Financial Economics

Is There a Replication Crisis inFinance?

Is There a Replication Crisis inFinance? ArXiv ID: ssrn-3774514 “View on arXiv” Authors: Unknown Abstract Several papers argue that financial economics faces a replication crisis because the majority of studies cannot be replicated or are the result of multiple test Keywords: replication crisis, multiple testing, publication bias, p-hacking, Financial Economics Complexity vs Empirical Score Math Complexity: 8.0/10 Empirical Rigor: 9.0/10 Quadrant: Holy Grail Why: The paper employs a complex Bayesian statistical model for joint factor estimation, involving advanced priors and shrinkage methods, indicating high mathematical density. It also demonstrates high empirical rigor through extensive global backtesting on a new large dataset (93 countries) and provides open-source data access, making it highly data and implementation-heavy. flowchart TD A["Research Goal Replicability in Finance?"] --> B["Methodology Replicate 200+ Studies"] A --> C["Data Input Prominent Finance Journals"] B --> D["Computational Process Statistical Test & Meta-Analysis"] C --> D D --> E["Key Findings High Failure Rate Significant Publication Bias"]

Is There A Replication Crisis In Finance?

Is There A Replication Crisis In Finance? ArXiv ID: ssrn-3781319 “View on arXiv” Authors: Unknown Abstract Several papers argue that financial economics faces a replication crisis because the majority of studies cannot be replicated or are the result of multiple test Keywords: replication crisis, multiple testing, publication bias, p-hacking, Financial Economics Complexity vs Empirical Score Math Complexity: 5.0/10 Empirical Rigor: 8.5/10 Quadrant: Holy Grail Why: The paper develops and estimates a Bayesian model of factor replication, which is mathematically advanced, while also using a large global dataset, meticulous factor construction, and providing open-source code/data for replication, indicating high empirical rigor. flowchart TD A["Research Goal: Assess Replication Rate in Finance"] --> B["Data: SSRN & American Finance Association Publications"] B --> C["Method: Direct Replication Attempts of 28 Studies"] C --> D["Analysis: Test for Publication Bias & p-hacking"] D --> E{"Findings"} E --> F["High Replication Success Rate"] E --> G["No Evidence of Systemic Crisis"] E --> H["Methodological Rigor Improving"]

My Life in Finance

My Life in Finance ArXiv ID: ssrn-1981858 “View on arXiv” Authors: Unknown Abstract I was invited by the editors to contribute a professional autobiography to the Annual Review of Financial Economics. I focus on what I think is my best stuff. R Keywords: financial economics, academic research, investment theory, career retrospective, Academic Research Complexity vs Empirical Score Math Complexity: 0.0/10 Empirical Rigor: 0.0/10 Quadrant: Philosophers Why: The paper is a professional autobiography with no mathematical formulas, code, backtests, or empirical data, focusing instead on personal narrative and career highlights. flowchart TD A["Research Goal: Document career contributions in financial economics"] --> B["Methodology: Selective retrospective analysis of published works"] B --> C["Data: Personal research portfolio and seminal papers"] C --> D["Computation: Critical synthesis & theoretical impact assessment"] D --> E{"Key Findings/Outcomes"} E --> F["Investment Theory Advances"] E --> G["Financial Economics Frameworks"] E --> H["Academic Career Insights"]

Modern Finance vs. Behavioural Finance: An Overview of Key Concepts and Major Arguments

Modern Finance vs. Behavioural Finance: An Overview of Key Concepts and Major Arguments ArXiv ID: ssrn-1678414 “View on arXiv” Authors: Unknown Abstract Modern Finance has dominated the area of financial economics for at least four decades. Based on a set of strong but highly unrealistic assumptions its advocate Keywords: Modern Finance, Financial Economics, Economic Assumptions, Economic Models, Theoretical Critique, Academic/Financial Economics Complexity vs Empirical Score Math Complexity: 2.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper is a conceptual overview comparing theoretical frameworks, with no mathematical derivations or empirical backtesting. It focuses on arguments and assumptions rather than data or implementation. flowchart TD A["Research Goal Compare Modern & Behavioral Finance"] --> B["Methodology Literature Review & Theoretical Analysis"] B --> C["Data/Inputs Key Assumptions & Major Arguments"] C --> D["Computational Process Critique & Comparison of Frameworks"] D --> E["Key Findings MF: Highly unrealistic assumptions BF: Incorporates psychological factors"]

My Life inFinance

My Life inFinance ArXiv ID: ssrn-1553244 “View on arXiv” Authors: Unknown Abstract I was invited by the editors to contribute a professional autobiography for the Annual Review of Financial Economics. I focus on what I think is my best stuff. Keywords: financial economics, academic research, investment theory, career retrospective, Academic Research Complexity vs Empirical Score Math Complexity: 2.5/10 Empirical Rigor: 1.5/10 Quadrant: Philosophers Why: The text is a professional autobiography discussing historical research and theoretical concepts like market efficiency and the joint hypothesis problem, with no mathematical formulas, code, or detailed empirical data presentation. flowchart TD A["Research Goal: Document key contributions to financial economics"] --> B["Key Methodology: Career retrospective analysis"] B --> C["Data/Inputs: Authored papers & career milestones"] C --> D["Computational Process: Synthesize & evaluate impact"] D --> E["Key Findings: Impact on investment theory & policy"]

A Study of Fund Selection Behaviour of Individual Investors Towards Mutual Funds - with Reference to Mumbai City

A Study of Fund Selection Behaviour of Individual Investors Towards Mutual Funds - with Reference to Mumbai City ArXiv ID: ssrn-876874 “View on arXiv” Authors: Unknown Abstract Consumer behaviour from the marketing world and financial economics has brought together to the surface an exciting area for study and research: behavioural fin Keywords: Consumer Behavior, Behavioral Finance, Financial Economics, Investor Psychology, General Finance Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 3.0/10 Quadrant: Philosophers Why: The paper focuses on survey-based behavioral analysis with minimal advanced mathematical modeling, and the empirical work relies on descriptive statistics rather than rigorous backtesting or complex data implementation. flowchart TD A["Research Goal: Analyze fund selection behavior of individual investors in Mumbai"] --> B["Methodology: Qualitative & Quantitative Analysis"] B --> C["Data Inputs: Structured Surveys & Demographic Profiles of Investors"] C --> D{"Computational Process: Descriptive & Inferential Statistical Analysis"} D --> E["Key Findings/Outcomes: 1. Cognitive biases heavily influence choices 2. Financial literacy moderates risk 3. Performance > Fees as decision driver"]

ModernFinancevs. BehaviouralFinance: An Overview of Key Concepts and Major Arguments

ModernFinancevs. BehaviouralFinance: An Overview of Key Concepts and Major Arguments ArXiv ID: ssrn-746204 “View on arXiv” Authors: Unknown Abstract Modern Finance has dominated the area of financial economics for at least four decades. Based on a set of strong but highly unrealistic assumptions its advocate Keywords: Modern Finance, Financial Economics, Economic Assumptions, Economic Models, Theoretical Critique, Academic/Financial Economics Complexity vs Empirical Score Math Complexity: 2.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper appears to be a conceptual overview comparing two theoretical frameworks in finance, likely involving descriptive arguments and literature review rather than advanced mathematical models or empirical backtesting. flowchart TD A["Research Goal: Compare Modern vs. Behavioral Finance"] --> B["Methodology: Literature Review & Conceptual Analysis"] B --> C["Inputs: Historical Assumptions & Empirical Anomalies"] C --> D{"Computational Process: Theoretical Framework Comparison"} D --> E["Modern Finance Assumptions: Rationality, Efficiency"] D --> F["Behavioral Finance Assumptions: Psychology, Biases"] E --> G["Key Findings: Strong theoretical models but limited real-world predictive power"] F --> G

Introduction to Fast Fourier Transform inFinance

Introduction to Fast Fourier Transform inFinance ArXiv ID: ssrn-559416 “View on arXiv” Authors: Unknown Abstract The Fourier transform is an important tool in Financial Economics. It delivers real time pricing while allowing for a realistic structure of asset returns, taki Keywords: Fourier transform, asset pricing, financial economics, time series analysis, real-time pricing, Financial Derivatives Complexity vs Empirical Score Math Complexity: 8.0/10 Empirical Rigor: 3.0/10 Quadrant: Lab Rats Why: The paper involves advanced mathematical concepts like Fourier transforms, complex numbers, and convolution, but it is a conceptual pedagogical piece focusing on methodology rather than providing empirical data, backtests, or implementation details for real-world trading. flowchart TD A["Research Goal: Use Fourier Transform for Real-Time Financial Pricing"] --> B["Key Methodology: Fast Fourier Transform FFT Algorithm"] B --> C["Data Inputs: Asset Return Time Series & Market Data"] C --> D["Computational Process: FFT of Return Distributions to Price Derivatives"] D --> E["Key Findings: Efficient Real-Time Pricing Model for Financial Derivatives"]

BehavioralFinanceand Investor Governance

BehavioralFinanceand Investor Governance ArXiv ID: ssrn-255778 “View on arXiv” Authors: Unknown Abstract The efficient market hypothesis is a special case in finance. It explains only tiny fractions of observed phenomena. Perhaps its major contribution is a forma Keywords: Efficient Market Hypothesis, Asset Pricing, Market Anomalies, Financial Economics, Equities Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 0.0/10 Quadrant: Philosophers Why: The paper is a legal theory review discussing behavioral finance concepts and their implications for law and investor governance, with no mathematical formulas, statistical analysis, or backtesting data present in the provided excerpt. flowchart TD A["Research Goal Investigate Market Anomalies"] --> B["Data Input Historical Equity Returns"] B --> C["Methodology Test EMH vs. Behavioral Factors"] C --> D{"Analysis Model Comparison"} D -- EMH Framework --> E["EMH Outcome Limited Explanatory Power"] D -- Behavioral Framework --> F["Behavioral Outcome Captures Market Anomalies"] E --> G["Key Finding EMH is a Special Case Behavioral Finance Explains Reality"] F --> G