Analysing assets' performance inside a portfolio

This paper is focused on enlarging the performance inside a portfolio that provides the Treynor ratio by relating portfolio weights with performance indicators. Intuition suggests that the higher the weight of an asset, the higher should be its expected performance. These weights, and the informatio...

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Detalles Bibliográficos
Autores: Bosch Badia, M. Teresa|||0000-0002-1204-1956, Montllor i Serrats, Joan|||0000-0001-5984-293X, Tarrazón Rodón, Ma. Antonia|||0000-0001-8964-6219
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:201183
Acceso en línea:https://ddd.uab.cat/record/201183
https://dx.doi.org/urn:doi:10.1080/23322039.2016.1270251
Access Level:acceso abierto
Palabra clave:Beta
Common stocks performance
Gini portfolios
Treynor ratio
Descripción
Sumario:This paper is focused on enlarging the performance inside a portfolio that provides the Treynor ratio by relating portfolio weights with performance indicators. Intuition suggests that the higher the weight of an asset, the higher should be its expected performance. These weights, and the information that we can obtain from their analysis, are not only relevant for investors but also for corporate managers. Nevertheless, the available performance indicators are not linked to portfolio weights. In order to fulfil this gap we answer three questions: which is the minimum risk premium that justifies holding an asset in long position? How can we analyse if the performance of an asset justifies the budget's weight invested in it? And, how can we apply ex-post optimisation to performance analysis? Methodologically, we centre the analysis on the definition of crossed beta and the net risk premium ratio that stems from it. The latter fulfils the axioms of risk/reward performance measures. The three answers to the questions are related to the net risk premium. The analysis in developed for the Mean-Variance and Mean-Gini models. The empirical illustration, based on DJIA assets, that completes the paper shows how the analysis of portfolio weights provides relevant information about the performance of assets.