Anomalies-in-Finance

Anomaly: irregularity, deviation from the common order, exceptional condition or circumstance

we survey the literatures on anomalies in finance, which is used to explain the cross-sectional variation in stock returns, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. More specifically, we focus on three closely related questions:

1. what drive the cross-sectional variation in stock returns?

2. How much cross-sectional variation in expected returns can we actually predict?

3. How reliable are estimates of expected returns from econometric method or machine learning algorithms?

this repo is to collect papers on anomalies in finance with high impact, to help reseachers explore and expand the boundary of stock return predictability.

We're looking for pull requests related papers or reliable disclosure we should add, and better organization of the results.

Backgroud

If Efficient Market Hypothesis or Capital Asset Pricing Model(CAPM) holds, all securities should have the same risk-adjusted returns. Therefore, observable stock characteristics such as size, PE ratio, or marker-to-book ratios will be useless in finding undervalued (i.e., positive abnormal return) stocks or overvalued (i.e., negative abnormal return) stocks.

In fact, more and more empirical evidence shows that under some condition or circumstance, there do exist cross sectional variation in stock returns(which can be called anormalies in this context), which is inconsistent with maintained theories (e.g., CAPM) of asset-pricing behavior. significant market anormalies exist like size anomaly, value anomaly, momentum anomaly et al.

• size anomaly: smaller firms earn higher returns than larger firms of equivalent risk
• value anomaly: stocks with higher book-to-matket ratio carry a positive risk premium in their return
• liquidity anomaly: more liquid stocks tend to have higher expected returns
• momentum anomaly: winers (stocks which have performed well in the past) would continue to outperform losers in the near future.

Academics and practitioners are keenly interested in exploring anomalies(or firm attributes) and analyze their ability to explain cross-sectional stock returns. In other words, considering future stock returns is a function of current state varibale, we are interested in exploring what kinds of state variable can predict stock returns, which is also known as predictor/factor/alpha/indicator/determinents.

Surveys

• 2016 | Does academic research destroy stock return predictability? | McLean R D, Pontiff J. | SSRN | pdf

• 2017 | Replicating anomalies | Hou K, Xue C, Zhang L. | National Bureau of Economic Research | pdf

• 2017 | The characteristi|cs that provide independent information about average us monthly stock returns | Green, Jeremiah, John RM Hand, and X. Frank Zhang. | RFS | pdf

• 2018 | What Firm Characteristics Drive US Stock Returns?| Han Y, He A, Rapach D, et al. | SSRN |pdf