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Article

Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?

1
Department of Economics, Universidade Federal de Santa Catarina & CNPq, Florianópolis 88040-970, Brazil
2
Department of Economics, University of Pretoria, Pretoria 0002, South Africa
3
Department of Statistics, Universidade Federal do Rio Grande do Sul, Porto Alegre 91509-900, Brazil
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(11), 2042; https://doi.org/10.3390/math8112042
Received: 16 September 2020 / Revised: 3 November 2020 / Accepted: 12 November 2020 / Published: 16 November 2020
(This article belongs to the Special Issue Advanced Methods in Mathematical Finance)
This paper analyzes the forecast performance of historical S&P500 and Dow Jones Industrial Average (DJIA) excess returns while using nonparametric functional data analysis (NP-FDA). The empirical results show that the NP-FDA forecasting strategy outperforms not only the the prevailing-mean model, but also the traditional univariate predictive regressions with standard predictors used in the literature and, most cases, also combination approaches that use all predictors jointly. In addition, our results clearly have important implications for investors, from an asset allocation perspective, a mean-variance investor realizes substantial economic gains. Indeed, our results show that NP-FDA is the only one individual model that can overcome the historical average forecasts for excess returns in statistically and economically significant manners for both S&P500 and DJIA during the entire period, NBER recession, and expansions periods. View Full-Text
Keywords: return forecast; nonparametric functional data analysis; performance evaluation; predictive regression; classical financial mathematics return forecast; nonparametric functional data analysis; performance evaluation; predictive regression; classical financial mathematics
MDPI and ACS Style

Caldeira, J.F.; Gupta, R.; Torrent, H.S. Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value? Mathematics 2020, 8, 2042. https://doi.org/10.3390/math8112042

AMA Style

Caldeira JF, Gupta R, Torrent HS. Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value? Mathematics. 2020; 8(11):2042. https://doi.org/10.3390/math8112042

Chicago/Turabian Style

Caldeira, João F., Rangan Gupta, and Hudson S. Torrent 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?" Mathematics 8, no. 11: 2042. https://doi.org/10.3390/math8112042

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