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The dynamics of expected returns: evidence from multi-scale time series modelling

Bianchi, Daniele and Tamoni, Andrea (2016) The dynamics of expected returns: evidence from multi-scale time series modelling. Financial Markets Group Discussion Papers (752). Financial Markets Group, The London School of Economics and Political Science, London, UK.

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Conventional wisdom posits that all the relevant investors' information lies at the highest possible frequency of observation, so that long-run expected returns can be mechanically inferred by a forward aggregation of short-run estimates. We reverse such logic and propose a novel framework to model and extract the dynamics of latent short-term expected returns by coherently combining the lower-frequency information embedded in multiple predictors. We show that the information cascade from low- to high-frequency levels allows to identify long-lasting effects on expected returns that cannot be captured by standard persistent ARMA processes. The empirical analysis demonstrates that the ability of the model to capture simultaneously medium- to long-term fluctuations in the dynamics of expected returns, has first order implications for forecasting and investment decisions.

Item Type: Monograph (Discussion Paper)
Official URL:
Additional Information: © 2016 The Authors
Divisions: Finance
Subjects: H Social Sciences > HC Economic History and Conditions
H Social Sciences > HG Finance
JEL classification: G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice; Investment Decisions
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Other Model Applications
Date Deposited: 08 Jun 2023 10:48
Last Modified: 16 Sep 2023 00:01

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