In this paper, a method based on Non-Dominated Sorting Genetic Algorithm (NSGA) has been presented for the Volt / Var control in power distribution systems with dispersed generation (DG). Genetic algorithm approach is used due to its broad applicability, ease of use and high accuracy. The proposed method is better suited for volt/var control problems. A multi-objective optimization problem has ...

A new approach to optimizing or hedging a portfolio of nancial instruments to reduce risk is presented and tested on applications. It focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value-at-Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well. CVaR, also called Mean Excess Loss, Mean Shortfall, or Tail VaR, is anyway considered to be a more co...

This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR) forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et a...

This paper presents a method for allocation and evaluation of reactive power (VAr) support contracts necessary to maintain system security and quality of supply. The method also quantifies the value of VAr support from individual generators or a portfolio of generators. Such information may be useful both to generating companies in preparing VAr tenders and to the market operator in assessing t...

Various species of common box (Buxus) are cultivated in the Arboretum of the Slovak Academy of Sciences in Mlyňany under the same soil and climatic conditions; consequently, the examination of alkaloids produced by those plants is of chemotaxonomical importance. From this locality we investigated so far alkaloids from Buxus sempervirens L.[l,2], B. microphylla SIEB, et ZUCC. var. sinica REHD. e...

We compare the performance of a subset of CBO’s economic forecasts against that of an unrestricted vector autoregression (VAR) model. We evaluate forecasts of real economic indicators as well as budget-related nominal statistics. We find that under most specifications, the VAR performs competitively with, if slightly worse than, the corresponding CBO forecasts at up to 20 quarters. Therefore, a...

This paper investigates optimal portfolio and wealth strategy of an institutional investor under the Value-at-Risk (VaR) constraint in an economy under jump diffusion. We show that overlooking or underestimating jump risk factor could be the cause of failure to satisfy the VaR constraint in the recent financial crisis for many financial institutions. We also find that the introduction of the ju...

We formulate a four-dimensional Ensemble Kalman Filter (4D-LETKF) that minimizes a cost function similar to that in a 4D-VAR method. Using perfect model experiments with the Lorenz-96 model, we compare assimilation of simulated asynchronous observations with 4D-VAR and 4D-LETKF. We find that both schemes have comparable error when 4D-LETKF is performed sufficiently frequently and when 4D-VAR is...

Practical use of the contamination technique in stress testing for risk measures Value at Risk (VaR) and Conditional Value at Risk (CVaR) and for optimization problems with these risk criteria is discussed. Whereas for CVaR its application is straightforward, the presence of the simple chance constraint in the definition of VaR requires that various distributional and structural properties are ...

Let X1, . . . , Xn and Y1, . . . , Yn be two independent sequences of i.i.d Bernoulli variables with parameter > 0. Let X designate the string X := X1X2 . . . Xn and let Y := Y1Y2 . . . Yn. Let Ln designate the length of the longest common subsequence (LCS) of X and Y . We prove that for a constant c > 0, VAR[Ln] > cn if > 0 is taken small enough. Hence for small , the order of magnitude of VAR...