CHF 70.00

Forecasting Models for the German Office Market
Dissertation Universität St. Gallen, 2009

Englisch · Taschenbuch

Versand in der Regel in 6 bis 7 Wochen

Beschreibung

Mehr lesen

This work is motivated by the research gap evident in the area of forecasting models for the German office market. Since rent, price or yield forecasting research is mainly done by commercially oriented organizations, this work delivers an examination from a scientific point of view. Thus the focus is set on an empirical investigation of several rent and total yield forecasting models for nine major German cities. Their applicability and performance are analyzed and city as well as forecasting horiz- specific patterns are determined and interpreted. After the literature review, mainly covering Anglo-Saxon research, I derive the theoretical foundations which are important in executing the empirical part of the work. Therefore, I discuss theoretically general real estate market characteristics, the specifics of time series and panel data, common forecasting models, and forecasting techniques as well as performance measures. The major findings of the first part of the empirical work, which contains the rent series investigation, is that ARIMA, GARCH and multivariate regression models are generally able to forecast rent series in the German office market. Furthermore, I observed that GARCH models are able to outperform single ARIMA models for forecasting horizons of three to five years, when increased volatility appears within the respective city rent series. Moreover, univariate models outperform multivariate regression models in the short run. On the other hand, multivariate regression models outperform the univariate models in the longer run. However, I found cities where one model permanently dominates.

Über den Autor / die Autorin

Dr. Alexander Bönner promovierte bei Prof. Dr. Pascal Gantenbein am Schweizerischen Institut für Banken und Finanzen an der Universität St. Gallen (Schweiz). Er ist als wissenschaftlicher Assistent am Lehrstuhl für Finanzwirtschaft der St. Gallen bei Prof. Dr. Dr. h.c. Klaus Spremann tätig.

Zusammenfassung

In every market with free floating prices, all market participants are interested in the future developments of these prices. However, there is an evident research gap for forecasting models for the German office market.



Alexander Bönner closes this gap by focusing on an empirical investigation of several rent and total yield forecasting models for nine major German cities. The applicability and performance of ARIMA, GARCH and multivariate regression models are analyzed and city as well as forecasting horizon-specific patterns are determined and interpreted. Univariate rent forecasting models generally outperform multivariate rent forecasting regression models in the short run. In the long run, multivariate regression models dominate. However, one must bear in mind that in some cities one model permanently outperforms the other. Eventually, the rent level is mainly determined by its economic fundamentals, which is also demonstrated for the total yield examination.

Produktdetails

Autoren Alexander Bönner
Verlag Gabler
 
Inhalt Buch
Produktform Taschenbuch
Erscheinungsdatum 19.02.2009
Thema Sozialwissenschaften, Recht,Wirtschaft > Wirtschaft > Volkswirtschaft
 
EAN 9783834915252
ISBN 978-3-8349-1525-2
Anzahl Seiten 175
Illustration XX, 175 p. 65 illus.
Abmessung (Verpackung) 14.8 x 21 cm
Gewicht (Verpackung) 258 g
 
Serie Gabler Edition Wissenschaft
Gabler Edition Wissenschaft
Themen Deutschland; Wirtschaft, Recht, Finance, Real Estate, Finance, general, Economics and Finance, Financial Economics, Real Estate Finance
 

Kundenrezensionen

Zu diesem Artikel wurden noch keine Rezensionen verfasst. Schreibe die erste Bewertung und sei anderen Benutzern bei der Kaufentscheidung behilflich.

Schreibe eine Rezension

Top oder Flop? Schreibe deine eigene Rezension.

Für Mitteilungen an CeDe.ch kannst du das Kontaktformular benutzen.

Die mit * markierten Eingabefelder müssen zwingend ausgefüllt werden.

Mit dem Absenden dieses Formulars erklärst du dich mit unseren Datenschutzbestimmungen einverstanden.