Summary: 2021 Betermier Investor Factors Appendix

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• What is a key objective of financial economics according to Campbell (2018)?

  - Relate equity risk premia to drivers of investor demand
  - Overcome challenge of empirically successful pricing factors unrelated to investor preferences, risks, and biases
  - Tie empirical pricing factors to consumption through economic mechanisms

• Why is it challenging to achieve the key objective of linking equity risk premia to investor demand?

  - Empirically successful pricing factors not directly related to investor preferences, risks, and biases
  - Disconnect between pricing factors and consumption prompts search for economic mechanisms
  - Consumption data are noisy and measured at relatively low frequency

• What does the new literature focus on in relation to investor-based asset pricing according to recent studies?

  - Exploiting rich information in investor portfolio holdings observed without error in real time
  - Using institutional holdings data to examine allocation of interest rate risk, currency risk, and transmission of monetary policy
  - Institutional holdings studied in relation to investors’ influence on asset prices

• Why is investigating individual investor portfolios considered theoretically important in financial theory?

  - Predict interactions between individual portfolio decisions and asset returns
  - Retail investors, though owning a limited fraction of aggregate equity, can drive stock returns due to elastic response to stock prices
  - Provides insights into preferences and trading behaviors for micro-founding investor-based asset pricing models

• What is a key benefit of exploring the portfolios of individual investors in understanding investor-based asset pricing models?

  - Informative about preferences and trading behaviors crucial for micro-founding investor-based asset pricing models
  - Relationships between stockholdings and socioeconomic characteristics can be measured in panel datasets
  - Extensive household finance literature has successfully applied empirical strategy to components of household balance sheets

• What are the major findings of the study regarding the factors that price the cross-section of equity returns?

  - The portfolios of stocks sorted by the age or wealth of individual investors produce powerful pricing factors
  - An empirically verified three-factor model includes mature-minus-young factor, high wealth-minus-low wealth factor, and the market factor
  - This model performs well in pricing the cross-section of stock returns both in and out of the sample

• What challenges were faced while investigating the factors that price the cross-section of equity returns and how were they resolved?

  - Available datasets often lack crucial dimensions for rigorous asset pricing tests
  - Datasets need a long time series, a large and diverse pool of investors, and detailed investor characteristics
  - The study overcame this challenge by using detailed portfolio data on all Norwegian direct stockholders between 1997 and 2018

• What is the significance of studying the portfolios of individual investors and how does it relate to the factors that price the cross-section of equity returns?

  - Sorting stocks by characteristics of individual investors reveals factors that price the cross-section of stock returns
  - New investor factors are compared with traditional factors from firm characteristics
  - The study examines how investor biases, risks, and characteristics affect portfolio tilts towards the new factors

• How did the study contribute to investigating the factors that price the cross-section of equity returns?

  - The study theoretically shows that sorting stocks by the age or wealth of individual investors should yield powerful pricing factors
  - Empirically, a three-factor model was validated using Norwegian panel data, showcasing its effectiveness in pricing stock returns
  - The study emphasizes the importance of investor characteristics in influencing pricing factors

• Why is it challenging to perform rigorous asset pricing tests and how did the study overcome these challenges?

  - Available datasets often lack key dimensions such as a long time series, a diverse pool of investors, and detailed investor characteristics required for rigorous testing
  - To address this, the study utilized detailed portfolio data on all Norwegian direct stockholders between 1997 and 2018
  - The study highlights the significance of having comprehensive data for accurate asset pricing tests in the cross-section of equity returns