How Much Do Subjective Growth Expectations Matter for Asset Prices?
Extensive technical appendices detail derivations, proofs, calibration, and robustness analysis for a sophisticated financial asset pricing model.
What it examines
This study develops a method to measure how changes in investors’ growth expectations affect stock prices. It uses high-frequency data from analyst reports, latent factor models, and demand-based pricing models. The approach aims to provide new insights into the gradual incorporation of growth expectations into asset prices.
What it concludes
The research finds that growth expectation changes impact prices much less than standard models suggest because investors adjust slowly. This has practical use in asset pricing, risk management, and market forecasting. Future work could investigate the reasons behind these gradual adjustments and test the model under different economic conditions.
Evidence objects
Study finds investor growth expectations minimally impact asset prices, with merely $$10%$$ to $$30%$$ of changes reflected instantly, challenging traditional theories that predicted near-full, immediate incorporation of new expectations significantly.
key_findings bullet 1 · key_findings · validation V0
Novel structural methodology employs analyst data and latent factor models to extract shocks and investor learning effects, introducing terms like $$M_g$$ and investor price elasticities linking beliefs to market outcomes.
key_findings bullet 2 · key_findings · validation V0
Analysis reveals subjective growth forecast biases exist but are diminished by portfolio adjustment costs and sluggish capital flow, explaining limited return volatility and muted overreaction in markets across global exchanges.
key_findings bullet 3 · key_findings · validation V0
This paper innovatively addresses asset pricing by modeling investors gradual incorporation of subjective growth expectations rather than immediate inclusion. Employing a novel structural methodology that recovers expectation shifts from analyst announcements, it contributes fresh empirical and theoretical insights, intersecting quantitative finance, offering valuable implications for stock and equity market debates.
key_findings bullet 4 · key_findings · validation V0
Raw abstract and provenance
No abstract available.
Source row: 1055 · abstract type: unknown