961,222 research outputs found
Enhanced indexation based on second-order stochastic dominance
Second order Stochastic Dominance (SSD) has a well recognised importance in portfolio selection, since it provides a natural interpretation of the theory of risk-Averse investor behaviour. Recently, SSD-based models of portfolio choice have been proposed; these assume that a reference distribution is available and a portfolio is constructed, whose return distribution dominates the reference distribution with respect to SSD. We present an empirical study which analyses the effectiveness of such strategies in the context of enhanced indexation. Several datasets, drawn from FTSE 100, SP 500 and Nikkei 225 are investigated through portfolio rebalancing and backtesting. Three main conclusions are drawn. First, the portfolios chosen by the SSD based models consistently outperformed the indices and the traditional index trackers. Secondly, the SSD based models do not require imposition of cardinality constraints since naturally a small number of stocks are selected. Thus, they do not present the computational difficulty normally associated with index tracking models. Finally, the SSD based models are robust with respect to small changes in the scenario set and little or no rebalancing is necessary. In this paper we present a unified framework which incorporates (a) SSD, (b) downside risk (Conditional Value-At-Risk) minimisation and (c) enhanced indexation. © 2013 Elsevier B.V. All rights reserved
Some experiments on solving multistage stochastic mixed 0-1 programs with time stochastic dominance constraints
In this work we extend to the multistage case two recent risk averse measures for two-stage stochastic
programs based on first- and second-order stochastic dominance constraints induced by mixed-integer linear
recourse. Additionally, we consider Time Stochastic Dominance (TSD) along a given horizon.
Given the dimensions of medium-sized problems augmented by the new variables and constraints required
by those risk measures, it is unrealistic to solve the problem up to optimality by plain use of MIP solvers
in a reasonable computing time, at least. Instead of it, decomposition algorithms of some type should be
used. We present an extension of our Branch-and-Fix Coordination algorithm, so named BFC-TSD, where
a special treatment is given to cross scenario group constraints that link variables from different scenario
groups. A broad computational experience is presented by comparing the risk neutral approach and the
tested risk averse strategies. The performance of the new version of the BFC algorithm versus the plain
use of a state-of-the-artMIP solver is also reported
First-Order Pontryagin Maximum Principle for Risk-Averse Stochastic Optimal Control Problems
In this paper, we derive a set of first-order Pontryagin optimality
conditions for a risk-averse stochastic optimal control problem subject to
final time inequality constraints, and whose cost is a general finite coherent
risk measure. Unlike previous contributions in the literature, our analysis
holds for classical stochastic differential equations driven by standard
Brownian motions. Moreover, it presents the advantages of neither involving
second-order adjoint equations, nor leading to the so-called weak version of
the PMP, in which the maximization condition with respect to the control
variable is replaced by the stationarity of the Hamiltonian
Wasserstein Distributionally Robust Look-Ahead Economic Dispatch
We consider the problem of look-ahead economic dispatch (LAED) with uncertain
renewable energy generation. The goal of this problem is to minimize the cost
of conventional energy generation subject to uncertain operational constraints.
The risk of violating these constraints must be below a given threshold for a
family of probability distributions with characteristics similar to observed
past data or predictions. We present two data-driven approaches based on two
novel mathematical reformulations of this distributionally robust decision
problem. The first one is a tractable convex program in which the uncertain
constraints are defined via the distributionally robust
conditional-value-at-risk. The second one is a scalable robust optimization
program that yields an approximate distributionally robust chance-constrained
LAED. Numerical experiments on the IEEE 39-bus system with real solar
production data and forecasts illustrate the effectiveness of these approaches.
We discuss how system operators should tune these techniques in order to seek
the desired robustness-performance trade-off and we compare their computational
scalability
Pension Funds under Investments Constraints: An Assessment of the Opportunity Cost to the Greek Social Security System
In this paper we study the opportunity loss of the Greek social security system in terms of risk and return, caused by the inflexible investment constraints under which Greek pension funds operated in the period 1958-2000. Using data on pension fund reserves as well as on money and capital market yields, we evaluate retrospectively the risks and returns of a more pro-investment fund reserve management by analyzing an indicative number of investment scenarios in local and international money and capital markets. In order to estimate local currency yields for international investment, we generate for the entire period – covering both a fixed and a partially floating exchange rates regime – a corresponding series of exchange rate variations based on the official rate fluctuations and inflation differentials. Our results suggest that in the 43-year period, there has been a significant opportunity loss in the system both in risk and returns: first, by excluding Greek bank deposits and Greek capital market securities that would have propped returns up at acceptable levels of risk and, second, by not allowing for some degree of international diversification that would have kept overall downside risk down. This opportunity loss could have alleviated, to some extent, the current imbalance of the system, had some of the restrictive investment rules been relaxed.pension funds; financial investment
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