Capturing UK real estate volitility

Volatility, or the variability of the underlying asset, is one of the key fundamental components of property derivative pricing and in the application of real option models in development analysis. There has been relatively little work on volatility in real terms of its application to property derivatives and the real options analysis. Most research on volatility stems from investment performance (Nathakumaran & Newell (1995), Brown & Matysiak 2000, Booth & Matysiak 2001). Historic standard deviation is often used as a proxy for volatility and there has been a reliance on indices, which are subject to valuation smoothing effects. Transaction prices are considered to be more volatile than the traditional standard deviations of appraisal based indices. This could lead, arguably, to inefficiencies and mis-pricing, particularly if it is also accepted that changes evolve randomly over time and where future volatility and not an ex-post measure is the key (Sing 1998). If history does not repeat, or provides an unreliable measure, then estimating model based (implied) volatility is an alternative approach (Patel & Sing 2000). This paper is the first of two that employ alternative approaches to calculating and capturing volatility in UK real estate for the purposes of applying the measure to derivative pricing and real option models. It draws on a uniquely constructed IPD/Gerald Eve transactions database, containing over 21,000 properties over the period 1983-2005. In this first paper the magnitude of historic amplification associated with asset returns by sector and geographic spread is looked at. In the subsequent paper the focus will be upon model based (implied) volatility

Capturing UK Real Estate Volitility

Volatility, or the variability of the underlying asset, is one of the key fundamental components of property derivative pricing and in the application of real option models in development analysis. There has been relatively little work on volatility in real terms of its application to property derivatives and the real options analysis. Most research on volatility stems from investment performance (Nathakumaran & Newell (1995), Brown & Matysiak 2000, Booth & Matysiak 2001). Historic standard deviation is often used as a proxy for volatility and there has been a reliance on indices, which are subject to valuation smoothing effects. Transaction prices are considered to be more volatile than the traditional standard deviations of appraisal based indices. This could lead, arguably, to inefficiencies and mis-pricing, particularly if it is also accepted that changes evolve randomly over time and where future volatility and not an ex-post measure is the key (Sing 1998). If history does not repeat, or provides an unreliable measure, then estimating model based (implied) volatility is an alternative approach (Patel & Sing 2000). This paper is the first of two that employ alternative approaches to calculating and capturing volatility in UK real estate for the purposes of applying the measure to derivative pricing and real option models. It draws on a uniquely constructed IPD/Gerald Eve transactions database, containing over 21,000 properties over the period 1983-2005. In this first paper the magnitude of historic amplification associated with asset returns by sector and geographic spread is looked at. In the subsequent paper the focus will be upon model based (implied) volatility.Real Estate, Volatility

Real Option Pricing in Mixed-use Development Projects

The application of real options theory to commercial real estate has developed rapidly during the last 15 Years. In particular, several pricing models have been applied to value real options embedded in development projects. In this study we use a case study of a mixed use development scheme and identify the major implied and explicit real options available to the developer. We offer the perspective of a real market application by exploring different binomial models and the associated methods of estimating the crucial parameter of volatility. We include simple binomial lattices, quadranomial lattices and demonstrate the sensitivity of the results to the choice of inputs and method.

Estimation rapide des paramètres d'un signal à phase polynomiale

National audiencePolynomial phase signals belong to a wide class of non-stationary signals used for modeling and engineering applications. In this paper, we take benefits of some advances in robust estimation in order to propose a new algorithm for estimating the parameters of a polynomial phase signal. The advantages of this algorithm are being fast and being robust to the shape of the noise

Parameter Estimation for Polynomial Phase Signals With a Fast and Robust Algorithm

International audiencePolynomial phase signals belong to a wide class of nonstationary signals used for modeling and engineering applications. In this paper, we take benefits of some advances in robust estimation in order to propose a new algorithm for estimating the parameters of a polynomial phase signal. This algorithm has the advantages to be fast and its structure is robust to the shape of the noise

Real option pricing in mixed-use development projects

The application of real options theory to commercial real estate has developed rapidly during the last 15 Years. In particular, several pricing models have been applied to value real options embedded in development projects. In this study we use a case study of a mixed use development scheme and identify the major implied and explicit real options available to the developer. We offer the perspective of a real market application by exploring different binomial models and the associated methods of estimating the crucial parameter of volatility. We include simple binomial lattices, quadranomial lattices and demonstrate the sensitivity of the results to the choice of inputs and method

Détection et localisation des panneaux routiers

Les panneaux routiers -- Obtention et gestion de la position des panneaux -- Description du système d'inspection et présentation des données -- Le système d'inspection -- Segmentation basée sur la couleur -- Détection des panneaux grâce à leur forme -- Solution proposée pour la détection des panneaux -- Pré-reconnaissance de forme -- Localisation des panneaux dans l'image -- Suivi et localisation des panneaux -- Utilisation de la redonnance temporelle -- Suivi des panneaux -- Localisation des panneaux à posteriori -- Simulation de l'inspection d'une portion de route

A fast robust and simple algorithm for estimating parameters of polynomial phase signals

Polynomial phase signals belong to a wide class of signals used for modeling but processing associated to them are always difficult since they are non-stationary signals. In the method introduced in this paper, we take benefits of some advances in robust estimation in order to build a new algorithm for estimating the phasis parameters of polynomial phase signal. This algorithm has the advantages of being fast and being able to deal with signal whose phase is a polynomial of unknown order. The structure of this algorithm is robust to the shape of the noise.Les signaux à phase polynomiale constituent une vaste classe de signaux utilisés en modélisation mais leurs traitements se révèlent difficiles en raison de leur caractère non-stationnaire. Dans la méthode présentée dans cet article, nous mettons à profit de récents travaux en matière d’estimation robuste afin de réaliser un nouvel algorithme d’estimation des paramètres de la phase d’un signal. Cet algorithme présente les avantages d’être rapide et capable de traiter des signaux dont la phase est d’ordre inconnu. La structure de cet algorithme reste indépendante par le type de bruit car il est résistant à la forme de la distribution du bruit

Unique Thermal Properties of Clothing Materials.

Cloth wearing seems so natural that everyone is self-deemed knowledgeable and has some expert opinions about it. However, to clearly explain the physics involved, and hence to make predictions for clothing design or selection, it turns out to be quite challenging even for experts. Cloth is a multiphased, porous, and anisotropic material system and usually in multilayers. The human body acts as an internal heat source in a clothing situation, thus forming a temperature gradient between body and ambient. But unlike ordinary engineering heat transfer problems, the sign of this gradient often changes as the ambient temperature varies. The human body also perspires and the sweat evaporates, an effective body cooling process via phase change. To bring all the variables into analysis quickly escalates into a formidable task. This work attempts to unravel the problem from a physics perspective, focusing on a few rarely noticed yet critically important mechanisms involved so as to offer a clearer and more accurate depiction of the principles in clothing thermal comfort