Asset Pricing

Institutional Investors and Stock Market Volatility ArXiv ID: ssrn-442940 “View on arXiv” Authors: Unknown Abstract We present a theory of excess stock market volatility, in which market movements are due to trades by very large institutional investors in relatively illiquid Keywords: Stock Market Volatility, Institutional Investors, Illiquidity, Asset Pricing, Market Microstructure Complexity vs Empirical Score Math Complexity: 7.5/10 Empirical Rigor: 6.0/10 Quadrant: Holy Grail Why: The paper is mathematically dense, employing power-law distributions and statistical physics methods to model investor behavior, while providing strong empirical backing with real-world data on stock market volatility, returns, and trading volumes. flowchart TD A["Research Goal: Explain excess stock market volatility"] B["Theory: Large institutional investors<br>in illiquid markets drive price swings"] C["Data: Institutional trading &<br>stock liquidity measures"] D["Methodology: Empirical asset pricing<br>& market microstructure analysis"] E["Key Findings: Institutional flows<br>significantly amplify market volatility"] A --> B B --> C C --> D D --> E

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