Estimating long-term volatility parameters for market-consistent models

Contemporary actuarial and accounting practices (APN 110 in the South African context) require the use of market-consistent models for the valuation of embedded investment derivatives. These models have to be calibrated with accurate and up-to-date market data. Arguably, the most important variable in the valuation of embedded equity derivatives is implied volatility. However, accurate long-term volatility estimation is difficult because of a general lack of tradable, liquid medium- and long-term derivative instruments, be they exchange-traded or over the counter. In South Africa, given the relatively short-term nature of the local derivatives market, this is of particular concern. This paper attempts to address this concern by: — providing a comprehensive, critical evaluation of the long-term volatility models most commonly used in practice, encompassing simple historical volatility estimation and econometric, deterministic and stochastic volatility models; and — introducing several fairly recent nonparametric alternative methods for estimating long-term volatility, namely break-even volatility and canonical option valuation. The authors apply these various models and methodologies to South African market data, thus providing practical, long-term volatility estimates under each modelling framework whilst accounting for real-world difficulties and constraints. In so doing, they identify those models and methodologies they consider to be most suited to long-term volatility estimation and propose best estimation practices within each identified area. Thus, while application is restricted to the South African market, the general discussion, as well as the suggestion of best practice, in each of the evaluated modelling areas remains relevant for all long-term volatility estimation

A dual process account of creative thinking

This article explicates the potential role played by type 1 thinking (automatic, fast) and type 2 thinking (effortful, logical) in creative thinking. The relevance of Evans's (2007) models of conflict of dual processes in thinking is discussed with regards to creative thinking. The role played by type 1 thinking and type 2 thinking during the different stages of creativity (problem finding and conceptualization, incubation, illumination, verification and dissemination) is discussed. It is proposed that although both types of thinking are active in creativity, the extent to which they are active and the nature of their contribution to creativity will vary between stages of the creative process. Directions for future research to test this proposal are outlined; differing methodologies and the investigation of different stages of creative thinking are discussed. © Taylor & Francis Group, LLC

Unterstützung kommunalplanerischer Prozesse mit CityGLM-basierter Anbindung Modelica-getriebener Quartierssimulationen

Eine integrale Planung städtischer (Energie-)Systeme bedarf einer planungsbegleitenden Unterstützung durch IT-basierte Planungs- und Simulationswerkzeuge. Die durchgängige Anwendung dieser digitalen Planungshilfsmittel wird allerdings bislang insbesondere durch den sehr hohen Aufwand bei der Spezifizierung und Erfassung benötigter Datengrundlagen sowie eine mangelhafte Interoperabilität zwischen den Systemen gehemmt. Im Rahmen eines Forschungsverbundprojektes wird dieses Problemfeld mittels praxisbezogener Prozessanalysen genauer spezifiziert und die technische und fachliche Integration durch die prozessbezogene Spezifikation relevanter Informationsbedarfe sowie die Entwicklung einer darauf aufbauenden, bidirektionalen Schnittstelle auf Basis des etablierten virtuellen Stadtmodellstandards CityGML verbessert. Als exemplarisches Anwendungsszenario innerhalb kommunaler Planungsprozesse wurde die Ausweisung von Vorranggebieten der Fernwärmenutzung basierend auf einer räumlichen Analyse des Wärmebedarfs für verschiedene Entwicklungsszenarien mittels einer bidirektionalen standard-basierten Koppelung von CityGML und Modelica ausgearbeitet

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared to 26.2% for the na\"ive persistence predictor. Note that in the stand alone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposedComment: Energy (2012)

Introduction

Introduction to the volume English in International Deaf Communicatio