Real-life decisions are usually made in the state of uncertainty or risk. In this article we present the risk measuring techniques value at risk (VaR) and tail value at risk (TVaR) under uncertainty. Firstly, we introduce the VaR concept of uncertain variable based on uncertainty theory and examine its fundamental properties. Then, the TVaR concept is evolved and some fundamental properties of ...

This article analyzes optimal, dynamic portfolio and wealth/consumption policies of utility maximizing investors who must also manage market-risk exposure using Value-atRisk (VaR). We find that VaR risk managers often optimally choose a larger exposure to risky assets than non-risk managers and consequently incur larger losses when losses occur. We suggest an alternative risk-management model, ...

In this seminar we show clean comparisons between EnKF and 4D-Var made in Environment Canada, briefly describe the Local Ensemble Transform Kalman Filter (LETKF) as a representative prototype of Ensemble Kalman Filter, and give several examples of how advanced properties and applications that have been developed and explored for 4D-Var can be adapted to the LETKF without requiring an adjoint mo...

Multivariate time-series modeling and forecasting constitutes an important problem with numerous applications. In this work, we consider multivariate continuous time series modeling from aviation, where the data consists of multiple sensor measurements from real world flights. While traditional approaches such as VAR (vector auto-regressive) models have been widely used for aviation time series...

It is well known that many countries around the world depend on the US as their major trade partner. As a result, if something does happen to US economy it surely will affect the economy of all these countries. In this study, we investigate the relationship between the US and four Asian emerging stock markets namely Hong Kong, India, South Korea and Malaysia using monthly data between 1996 and ...

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...