Slicing an Asset to Learn about Its Future: A New Perspective on Return and Cash-Flow Forecasting

82 Pages Posted: 23 Oct 2023 Last revised: 27 Jun 2024

See all articles by Ye Li

Ye Li

University of Pennsylvania - Finance Department; University of Washington - Foster School of Business

Chen Wang

University of Notre Dame - Mendoza College of Business

Date Written: August 31, 2023

Abstract

Slicing an asset by payout horizons unseals information about its future returns and cash flows. As an example, we slice an equity market index into granular pieces (dividend strips) and show that valuation ratios of its strips span the underlying state variables of the index. Strip valuation ratios form a term structure. The level and slope strongly predict the index dividends. The slope alone is sufficient for forecasting the index return. The steepening and flattening of valuation term structure reflect discount-rate variations rather than information on the cash-flow trajectory, because market participants have very limited information about long-term cash flows.

Keywords: state space dimension, cash flow expectations, return predictability, valuation term structure, machine learning

JEL Classification: G14

Suggested Citation

Li, Ye and Wang, Chen, Slicing an Asset to Learn about Its Future: A New Perspective on Return and Cash-Flow Forecasting (August 31, 2023). Available at SSRN: https://ssrn.com/abstract=4561560 or http://dx.doi.org/10.2139/ssrn.4561560

Ye Li

University of Pennsylvania - Finance Department ( email )

The Wharton School
3620 Locust Walk
Philadelphia, PA 19104
United States

University of Washington - Foster School of Business ( email )

Box 353200
Seattle, WA 98195
United States

HOME PAGE: http://https://yeli-macrofinance.com/

Chen Wang (Contact Author)

University of Notre Dame - Mendoza College of Business ( email )

Notre Dame, IN 46556-5646
United States

HOME PAGE: http://chenwang.one/

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