Pulled-to-par returns for zero coupon bonds : historical simulation value at risk

Due to bond prices pull-to-par, zero coupon bonds historical returns are not stationary, as they tend to zero as time to maturity approaches. Given that the historical simulation method for computing Value at Risk (VaR) requires a stationary sequence of historical returns, zero coupon bonds historical returns can not be used to compute VaR by historical simulation. Their use would systematically overestimate VaR, resulting in invalid VaR sequences. In this paper we propose an adjustment of zero coupon bonds historical returns. We call the adjusted returns “pulled-to- par" returns. We prove that when the zero coupon bonds continuously compounded yields to maturity are stationary the adjusted pulled-to-par returns allow VaR computation by historical simulation. We first illustrate the VaR computation in a simulation scenario, then we apply it to real data on euro zone STRIPS.info:eu-repo/semantics/publishedVersio

El uso de fluidos supercríticos en la industria de aceites alimentarios

Residual olive oil extraction experiments were made with carbon dioxide under pressures of 12 and 15 MPa and 308.15, 313.15 and 318.15 K of temperature. We may conclude through the experiments, that under these pressures and temperature of 313.15 K there is no selected extraction of fatty acids, and higher recovery rates can be obtained in a short period of time.Se han realizado experiencias de extracción de aceite de orujo con dióxido de carbono a presiones de 12 y 15 MPa y a las temperaturas de 308.15, 313.15 y 318.15 K. Las pruebas efectuadas permiten concluir que en esta gama de presiones y a la temperatura de 313.15 K no existe extracción selectiva de los ácidos grasos y que se obtienen rendimientos elevados en relativamente poco tiempo

Identifying the Main Predictors of Length of Care in Social Care in Portugal

In this paper, we aim to identify the main predictors at admission and estimate patients' length of care (LOC), within the framework of the Portuguese National Network for Long-Term Integrated Care, considering two care settings: (1) home and community-based services (HCBS) and (2) nursing home (NH) units comprising Short, Medium, or Long Stay Care. This study relied on a database of 20,984 Portuguese individuals who were admitted to the official long-term care (LTC) system and discharged during 2015. A generalised linear model (GLM) with gamma distribution was adjusted to HCBS and NH populations. Two sets of explanatory variables were used to model the random variable, LOC, namely, patient characteristics (age, gender, family/neighbour support, dependency levels at admission for locomotion, cognitive status, and activities of daily living [ADL]) and external factors (referral entity, number of beds/treatment places per 1,000 inhabitants ≥65 years of age), maturity and occupancy rate of the institution, and care setting. The features found to most influence the reduction of LOC are: male gender, having family/neighbour support, being referred by hospitals to NH (or by primary care to HCBS), and being admitted to units with a lower occupancy rate and with fewer months in operation. Regarding the dependency levels, as the number of ADL considered "dependent"increases, LOC also increases. As for the cognitive status, despite the opposite trend, it was only statistically significant for NH. Furthermore, two additional models were applied by including "death,"although this feature is not observable upon admission. By creating a model that allows for an estimate of the expected LOC for a new individual entering the Portuguese LTC system, policy-makers are able to estimate future costs and optimise resources

Isoenzymatic variability in population of the genus Plagiochila in Portugal and Madeira

info:eu-repo/semantics/publishedVersio