We review a few of the relavitely recent developments in cone programming that seem to have important applications in financial planning. In particular, we go over the semidefinite programming representation of a polynomial inequality as given by Nesterov. We mention some relevant references which show the power of cone programming in portfolio optimization. Then we turn to the recent work of L...

We consider the problem of portfolio optimization under VaR risk measure taking into account transaction costs. Fixed costs as well as impact costs as a nonlinear function of trading activity are incorporated in the optimal portfolio model. Thus the obtained model is a nonlinear optimization problem with nonsmooth objective function. The model is solved by an iterative method based on a smoothi...

In this paper we test the effects of temporal aggregation (disaggregation) on the efficiency of portfolio construction using the mean variance optimization approach. Using Monte Carlo techniques and empirical data from the Athens Stocks Exchange we confirm that the use of temporally aggregated data effects very seriously the efficiency of the constructed portfolio. Especially as the degree of t...

In this paper, we study some discrete-time portfolio optimization problems. We introduce a discrete-time financial market model. The change in asset prices is modelled in contrast to the continuous-time market model by stochastic difference equations. We provide solutions of these stochastic difference equations. Then we introduce the discrete-time risk measures and the portfolio optimization p...

Portfolio selection is concerned with optimization of capital allocation to a large number of securities. In portfolio selection, risk analysis is one of the most important topics and research on quantitative definition of risk remains core of the topic. This paper proposes a novel risk definition for portfolio selection with uncertain returns. A risk curve is introduced and a new safe criterio...

We introduce a new methodology that incorporates advanced higher moments evaluation in a new approach of the Portfolio Selection problem, supported by effective Computational Intelligence models. The Evolutional Portfolio Optimization System (EPOS) extracts hidden patterns out of the numerous accounting data and financial statements filtering misguiding effects such as noise or fraud, offering ...

Portfolio methods provide an effective, principled way of combining a collection of acquisition functions in the context of Bayesian optimization. We introduce a novel approach to this problem motivated by an information theoretic consideration. Our construction additionally provides an extension of Thompson sampling to continuous domains with GP priors. We show that our method outperforms a ra...

According to the theory proposed by Acerbi & Scandolo (2008), the value of a portfolio is defined in terms of public market data and idiosyncratic portfolio constraints imposed by an investor holding the portfolio. Depending on the constraints, one and the same portfolio could have different values for different investors. As it turns out, within the Acerbi-Scandolo theory, portfolio valuation ...

In this work, the ability of the Dynamic Objectives Aggregation Methods to solve the portfolio rebalancing problem is investigated conducting a computational study on a set of instances based on real data. The portfolio model considers a set of realistic constraints and entails the simultaneously optimization of the risk on portfolio, the expected return and the transaction cost.