The effect of asymmetries on stock index return value-at-risk estimates

It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models

Stress factors and stress management interventions: the heuristic of “bottom up” an update from a systematic review

Organizations have increasingly sought to adopt innovative interventions to prevent stress-related issues. In the field of manufacturing, however, the effectiveness of these interventions remains unclear because a systematic and specific review of existing primary evidence has not been undertaken. The present systematic literature review sought to address the foregoing limitation in the literature by summarizing the main source of stress and effectiveness of stress management interventions as grounded in the context of manufacturing. Our review was limited to only randomized clinical trials (RCTs) and quasi-experimental studies and concerned employees from the manufacturing sector. Twenty-two studies on primary, secondary and tertiary interventions across four continents (Asia, Europe, USA and South America) were selected and analyzed in terms of stress factors, methodological properties and outcomes. Most of these were RCT studies (68% Vs 32%) with a majority of secondary interventions (N = 11, 50%), followed by primary (N = 5, 22%), tertiary (N = 3, 13%), and two (9%) mixed interventions. The main outcomes included an improvement of psychological wellbeing, decreased stress reactivity and an increment of general health. There was a predominance of interventions utilizing skills programs and/or cognitive-behavioral techniques. The main source of stress reported related to professional identity, organizational deficiencies, interpersonal conflicts, physical complaints and poor work environment. Taken together, the findings provide important theoretical and practical implications for advancing the study of stress factors and the use of stress management interventions in the workplace. The prerequisite for a successful intervention is to address the real problems experienced by professionals and help them to cope with their difficult situations. The strategy of “bottom-up” offers a potential means of enhancing employees’ health and well-being; however, the most effective means of implementing these interventions needs to be understood better

Thyristor-Controlled Switch Capacitor Placement in Large-Scale Power Systems via Mixed Integer Linear Programming and Taylor Series Expansion

Allocation of flexible alternating current transmission system (FACTS) devices to an electric power transmission network may be formulated as a nonlinear mathematical program. Solving such a nonlinear program for a large transmission network is computationally very expensive, and obtaining the optimal solution may be impossible. We present a Taylor series expansion approximation of the nonlinearities of the problem and propose a mixed integer linear program (MILP) for finding the optimum location and proper settings of a Thyristor-Controlled Series Capacitor (TCSC) in an electric power network. The objective of this problem is to minimize total generation cost based on the DC load flow model. The proposed method is implemented for the 118-bus IEEE test case and the results are discussed

A Quantile-Based Approach for Transmission Expansion Planning

Transmission expansion planning is an integral part of power system planning and consists of generating and selecting transmission proposals for maintaining sufficient transmission capacity to satisfy the electric load. Specifically, the desire to increase the use of renewable energy has exposed the limitations of transmission networks and has elevated the importance of transmission expansion planning. However, considering the random nature of renewable sources in conjunction with the power outages makes the planning process very challenging. We present a new procedure for selecting the best transmission enhancement proposal from a set of finite proposals under uncertainty. The selection is based on the quantile value of the cost of each proposal. The procedure uses a combination of simulation and optimization and considers randomness of uncertain parameters of the network. Wind energy and network contingencies are among the considered random parameters. The procedure is suitable for evaluating investor-initiated enhancement proposals by the planner and statistically guarantees satisfaction of the planner’s prespecified probability of correct selection since simulation is involved. Two IEEE test networks are used for demonstrating the implementation of the new procedure. For these two test networks, solutions obtained using quantiles are compared with those when the expected value or a weighted combination of the expected value and the conditional-value-at-risk are used as selection criteria. The comparison shows that similar to the use of conditional-value-at-risk, the selection is sensitive to the choice of the quantile

Optimal Energy Scheduling for a Smart Entity

Real-time availability of electricity prices via a smart power grid has a potential bilateral benefit to electricity users and suppliers. The users can reduce their costs by consuming energy during low-price hours and balancing their energy usage during other hours. This in turn benefits energy utility companies by reducing their peak power demand. This article describes an optimal shrinking horizon model for electricity-consuming units based on user preferences. The proposed model optimizes the end user’s electricity cost while meeting preferred comfort levels. The user can set preferences in the model using a tristate flexibility parameter for each electric-power-consuming unit. The electricity price model used in the optimization model is general and covers all pricing schemes in the electricity market today. The model derived can be described by a simple mixed integer linear program and solved by most optimization software in a short time. The most distinguishing characteristics of our proposed model are its simplicity, generality, comprehensibility, and ease of implementation. Simulation results are used to verify the model’s performance in reducing consumer electricity costs and satisfying comfort preferences

Health effects of occupational exposure to static magnetic field in a chloralkali plant

A cross-sectional study was conducted to determine if long-term exposure to static magnetic fields could be related to findings of medical examination. Health data was obtained for 20 workers who spent a major period of their working time in the magnetic field produced by direct current through large electric cells. The data was compared to that of control group of 21 workers. Intensity of magnetic flux density was measured in the Chloralkali plant and the TWA exposure to magnetic field was determined for each job classification. Maximum and minimum intensities were found to be 16.99 and 0.49 mT, respectively, which were well below the recommended level. Maximum TWA exposure to magnetic field was equal to 47.59 mT that was less than the acceptable level. The results of clinical examinations and blood tests revealed that there was no significant difference between the two groups. The only effects which were found to be related to exposure to the magnetic field were nervousness and fatigue. Studying a larger sample size may contribute to detect any health effects of occupational exposure to static magnetic field in industrial settings

The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty

A material requirements planning simulator with a two-level bill-of-material is used to study the impact of introducing component commonality into an assemble-to-order environment when demand is subject to random variations, and component procurement orders experience random delays. By using simulated data, our ANOVA results show that component commonality significantly interacts with existence of demand and supply chain uncertainties, and benefits of component commonality are most pronounced when both uncertainties exist.Component commonality Lead-time uncertainty Demand uncertainty Assemble-to-order environment

A quantile-based approach to system selection

We propose a quantile-based ranking and selection (R&S) procedure for comparing a finite set of stochastic systems via simulation. Our R&S procedure uses a quantile set of the simulated probability distribution of a performance characteristic of interest that best represents the most appropriate selection criterion as the basis for comparison. Since this quantile set may represent either the downside risk, upside risk, or central tendency of the performance characteristic, the proposed approach is more flexible than the traditional mean-based approach to R&S. We first present a procedure that selects the best system from among K systems, and then we modified that procedure for the case where K - 1 systems are compared against a standard system. We present a set of experiments to highlight the flexibility of the proposed procedures.Simulation Ranking and selection Risk Quantile