Protecting portfolio against extreme losses is a fundamentally difficult task since past experience provides a poor guidance for the future. This paper focuses on a robust approach to the portfolio insurance, which does not require historical calibration, and therefore avoids the hazards of data...

We propose a novel linear approximation of expected utility. The approximation guides us as we transfer the traditional quadratic dependence of third-order stochastic dominance (TSD) into an equivalent linear system. The finding also shows a dual relationship between traditional low partial...

Conventional wisdom holds that multiperiod portfolio optimization problems are best, if not only, solved by dynamic programming. But dynamic programming suffers from the curse of dimensionality whereby optimization becomes intractable as time horizon and number of assets increase, thereby...

A framework is developed for portfolio optimization with higher-order Stochastic Dominance constraints. A finite system of restrictions on the lower partial moments can be used for evaluating the efficiency of a given benchmark and for constructing enhanced portfolios which dominate the...

We introduce a generic solver for dynamic portfolio allocation problems when the market exhibits return predictability, price impact and partial observability. We assume that the price modeling can be encoded into a linear state-space and we demonstrate how the problem then falls into the LQG...

An optimization method is developed for constructing investment portfolios which stochastically dominate a given benchmark for all decreasing absolute risk-averse investors, using Quadratic Programming. The method is applied to standard data sets of historical returns of equity price reversal...

This supplementary Technical Appendix contains formal proofs of the propositions which are stated in Anyfantaki, S., S. Arvanitis, S., Th. Post, Th. and N. Topaloglou, 2019, 'Stochastic Bounds for Portfolio Analysis', available at SSRN:"https://ssrn.com/abstract=3181869 "...

Dynamic programming is the essential tool in dynamic economic analysis. Problems such as portfolio allocation for individuals and optimal economic growth are typical examples. Numerical methods typically approximate the value function. Recent work has focused on making numerical methods more...

Since the publication of “Portfolio selection” by H. M. Markowitz in the Journal of Finance in 1952, investment portfolios have been optimized using assumptions on utility and risk trade-offs. We prove that when regular intra-period portfolio rebalancing strategies are applied, the...