ensure full employment of public financial management practices through strict adherence to the laid down frameworks in budgetary processes, resources management, financial policies, and internal audit. This would lead to optimal use of the available funds.”

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Derevyanko, Bogdan, Liudmyla Nikolenko, Irina Syrmamiik, Yevgen Mykytenko, and Iosif Gasparevich. "Assessment of financial and economic security of the region (based on the relevant statistics of the Donetsk region)." Investment Management and Financial Innovations 15, no. 4 (December 7, 2018): 283–95. http://dx.doi.org/10.21511/imfi.15(4).2018.23.

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In the article, the indicators of financial and economic security of Donetsk region are analyzed. The task of setting statistical estimation of financial and economic security of the region in modern conditions is based on the official materials of the State Statistics Service. For the possibility of further econometric modeling and forecasting, only quantitative indicators are used. This approach limits the number of evaluated indicators, but is considered the most objective. The analysis of financial and economic security is carried out in the context of two spheres of regional development: economic and social. The conducted analysis of the dynamics of the main socio-economic indicators of development of the Donetsk region for the period 2012–2016 allowed to identify the main trends characterizing the development of the region’s economy; provide an assessment of the financial and economic security of the region and identify some “problematic” places of financial and economic security in Donetsk region. Some of the most acute problems were identified in the assessment of financial and economic security and the features of state-legal provision of financial and economic security in the present conditions, as well as the proposed algorithm for monitoring the financial and economic security of the region. The analysis allowed to identify some “bottlenecks” of financial and economic security in the Donetsk region and to demonstrate that close attention and monitoring are required by the level of capital investments, the level of unemployment and the share of households with incomes per month below the legal living wage. The study enables to minimize the risks to form effective directions in assessing the financial and economic security of the region and proposes to optimize on a legal basis the whole mechanism for ensuring the financial and economic security of the region. As a result, the research revealed the most acute problems in assessing the financial and economic security of the region and proposed an appropriate algorithm for monitoring its level.

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Volkov, A. "Financial Statistics and the Transition to a Market Economy." Problems in Economics 34, no. 7 (November 1991): 82–91. http://dx.doi.org/10.2753/pet1061-1991340782.

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Walker, Graeme. "Developing financial statistics for policy - Progress report January 2011." Economic & Labour Market Review 5, no. 1 (January 2011): 46–58. http://dx.doi.org/10.1057/elmr.2011.6.

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Agundu, Prince Umor C. "Financial Statistics for Public Health Dispensary Decisions in Nigeria." Journal of Hospital Marketing & Public Relations 14, no. 2 (December 11, 2002): 59–76. http://dx.doi.org/10.1300/j375v14n02_06.

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Borio, Claudio. "The Great Financial Crisis: Setting priorities for new statistics." Journal of Banking Regulation 14, no. 3-4 (July 2013): 306–17. http://dx.doi.org/10.1057/jbr.2013.9.

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40

Hope, Joan. "Compare nationwide financial aid statistics with your institution's practices." Successful Registrar 18, no. 2 (March 25, 2018): 9. http://dx.doi.org/10.1002/tsr.30458.

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Hope, Joan. "Compare nationwide financial aid statistics with your institution's practices." Enrollment Management Report 22, no. 1 (March 25, 2018): 8. http://dx.doi.org/10.1002/emt.30406.

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Rahadjeng, Erna Retna, and Yulist Rima Fiandari. "The Effect of Financial Technology on the Financial Satisfaction of MSMEs in Malang." Manajemen Bisnis 12, no. 01 (April 9, 2022): 01–07. http://dx.doi.org/10.22219/mb.v12i01.19218.

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This study aims to determine the effect of financial technology on financial satisfaction of Small Businesses (SMEs) in Malang City. By using primary data and random sampling, as well as using a questionnaire distributed to entrepreneurs and measured with a Likert scale. The collection of data on MSME respondents in the city of Malang is based on the distribution of questionnaires. The research objectives are as follows: To know the influence of Fintech on financial satisfaction?”. The analytical method used to determine the effect is to use simple regression statistics, with regression analysis tools used SPPS tools. The results obtained from the regression analysis show that there is a significant influence between Fintech variables on Financial Satisfaction. This is indicated by the value of the coefficient of determination (Adj.R-square) generated by the Fintech regression model (effect of feature convenience, social influence, performance expectations, system security and payment system drivers) on financial satisfaction of 0.565. Simultaneous testing of the hypothesis of the influence of Fintech variables (Ease of Features, Social Influence, Performance Expectations, System Security and Payment System Drivers) on Financial Satisfaction resulted in an F-test statistic of 26,716 with a probability of 0.000. This means that there is a simultaneous significant influence (together) with Fintech (Feasibility of Features, Social Influence, Performance Expectations, System Security and Payment System Drivers) on Financial Satisfaction.

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43

Kamal, Lillian. "Financial Development, Financial Repression, And Growth In Developing Economies." International Business & Economics Research Journal (IBER) 11, no. 1 (December 21, 2011): 115. http://dx.doi.org/10.19030/iber.v11i1.6676.

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Many studies have examined the relationship between economic growth and finance. A continuing question is the choice of a clear proxy for financial development. This paper attempts to elucidate this issue from a developing country perspective, while controlling for financial repression. The proxy of choice is the ratio of currency outside the banking system to real output (CB). This proxy is unique in that it is related to the degree of financial repression, and thus relates differently to economic growth depending on the level of financial development. The statistics support the hypothesis of a U-shaped behavior of CB with financial liberalization. The empirical results show that CB relates negatively to growth in countries that are less financially liberalized and positively with growth in countries that are more financially liberalized. The literature has used real interest rates as a measure of financial repression. An innovative measure of financial repression is then proposed that combines the use of currency inside banks and currency outside banks, and is tested concurrently with a broad money depth measure. The study is carried out using a panel approach, and the sample is also divided into different geographical regions, in order to see whether the relationship differs between geographical regions. The study concludes that there is overwhelming evidence that financial repression, which is indicative of financial under-development, is negatively related to growth.

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Dvorkina, M. Ya, A. A. Dzhigo, and T. V. Maistrovitch. "Theoretical Foundations of the National Standard «Library Statistics: Statistical Rates and Measurement Units»." Bibliotekovedenie [Library and Information Science (Russia)], no. 4 (August 28, 2014): 21–28. http://dx.doi.org/10.25281/0869-608x-2014-0-4-21-28.

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The paper analyses the theoretical problems of creating the statistical rates and measurement units in the field of librarianship and scientific research information. These problems include the library collection size, characteristics of user population, the list of available services and delivered activities, research and methodic activities, material and technical basis, communication equipment and services, financial management and library staff.

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Terdik, György. "Optimal statistical inference in financial engineering." Journal of Time Series Analysis 32, no. 1 (December 12, 2010): 92. http://dx.doi.org/10.1111/j.1467-9892.2010.00661.x.

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Herman, Michele, and Balasundram Maniam. "Personal Finance Education: An Early Start To A Secure Future." College Teaching Methods & Styles Journal (CTMS) 3, no. 1 (July 22, 2011): 39. http://dx.doi.org/10.19030/ctms.v3i1.5274.

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The lack of mandated personal finance curriculum in American schools is an issue that has gained considerable momentum in recent years. Studies have indicated that personal finance education contributes to financial literacy and financial success. Although some strides have been made to incorporate personal finance education into core curriculum, statistics show that American students are financially illiterate. This paper investigates the impact of personal finance education on financial well-being and presents arguments for including personal finance education into core curriculum. This paper also provides an overview of the current trends in the US economy that are dramatically affecting the financial management behaviors of American households and their financial well-being

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Bardoscia, Marco, Giacomo Livan, and Matteo Marsili. "Financial instability from local market measures." Journal of Statistical Mechanics: Theory and Experiment 2012, no. 08 (August 31, 2012): P08017. http://dx.doi.org/10.1088/1742-5468/2012/08/p08017.

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Devi, Sandhya. "Financial market dynamics: superdiffusive or not?" Journal of Statistical Mechanics: Theory and Experiment 2017, no. 8 (August 24, 2017): 083207. http://dx.doi.org/10.1088/1742-5468/aa8199.

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Kirby, Dale. "Statistics and the Canada Millennium Scholarship Foundation." Canadian Journal of Higher Education 32, no. 3 (December 31, 2002): 111–18. http://dx.doi.org/10.47678/cjhe.v32i3.183421.

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This article critiques the Canada Millennium Scholarship Foundation's claim that recent research indicates that "Canada must move beyond (its focus on) student financial assistance" as a means of ensuring access to postsecondary education since "three out of four Canadian youth cite non-financial reasons to explain why they chose not to pursue postsecondary studies." This article argues that the Scholarship Foundation's research claims are not entirely accurate and are presented in a manner that is misleading.

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Frey, Rudiger, Marek Musiela, and Marek Rutkowski. "Martingale Methods in Financial Modelling." Journal of the American Statistical Association 93, no. 443 (September 1998): 1247. http://dx.doi.org/10.2307/2669888.

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Journal articles on the topic 'Financial statistics'

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