Citation:
Arratia, A., Gzyl, H., & Mayoral, S. (2022). Tracking a Well Diversified Portfolio with Maximum Entropy in the Mean. Mathematics, 10 (4), p. 557.
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Comunidad de Madrid Agencia Estatal de Investigación (España)
Sponsor:
The work of the third author has been supported by the Madrid Government (Comunidad
de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University
Professors (EPUC3M12), and in the context of the V PRICIT (Regional Programme of Research
and Technological Innovation). We acknowledge financial support from Ministerio de Ciencia e
Innovacion grant PID2020-115744RB-I00.
Project:
Comunidad de Madrid. EPUC3M12 Gobierno de España. PID2020-115744RB-I00
Keywords:
Benchmark Tracking
,
Maximum entropy in mean for linear programming problems
,
Optimal portfolio
,
Well diversified portfolio
In this work we address the following problem: Having chosen a well diversified portfolio, we show how to improve on its return, maintaining the diversification. In order to achieve this boost on return we construct a neighborhood of the well diversified portfIn this work we address the following problem: Having chosen a well diversified portfolio, we show how to improve on its return, maintaining the diversification. In order to achieve this boost on return we construct a neighborhood of the well diversified portfolio and find a portfolio that maximizes the return in that neighborhood. For that we use the method of maximum entropy in the mean to find a portfolio that yields any possible return up to the maximum return within the neighborhood. The implicit bonus of the method is that if the benchmark portfolio has acceptable risk and diversification, the portfolio of maximum return in that neighborhood will also have acceptable risk and diversification.[+][-]