Market Anomalies

Fact, Fiction, and the Size Effect ArXiv ID: ssrn-3177539 “View on arXiv” Authors: Unknown Abstract In the earliest days of empirical work in academic finance, the size effect was the first market anomaly to challenge the standard asset pricing model and promp Keywords: Size Effect, Asset Pricing, Market Anomalies, Equity Valuation, Small Cap Stocks, Equities Complexity vs Empirical Score Math Complexity: 2.5/10 Empirical Rigor: 8.0/10 Quadrant: Street Traders Why: The paper primarily uses standard statistical tests on public datasets (like CRSP) and factor return data (Fama-French) to empirically dissect the size effect, with minimal advanced mathematical formalism beyond basic regression and performance metrics. flowchart TD A["Research Goal: Investigate the existence<br>and persistence of the Size Effect"] --> B["Data Inputs: Historical equity data,<br>CRSP database, Fama-French factors"] B --> C["Methodology: Portfolio Sorts<br>& Regression Analysis"] C --> D{"Computational Process:<br>Decomposing Size Premium"} D -- "Statistical Testing" --> E["Key Findings: Size Effect is<br>conditional on volatility & liquidity"] D -- "Out-of-Sample Validation" --> E E --> F["Outcome: Small-cap premium<br>diminishes after accounting for<br>risk factors & data snooping"]

From Efficient Market Theory to BehavioralFinance ArXiv ID: ssrn-349660 “View on arXiv” Authors: Unknown Abstract The efficient markets theory reached the height of its dominance in academic circles around the 1970s. Faith in this theory was eroded by a succession of discov Keywords: efficient markets hypothesis, behavioral finance, market anomalies, asset pricing, financial bubbles, Equities Complexity vs Empirical Score Math Complexity: 6.5/10 Empirical Rigor: 4.0/10 Quadrant: Lab Rats Why: The paper presents formal econometric models and variance tests (e.g., present value equations, vector autoregressions) indicating advanced math, but relies on historical data analysis and theoretical critique without detailed backtest specifications, datasets, or implementation code. flowchart TD A["Research Goal: <br/>Explain Market Anomalies"] --> B["Methodology: <br/>Comparative Analysis"] B --> C["Data: <br/>Equities & Historical Prices"] C --> D["Computational Process: <br/>Test EMH vs. Behavioral Models"] D --> E["Key Findings: <br/>Behavioral Factors Drive Bubbles"] D --> F["Key Findings: <br/>Markets are not Fully Efficient"]

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<br/>Investigate Market Anomalies"] --> B["Data Input<br/>Historical Equity Returns"] B --> C["Methodology<br/>Test EMH vs. Behavioral Factors"] C --> D{"Analysis<br/>Model Comparison"} D -- EMH Framework --> E["EMH Outcome<br/>Limited Explanatory Power"] D -- Behavioral Framework --> F["Behavioral Outcome<br/>Captures Market Anomalies"] E --> G["Key Finding<br/>EMH is a Special Case<br/>Behavioral Finance Explains Reality"] F --> G