Measuring and Modeling Risk Using High-Frequency Data

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns. In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures of systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorporation and of the DJIA index

A regional end use energy demand model

This paper describes a long-term energy demand forecasting model for Northern Ireland. The model is of the 'what-if' type for testing possible futures described by the model user and is based on a detailed activity analysis approach. The demand subsystem of the Northern Ireland energy system is divided into seven sectors and the demand for four end use categories for fuels considered. The structure of each of the seven sectors is modelled and future fuel demands calculated based on the driving functions of population and social and economic activity. For a given input scenario the model calculates the dockside oil equivalent primary fuel in tonnes for each year for 30 years.

The p-median problem and health facilities: Cost saving and improvement in healthcare delivery through facility location

The importance of health to economic growth and development is an undisputed fact. Modern advancement in technology and healthcare has contributed to improved health and productivity, but there are many people who cannot access healthcare in a timely fashion. Factors affecting delays in accessing healthcare include inadequate supply, poor location, or lack of healthcare facilities all of which can be exacerbated by increasing healthcare costs and scarcity of resources. In this study, we develop a simple two-stage method based on the p-median problem to investigate the location and access to healthcare (emergency) facilities in urban areas. We compare the results of our new method with the results of similar existing methods using 26-node, 42-node, and 55-node data. We also show the efficiency of our method with exact methods using 150-node random data. Our method compares favorably with optimal and the existing methods

Forming social impressions from voices in native and foreign languages

We form very rapid personality impressions about speakers on hearing a single word. This implies that the acoustical properties of the voice (e.g., pitch) are very powerful cues when forming social impressions. Here, we aimed to explore how personality impressions for brief social utterances transfer across languages and whether acoustical properties play a similar role in driving personality impressions. Additionally, we examined whether evaluations are similar in the native and a foreign language of the listener. In two experiments we asked Spanish listeners to evaluate personality traits from different instances of the Spanish word “Hola” (Experiment 1) and the English word “Hello” (Experiment 2), native and foreign language respectively. The results revealed that listeners across languages form very similar personality impressions irrespective of whether the voices belong to the native or the foreign language of the listener. A social voice space was summarized by two main personality traits, one emphasizing valence (e.g., trust) and the other strength (e.g., dominance). Conversely, the acoustical properties that listeners pay attention to when judging other’s personality vary across languages. These results provide evidence that social voice perception contains certain elements invariant across cultures/languages, while others are modulated by the cultural/linguistic background of the listener.This study was funded by the Agencia Estatal de Investigación (AEI, National Research Agency) and Fondo Europeo de Desarrollo Regional (FEDER, European Regional Development Fund) under projects PSI2017- 84539-P and PSI2014-52181-P, the Catalan Government (2017 SGR 268), and the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613465 - AThEME. CB was supported by the People Program (Marie Curie Actions, FP7-PEOPLE 2014–2016) under REA agreement n°623845 and now is supported by the Beatriu de Pinòs program (AGAUR, BP00381). PB was supported by supported by grant AJE201214 from French Foundation for Medical Research, and grants ANR-16-CONV-0002 (Institute of Language, Communication and the Brain), ANR-11-LABX-0036 (Brain and Language Research Institute) and the Excellence Initiative of Aix-Marseille University (A*MIDEX)