Conference Agenda

 
 
Session Overview
Session
AP 11: Advances in Factor Analysis
Time:
Friday, 18/Aug/2023:
8:30am - 10:00am

Session Chair: Esther Eiling, University of Amsterdam
Location: 1A-33 (floor 1)


Presentations
ID: 1347

Anomaly or Possible Risk Factor? Simple-To-Use Tests

Benjamin Holcblat1, Abraham Lioui2, Michael Weber3

1University of Luxembourg, Luxembourg; 2EDHEC Business School; 3Booth School of Business, University of Chicago, CEPR, and NBER

Discussant: Seth Pruitt (Arizona State University)

Asset pricing theory predicts high expected returns are a compensation for risk. However, high expected returns might also represent anomalies due to frictions or behavioral biases. We propose two complementary tests to assess whether risk alone can explain differences in expected returns, provide general-equilibrium foundations, and study their properties in simulations. The tests account for any risk disliked by risk-averse individuals, including high-order moments and tail risks. The tests do not rely on the validity of a factor model or other parametric statistical models. Empirically, we find risk cannot explain a large majority of differences in expected returns of characteristic-sorted portfolios.

EFA2023_1347_AP 11_1_Anomaly or Possible Risk Factor Simple-To-Use Tests.pdf


ID: 1730

Asset-Pricing Factors with Economic Targets

Svetlana Bryzgalova1, Victor DeMiguel1, Sicong Li1, Markus Pelger2

1London Business School; 2Stanford University

Discussant: Mirela Sandulescu (University of Michigan)

We propose a method to estimate latent asset-pricing factors that incorporates economically motivated targets for both cross-sectional and time-series properties of the factors. Cross-sectional targets may capture the shape of loadings (monotonicity of expected returns across characteristic-sorted portfolios) or the pricing span of exogenous state variables (macroeconomic innovations or intermediary-based risk factors). Time-series targets may capture overall expected returns or mispricing relative to a benchmark reduced-form model. Using a large-scale set of assets, we show that these targets nudge risk factors to better span the pricing kernel, leading to substantially higher Sharpe ratios and lower pricing errors than conventional approaches.

EFA2023_1730_AP 11_2_Asset-Pricing Factors with Economic Targets.pdf


ID: 1396

Inflation Surprises in the Cross-section of Equity Returns

Antonio Gil de Rubio Cruz, Emilio Osambela, Berardino Palazzo, Francisco Palomino, Gustavo Suarez

Board of Governors of the Federal Reserve System, United States of America

Discussant: Fotis Grigoris (University of Iowa)

U.S. stocks' response to inflation surprises is, on average, robustly negative. Stocks' response to positive inflation surprises shows much more pronounced time-series variability than their response to negative inflation surprises. In our sample, stocks react significantly to positive inflation surprises only when there is a contemporaneous change in monetary policy expectations. In the cross-section, firms with low net leverage, large market capitalization, high market beta, low book-to-market, and low market power (i.e. low markups) are especially susceptible to inflation surprises.

EFA2023_1396_AP 11_3_Inflation Surprises in the Cross-section of Equity Returns.pdf