Managing value-at-risk for a bond using bond put options

This paper studies a strategy that minimizes the Value-at-Risk (VaR) of a position in a zero-coupon bond by buying a percentage of a put option, subject to a fixed budget available for hedging. We elaborate a formula for determining the optimal strike price for this put option in case of a Vasicek stochastic interest rate model. We demonstrate the relevance of searching the optimal strike price, since moving away from the optimum implies a loss, either due to an increased VaR or due to an increased hedging expenditure. In this way, we extend the results of [Ahn, Boudoukh, Richardson, and Whitelaw (1999). Journal of Finance, 54, 359–375] who minimize VaR for a position in a share. In addition, we look at the alternative risk measure Tail Value-at-Risk.     

Error bounds in the averaging of hybrid systems

The authors analyze the error introduced by the averaging of hybrid systems. These systems involve linear systems which can take a number of different realizations based on the state of an underlying finite state process. The averaging technique (based on a formula from Lie algebras known as the Backer-Campbell-Hausdorff (BCH) formula) provides a single system matrix as an approximation to the hybrid system. The two errors discussed are: (1) the error induced by the truncation of the BCH series expansion and (2) the error between the actual hybrid system and its average. A simple sufficient stability test is proposed to check the asymptotic behavior of this error. In addition, conditions are derived that allow the use of state feedback instead of averaging to arrive at a time-invariant system matrix     

Experimental studies on bubble pump operated diffusion absorption machine based on light hydrocarbons for solar cooling

An experimental investigation of an air-cooled diffusion absorption machine operating with a binary light hydrocarbon mixture (C₄H₁₀/C₉H₂₀) as working fluids and helium as pressure equalizing inert gas is presented in this paper. The machine, made of copper an available and very good heat conducting metal, is intended to be solar powered heat from flat plate or common evacuated tube collectors. The cooling capacity is 40–47 W respectively for 9 and 11°C chilled water temperature. Cold is produced at temperatures between −10 and +10 °C for a driving temperature in the range of 120–150 °C.     

Essential Oil and Phenolic Compounds of Artemisia herba-alba (Asso.): Composition,Antioxidant, Antiacetylcholinesterase,and Antibacterial Activities

Total phenols, flavonoids, flavonols, and flavanols of the methanolic extract of the aerial part of Artemisia herba-alba were determined. The extract was analyzed by liquid chromatography with photodiode array coupled with electrospray ionisation mass spectrometry and allowed to identify of 10 phenolic compounds. Apigenin-6-C-glycosyl flavonoids and caffeoylquinic acids were identified. Chlorogenic acid and 1,4 dicaffeoylquinic acid being the major constituents. The essential oil obtained by hydrodistillation was analyzed by gas chromatography–mass spectrometry. Twenty-three compounds, representing 97.8% of the total oil, were identified. The most abundant components were β-thujone (41.9%), α-thujone (18.4%), and camphor (13.2%). Methanolic extract and essential oil exhibited a considerable antioxidant activity as evaluated by 2,2-diphenyl-pycrilhydrazil hydrate scavenging activity, reducing power, β-carotene bleaching test, and chelating ability. The methanolic extract was found to be more efficient, while the essential oil exhibited the highest acetylcholinesterase inhibitory activity. Analysis of the antibacterial activity showed that A. herba-alba methanolic extract and essential oil are efficient against gram positive and gram negative bacteria.     

A numerical investigation of a diffusion-absorption refrigeration cycle based on R124-DMAC mixture for solar cooling

Research on new working fluid for uses in absorption systems has been continued. The feasibility of a solar driven DAR using the mixture R124/DMAC as working fluid is investigated by numerical simulation. The cycle is simulated for two cooling medium temperatures, 27 °C and 35 °C, and four driving heat temperatures in the range [90 °C–180 °C]. The performance characteristics of this system is analyzed parametrically by computer simulation for a design cooling capacity of 1 kW. The results show that the system performance and the lowest (minimum) evaporation temperature reached are largely dependent upon the absorber efficiency and the driving temperature. It is shown that for solar applications this fluid mixture has a higher COP and may constitute an alternative to the conventional ammonia–water system.     

Modélisation des données thermodynamiques du mélange ammoniac/eauModelling of the thermodnyamic properties of the ammonia/water mixture

The present work deals with the modeling of the thermodynamic properties of the ammonia/water mixture using the Gibbs free energy function. For the liquid phase, a three constant Margules model of the excess free enthalpy is formulated. The vapour phase is considered as a perfect mixture of real gases, each pure gas being described by a virial equation state in pressure truncated after the third term. The model developed describes with a good accuracy the mixture in the three states, subcooled liquid, superheated vapour and liquid-vapour saturation for temperatures from 200 to 500 K and pressures up to 100 bar.     

Design optimization of an artificial lateral line system incorporating flow and sensor uncertainties

An artificial lateral line (ALL) system consists of a set of flow sensors around a fish-like body. An ALL system aims to identify surrounding moving objects, a common example of which is a vibrating sphere, called a dipole. Accurate identification of a vibrating dipole is a challenging task because of the presence of different types of uncertainty in measurements or in the underlying flow model. Proper selection of design parameters of the ALL system, including the shape, size, number and location of the sensors, can highly influence the identification accuracy. This study aims to find such an optimum design by developing a specialized bi-level optimization methodology. It identifies and simulates different sources of uncertainty in the problem formulation. A parametric fitness function addresses computational and practical goals and encompasses the effect of different sources of uncertainty. It can also analyse the trade-off between localization accuracy and the number of sensors. Comparison of the results for different extents of uncertainty reveals that the optimized design strongly depends on the amount of uncertainty as well as the number of sensors. Consequently, these factors must be considered in the design of an ALL system. Another highlight of the proposed bi-level optimization methodology is that it is generic and can be readily extended to solve other noisy and nested optimization problems.