Search results for "Portfolio selection."
showing 8 items of 8 documents
Designing and pricing guarantee options in defined contribution pension plans
2015
Abstract The shift from defined benefit (DB) to defined contribution (DC) is pervasive among pension funds, due to demographic changes and macroeconomic pressures. In DB all risks are borne by the provider, while in plain vanilla DC all risks are borne by the beneficiary. However, for DC to provide income security some kind of guarantee is required. A minimum guarantee clause can be modeled as a put option written on some underlying reference portfolio and we develop a discrete model that selects the reference portfolio to minimize the cost of a guarantee. While the relation DB–DC is typically viewed as a binary one, the model shows how to price a wide range of guarantees creating a continu…
Selezione di Portafoglio e Metaeuristiche
2013
Il problema della selezione del portafoglio (PSP) ha come obiettivo quello di determinare, disponendo di un dato insieme di titoli, il portafoglio che minimizza una misura di rischio per un dato livello di rendimento minimo richiesto. Sebbene nella sua formulazione originaria il PSP può essere risolto utilizzando algoritmi di programmazione lineare o quadratica, l'inclusione di ulteriori vincoli ed obiettivi rende il problema computazionalmente difficile. Nel presente lavoro viene proposto un approccio metaeuristico al PSP in cui vengono considerate diverse misure di distanza tra i portafogli della frontiera efficiente (Mean-Variance) ed il portafoglio ottimo che si ottiene in corrispondenz…
Grading investment diversification options in presence of non-historical financial information
2021
Modern portfolio theory deals with the problem of selecting a portfolio of financial assets such that the expected return is maximized for a given level of risk. The forecast of the expected individual assets’ returns and risk is usually based on their historical returns. In this work, we consider a situation in which the investor has non-historical additional information that is used for the forecast of the expected returns. This implies that there is no obvious statistical risk measure any more, and it poses the problem of selecting an adequate set of diversification constraints to mitigate the risk of the selected portfolio without losing the value of the non-statistical information owne…
A Conditional Value–at–Risk Model for Insurance Products with Guarantee
2009
We propose a model to select the optimal portfolio which underlies insurance policies with a guarantee. The objective function is defined in order to minimise the conditional value at-risk (CVaR) of the distribution of the losses with respect to a target return. We add operational and regulatory constraints to make the model as flexible as possible when used for real applications. We show that the integration of the asset and liability side yields superior performances with respect to naive fixed-mix portfolios and asset based strategies. We validate the model on out-of-sample scenarios and provide insights on policy design.
Minimising value-at-risk in a portfolio optimisation problem using a multi-objective genetic algorithm
2011
[EN] In this paper, we develop a general framework for market risk optimisation that focuses on VaR. The reason for this choice is the complexity and problems associated with risk return optimisation (non-convex and non-differential objective function). Our purpose is to obtain VaR efficient frontiers using a multi-objective genetic algorithm (GA) and to show the potential utility of the algorithm to obtain efficient portfolios when the risk measure does not allow calculating an optimal solution. Furthermore, we measure differences between VaR efficient frontiers and variance efficient frontiers in VaR-return space and we evaluate out-sample capacity of portfolios on both bullish and bearis…
Distance Measures for Portfolio Selection
2017
The classical Markowitz approach to the portfolio selection problem (PSP) consists of selecting the portfolio that minimises the return variance for a given level of expected return. By solving the problem for different values of this expected return we obtain the Pareto efficient frontier, which is composed of non-dominated portfolios. The final user has to discriminate amongst these points by resorting to an external criterion in order to decide which portfolio to invest in. We propose to define an external portfolio that corresponds to a desired criterion, and to assess its distance from the Markowitz frontier in market allowing for short-sellings or not. We show that this distance is ab…
Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming
2008
AbstractThis paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.
An user friendly Real Options based Model to Optimize Pharmaceutical R&D Portfolio
2013
Pharmaceutical industry pays great attention to its R&D process because it is a long, dynamic, very expensive, and uncertain process. On the other hand this process can be modelled as a step-wise process and each stage allows to achieve better information and generally lower uncertainty. In order to build up the best portfolio a tool able to capture the intrinsic flexible nature of the process should be selected: real options analysis has this characteristic but as widely demonstrated in literature, is narrowed to very limited cases because its perceived complexity. Basing on OptFolio, a model available in literature, this paper proposes an user friendly programming model based on Real Opti…