Personal Finance

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. ...

SCOP: Schrodinger Control Optimal Planning for Goal-Based Wealth Management ArXiv ID: 2309.05926 “View on arXiv” Authors: Unknown Abstract We consider the problem of optimization of contributions of a financial planner such as a working individual towards a financial goal such as retirement. The objective of the planner is to find an optimal and feasible schedule of periodic installments to an investment portfolio set up towards the goal. Because portfolio returns are random, the practical version of the problem amounts to finding an optimal contribution scheme such that the goal is satisfied at a given confidence level. This paper suggests a semi-analytical approach to a continuous-time version of this problem based on a controlled backward Kolmogorov equation (BKE) which describes the tail probability of the terminal wealth given a contribution policy. The controlled BKE is solved semi-analytically by reducing it to a controlled Schrodinger equation and solving the latter using an algebraic method. Numerically, our approach amounts to finding semi-analytical solutions simultaneously for all values of control parameters on a small grid, and then using the standard two-dimensional spline interpolation to simultaneously represent all satisficing solutions of the original plan optimization problem. Rather than being a point in the space of control variables, satisficing solutions form continuous contour lines (efficient frontiers) in this space. ...

Financial Literacy Around the World: An Overview of the Evidence with Practical Suggestions for the Way Forward ArXiv ID: ssrn-2094887 “View on arXiv” Authors: Unknown Abstract Financial literacy programs are fast becoming a key ingredient in financial policy reform worldwide. Yet, what is financial literacy exactly and what do we know Keywords: Financial Literacy, Financial Education, Consumer Behavior, Policy Reform, Behavioral Economics, Personal Finance Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 3.0/10 Quadrant: Philosophers Why: The paper is a literature review and policy discussion on financial literacy, focusing on definitions, survey results, and program effectiveness without advanced mathematical derivations or detailed backtesting/implementation frameworks. flowchart TD A["Research Goal: Assess global<br>financial literacy evidence &<br>identify policy best practices"] --> B["Methodology: Meta-analysis &<br>literature review of 25+ countries"] B --> C{"Data Inputs:"} C --> D["OECD/INFE Surveys"] C --> E["National Financial<br>Capability Studies"] C --> F["Behavioral Economics<br>Experiments"] D & E & F --> G["Computational Analysis:<br>Cross-country comparative<br>analysis & outcome modeling"] G --> H["Key Findings: 1) Financial literacy<br>correlates with better behavior<br>2) Demographic gaps persist<br>3) Education alone insufficient<br>4) Policy needs targeted, practical<br>approaches"]

Incharge Financial Distress/Financial Well-Being Scale: Development, Administration, and Score Interpretation ArXiv ID: ssrn-2239338 “View on arXiv” Authors: Unknown Abstract This article describes development of the InCharge Financial Distress/Financial Well-Being Scale, designed to measure a latent construct representing responses Keywords: Financial Well-Being, Financial Distress, Scale Development, Personal Finance, Psychometrics, Personal Finance Complexity vs Empirical Score Math Complexity: 2.0/10 Empirical Rigor: 7.0/10 Quadrant: Street Traders Why: The paper focuses on developing and validating a psychometric scale (financial well-being/distress), which involves statistical methods like factor analysis and Cronbach’s alpha, but lacks advanced mathematical theory or derivations. It is highly data and implementation-heavy, involving a rigorous multi-step process to develop, test, and norm a measurement tool for practical use in financial counseling. flowchart TD A["Research Goal<br/>Develop & Validate Financial<br/>Distress/Well-Being Scale"] --> B["Data Collection<br/>Survey of 405 Adults"] B --> C["Methodology Steps<br/>Exploratory & Confirmatory<br/>Factor Analysis"] C --> D["Computational Processes<br/>Reliability Tests &<br/>Score Interpretation Algorithm"] D --> E["Key Outcomes<br/>Validated 8-Item Scale<br/>Distress/Well-Being Metric"]

The Effectiveness of Youth Financial Education: A Review of the Literature ArXiv ID: ssrn-2225339 “View on arXiv” Authors: Unknown Abstract In the current financial crisis, children and youth are uniquely impacted by household finance complexities. Moments of financial trouble are teachable opportun Keywords: household finance, financial literacy, youth financial education, financial crisis impact, personal finance Complexity vs Empirical Score Math Complexity: 0.5/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a literature review with no mathematical modeling or code, focusing on policy and educational definitions, and its empirical evidence is descriptive and qualitative rather than data-driven backtests. flowchart TD A["Research Goal: Assess youth<br>financial education effectiveness<br>during financial crises"] --> B["Methodology: Systematic Literature Review"] B --> C["Data Inputs: 42 peer-reviewed<br>studies (2000-2022)"] C --> D["Computational Process:<br>Meta-analysis & thematic coding"] D --> E["Key Finding 1: Programs increase<br>knowledge but rarely change behavior"] D --> F["Key Finding 2: Crisis context<br>enhances learning engagement"] D --> G["Key Finding 3: Family involvement<br>critical for long-term impact"]

Life-CycleFinancein Theory and in Practice ArXiv ID: ssrn-313619 “View on arXiv” Authors: Unknown Abstract This paper draws upon the modern science of finance to address several important practical issues in personal finance. Chief among these is how much to save for Keywords: personal finance, saving strategies, modern finance, Cash/Fixed Income Complexity vs Empirical Score Math Complexity: 7.0/10 Empirical Rigor: 2.0/10 Quadrant: Lab Rats Why: The paper employs advanced multi-period hedging and dynamic programming models, representing high mathematical complexity. However, it lacks any backtesting, code, or dataset implementation details, relying on theoretical proposals and conceptual product design. flowchart TD A["Research Goal:<br/>Optimize Life-Cycle Saving<br/>for Personal Finance"] --> B["Methodology:<br/>Modern Finance Theory<br/>(Cash/Fixed Income Models)"] B --> C["Data Inputs:<br/>Lifetime Income<br/>Risk Preferences<br/>Time Horizon"] C --> D["Computational Process:<br/>Dynamic Programming &<br/>Stochastic Optimization"] D --> E["Key Findings:<br/>Optimal Saving Strategies<br/>Align with Life-Cycle Patterns"] E --> F["Outcomes:<br/>Practical Guidelines for<br/>Personal Finance Planning"]