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Determinants of Saving Behavior Among Employees in Dhaka, Bangladesh

Determinants of Saving Behavior Among Employees in Dhaka, Bangladesh ArXiv ID: 2507.21254 “View on arXiv” Authors: Soumita Roy, Md Muntasir Kamal Dihan, Tasnimah Haque, Nafisa Nomani, Sadia Islam Preety Abstract Purpose With an emphasis on elements like financial knowledge, financial attitude, social influence, financial self-efficacy, and financial management practices, this study explores the factors that influence employees’ saving behavior in Dhaka, Bangladesh. We also welcome others to work on saving behavior, which is the main reason for publishing. The purpose is to make others aware of the methods for quantitative financial behavior analysis in Bangladesh. Design/methodology/approach The study uses a quantitative approach with a cross-sectional survey design. Data was collected from 40 participants through a structured questionnaire adapted from reliable sources. The questionnaire captured demographic information and used established items to measure the key variables. Data analysis included descriptive statistics, reliability analysis using Cronbachs alpha, and regression analysis to test the hypothesized relationships. Findings The results indicate that among the factors examined, only financial management practices had a significant positive relationship with saving behavior. Rest of the factors did not show significant relationships with saving behavior in this study sample. Limitation or Disclaimer It is still a work in progress, this paper is meant for pre-print with mostly incomplete and limited data. No data cleaning was performed, so it is very likely to include outliers and faulty data. Originality or value This study contributes to the limited research on saving behavior determinants in the Bangladeshi context, specifically among employees in the capital city of Dhaka. It explores the influence of multiple factors, including the rarely studied aspect of social influence. ...

July 28, 2025 · 2 min · Research Team

Enforcing asymptotic behavior with DNNs for approximation and regression in finance

Enforcing asymptotic behavior with DNNs for approximation and regression in finance ArXiv ID: 2411.05257 “View on arXiv” Authors: Unknown Abstract We propose a simple methodology to approximate functions with given asymptotic behavior by specifically constructed terms and an unconstrained deep neural network (DNN). The methodology we describe extends to various asymptotic behaviors and multiple dimensions and is easy to implement. In this work we demonstrate it for linear asymptotic behavior in one-dimensional examples. We apply it to function approximation and regression problems where we measure approximation of only function values (Vanilla Machine Learning''-VML) or also approximation of function and derivative values (Differential Machine Learning’’-DML) on several examples. We see that enforcing given asymptotic behavior leads to better approximation and faster convergence. ...

November 8, 2024 · 2 min · Research Team

Capital Structure Theories and its Practice, A study with reference to select NSE listed public sectors banks, India

Capital Structure Theories and its Practice, A study with reference to select NSE listed public sectors banks, India ArXiv ID: 2307.14049 “View on arXiv” Authors: Unknown Abstract Among the various factors affecting the firms positioning and performance in modern day markets, capital structure of the firm has its own way of expressing itself as a crucial one. With the rapid changes in technology, firms are being pushed onto a paradigm that is burdening the capital management process. Hence the study of capital structure changes gives the investors an insight into firm’s behavior and intrinsic goals. These changes will vary for firms in different sectors. This work considers the banking sector, which has a unique capital structure for the given regulations of its operations in India. The capital structure behavioral changes in a few public sector banks are studied in this paper. A theoretical framework has been developed from the popular capital structure theories and hypotheses are derived from them accordingly. The main idea is to validate different theories with real time performance of the select banks from 2011 to 2022. Using statistical techniques like regression and correlation, tested hypotheses have resulted in establishing the relation between debt component and financial performance variables of the select banks which are helping in understanding the theories in practice. ...

July 26, 2023 · 2 min · Research Team