Operations Research
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Operations Research2015-08-30Walter FrischStochastic intrinsic kriging for simulation metamodelling
http://d.repec.org/n?u=RePEc:tiu:tiucen:00bed9cb-d34c-4e98-93ef-e805fce63fa0&r=all
Kriging provides metamodels for deterministic and random simulation models. Actually, there are several types of Kriging; the classic type is so-called universal Kriging, which includes ordinary Kriging. These classic types require estimation of the trend in the input-output data of the underlying simulation model; this estimation deteriorates the Kriging metamodel. We therefore consider so-called intrinsic Kriging originating in geostatistics, and derive intrinsic Kriging for deterministic and random simulations. Moreover, for random simulations we derive experimental designs that specify the number of replications that varies with the input combination of the simulation model. To compare the performance<br/>of intrinsic Kriging and classic Kriging, we use several numerical experiments with deterministic simulations and random simulations. These experiments show that intrinsic Kriging gives better metamodels, in most experiments.Mehdad, Ehsan, Kleijnen, J.P.C.2015simulation; gaussian process; Kriging; intrinsic random functions; metamodelInstitutional Dynamics Under Revenue Volatility and Revenue-Dependent Lobbying Power: A Stochastic Differential Game Approach
http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-01181214&r=all
We propose an analysis of institutional dynamics under uncertainty by the means of a stochastic differential lobbying game with two main ingredients. The first one is uncertainty inherent in the institutional process itself. The second one has to do with the crucial role of resource windfalls in economic and political outcomes, shaping lobbying power and adding a second source of uncertainty. First, we focus on uncertainty surrounding the institutional process only and show that its main consequence is the existence of multiple equilibria with very distinct features: symmetric equilibria which lead the economy to reach almost surely a stable pointwise institutional steady state in the long run even in the absence of the retaliation motive put forward by the deterministic lobbying literature, and asymmetric equilibria which only show up under uncertainty and do no allow for stochastic convergence to a steady state. Second, when accounting for the two sources of uncertainty together with resource revenue-dependent lobbying power, we show that revenue volatility tends to stabilize institutional dynamics compared to the deterministic counterpart.Raouf Boucekkine, Fabien Prieur, Benteng Zou2015-07Efficient Global Optimization for Black-Box Simulation via Sequential Intrinsic Kriging
http://d.repec.org/n?u=RePEc:tiu:tiucen:5e785713-146c-4e5b-b671-f7eb4a8b7a41&r=all
Efficient Global Optimization (EGO) is a popular method that searches sequentially for the global optimum of a simulated system. EGO treats the simulation model as a black-box, and balances local and global searches. In deterministic simulation, EGO uses ordinary Kriging (OK), which is a special case of universal Kriging (UK). In our EGO variant we use intrinsic Kriging (IK), which eliminates the need to estimate the parameters that quantify the trend in UK. In random simulation, EGO uses stochastic Kriging (SK), but we use stochastic IK (SIK). Moreover, in random simulation, EGO needs to select the number of replications per simulated input combination, accounting for the heteroscedastic variances of the simulation outputs. A popular selection method uses optimal computer budget allocation (OCBA), which allocates the available total number of replications over simulated combinations. We derive a new allocation algorithm. We perform several numerical experiments with deterministic simulations and random simulations. These experiments suggest that (1) in deterministic simulations, EGO with IK outperforms classic EGO; (2) in random simulations, EGO with SIK and our allocation rule does not differ significantly from EGO with SK combined with the OCBA allocation rule.Mehdad, Ehsan, Kleijnen, J.P.C.2015global optimization; Gaussian process; Kriging; intrinsic Krgigin; metamodelRisk Spillovers across the Energy and Carbon Markets and Hedging Strategies for Carbon Risk
http://d.repec.org/n?u=RePEc:emu:wpaper:15-10.pdf&r=all
This study examines the risk spillovers between energy futures prices and Europe-based carbon futures contracts. We use a Markov regime-switching dynamic correlation, generalized autoregressive conditional heteroscedasticity (MSDCC- GARCH) model in order to capture the time variations and structural breaks in the spillovers. We further evaluate the optimal weights, hedging effectiveness, and dynamic hedging strategies for the MS-DCC-GARCH model based on both the regime dependent and regime independent optimal hedge ratios. We finally complement our analysis by examining the in- and out-of sample hedging performances for alternative strategies. Our results mainly show significant volatility and time-varying risk transmission from energy markets to carbon market. We also find that spot and futures segments of the emission markets exhibit time-varying correlations and volatile hedging effectiveness. These results have important investment and policy implicationsMehmet Balcilar, Riza Demirer, Shawkat Hammoudeh, Duc Khuong Nguyen2014Multivariate regime-switching; time-varying correlations; hedging; CO2 allowance pricesA novel initialization of PSO for costly portfolio selection problems
http://d.repec.org/n?u=RePEc:vnm:wpdman:105&r=all
In this paper we propose an efficient initialization of a deterministic Particle Swarm Optimization (PSO) scheme. PSO has showed to be promising for solving several unconstrained global optimization problems from real applications, where derivatives are unavailable and the evaluation of the objective function tends to be costly. Here we provide a theoretical framework which motivates the use of a deterministic version of PSO, in place of the standard stochastic iteration currently adopted in the literature. Then, in order to test our proposal, we include a numerical experience using a realistic complex portfolio selection problem. This numerical experience includes the application of PSO to a parameter dependent unconstrained reformulation of the considered portfolio selection problem. The parameters are either adaptively updated as in an exact penalty framework, or they are tuned by the code REVAC. We show that in both these settings our PSO initialization is preferable with respect to the standard proposal from the literature.Marco Corazza, Giacomo Di Tollo, Giovanni Fasano, Raffaele Pesenti2015-07Deterministic PSO, Global Optimization, Portfolio Selection Problems, Exact Penalty functions.Mean-risk hedging strategies in electricity markets with limited liquidity
http://d.repec.org/n?u=RePEc:zbw:zewdip:15056&r=all
This article investigates mean risk hedging with respect to limited liquidity and studies the impact of different risk measures on the hedging strategies. For motivation and application purposes hedging in electricity markets is chosen, because the relevant hedging markets are characterized by limited liquidity. We enhance the approach in Woll and Weber (2015) to a mean-risk optimization under limited liquidity, including the risk measures absolute and relative Value and Conditional Value at Risk (VaR and CVaR). It can be shown that for position independent measures (Variance, relative VaR, relative CVaR) liquidity has no influence on the minimum risk hedging strategies, whereas for position dependent measures (absolute VaR, absolute CVaR) liquidity has an impact on the minimum risk hedging strategies. The article gives the mathematical formulations of the problems and discusses the economic relevance of the different models. In addition, we apply the analyzed concepts to the German Electricity markets.Woll, Oliver2015optimization,electricity,liquidity,electricity trading,mean-risk-modelLie Symmetry Analysis of the Black-Scholes-Merton Model for European Options with Stochastic Volatility
http://d.repec.org/n?u=RePEc:arx:papers:1508.06797&r=all
We perform a classification of the Lie point symmetries for the Black-Scholes-Merton model for European options with stochastic volatility $% \sigma$, in which the last is defined by a stochastic differential equation with the Orstein-Uhlenbeck term. In this model the value of the option is given by a linear (1+2) evolution partial differential equation, in which the price of the option depends on two independent variables, the value of the underlying asset $S$ and a new variable, $y$, which follow from the Orstein-Uhlenbeck process. We find that for arbitrary functional form of the volatility, $\sigma(y)$, the (1+2) evolution equation admits always two Lie symmetries, plus the linear symmetry and the infinity number of solution symmetries. However when $\sigma(y)=\sigma_{0}$ and since the price of the option depends on the second Brownian motion in which the volatility is defined, the (1+2) evolution is not reduced to the Black-Scholes-Merton equation, the model admits five Lie symmetries, plus the linear symmetry and the infinity number of solution symmetries. Furthermore we apply the zero-order invariants of the Lie symmetries and we reduce the (1+2) evolution equation to a linear second-order ordinary differential equation. Finally we study two models of special interest, the Heston model and the Stein-Stein model.A. Paliathanasis, K. Krishnakumar, K. M. Tamizhmani, P. G. L. Leach2015-08New Entropy Restrictions and the Quest for Better Specified Asset Pricing Models
http://d.repec.org/n?u=RePEc:ecl:ohidic:2014-07&r=all
Under the setting that stochastic discount factors (SDFs) jointly price a vector of returns, this paper features entropy-based restrictions on SDFs, and its correlated multiplicative components, to evaluate asset pricing models. Specifically, our entropy bound on the square of the SDFs is intended to capture the time-variation in the conditional volatility of the log SDF as well as distributional non-normalities. Each entropy bound can be inferred from the mean and the variance-covariance matrix of the vector of asset returns. Extending extant treatments, we develop entropy codependence measures and our bounds generalize to multi-period SDFs. Our approach offer ways to improve model performance.Bakshi, Gurdip, Chabi-Yo, Fousseni2014-05Oil Price Forecasts for the Long-Term: Expert Outlooks, Models, or Both?
http://d.repec.org/n?u=RePEc:lvl:creacr:2015-3&r=all
Expert outlooks on the future path of oil prices are often relied on by industry participants and policymaking bodies for their forecasting needs. Yet little attention has been paid to the extent to which these area accurate. Using the regular publications by the Energy Information Administration (EIA), we examine the accuracy of annual recursive oil price forecasts generated by the National Energy Modeling System model of the Agency for forecast horizons of up to 15 years. Our results reveal that the EIA model is quite successful at beating the benchmark random walk model, but only at either end of the forecast horizons. We also show that, for the longer horizons, simple econometric forecasting models often produce similar if not better accuracy than the EIA model. Among these, time-varying specifications generally also exhibit stability in their forecast performance. Finally, while combining forecasts does not change the overall patterns, some additional accuracy gains are obtained at intermediate horizons, and in some cases forecast performance stability is also achieved.Jean-Thomas Bernard, Lynda Khalaf, Maral Kichian, Clement Yelou2015Oil price, expert outlooks, long run forecasting, forecast combinationsSuper-replication of Game Options in Stochastic Volatility Models
http://d.repec.org/n?u=RePEc:arx:papers:1508.05233&r=all
We study the problem of super-replication of game options in general stochastic volatility models which include e.g. the Heston model, the Hull-White model and the Scott model. For simplicity, we consider models with one risky asset. We show that the super-replication price is the cheapest cost of a trivial super-replication strategy. Furthermore, we calculate explicitly the super-replication price and the corresponding optimal hedge. The super-replication price can be seen as the game variant of a concave envelope. Our approach is purely probabilistic.Yan Dolinsky, Ariel Neufeld2015-08