Applied mean-ETL optimization in using earnings forecasts

Autor:	Svetlozar T. Rachev, Yu Mu, Barret Pengyuan Shao
Rok vydání:	2015
Předmět:	Rate of return on a portfolio Actuarial science Earnings Econometrics Economics Portfolio Multivariate normal distribution Business and International Management Portfolio optimization Time series Stock (geology) Portfolio construction
Zdroj:	International Journal of Forecasting. 31:561-567
ISSN:	0169-2070
DOI:	10.1016/j.ijforecast.2014.10.005
Popis:	In this article, we apply the mean-expected tail loss (ETL) portfolio optimization to the consensus temporary earnings forecasting (CTEF) data from global equities. The time series model with multivariate normal tempered stable (MNTS) innovations is used to generate the out-of-sample scenarios for the portfolio optimization. We find that (1) the CTEF variable continues to be of value in portfolio construction, (2) the mean-ETL portfolio optimization produces statistically significant active returns, and (3) the active returns generated in the mean-ETL portfolio with CTEF indicate a statistically significant stock selection.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::462744a9c6bdaef0e992b7e1dce05702 https://doi.org/10.1016/j.ijforecast.2014.10.005 Zobrazit plný text záznamu Full Text from ScienceDirect