Amidst the dramatic real estate fluctuations in the first decade of the twenty-first century, this study recognized that there is a necessity to create a real estate prediction model for future real estate ventures and prevention of losses such as the mortgage meltdown and housing bust. This real estate prediction model study sought to reinstall the integrity into the American building and development industry, which was tarnished by the sudden emergence of various publications offering get-rich-quick schemes. In the fast-paced and competitive world of lending and real estate development, it is becoming more complex to combine current and evolving factors into a profitable business model. This prediction model correlated past real estate cycle pinpoints to economical driving forces in order to create an ongoing formula. The study used a descriptive, secondary interpretation of raw data already available. Quarterly data was taken from the study's seven independent variables over a 24-year span from 1985 to 2009 to examine the correlation over two real estate cycles. Public information from 97 quarters (1985-2009) was also gathered on seven topics: consumer confidence, loan origination volume, construction employment statistics, migration, GDP, inflation, and interest rates. The Null hypothesis underwent a test of variance at a .05 level of significance. Multiple regression analysis uncovered that four of seven variables have correlated and could predict movement in real estate cycle evidence from previous data, based in the Inland Empire. GDP, interest rates, loan origination volume, and inflation were the four economical driving variables that completed the Inland Empire's real estate prediction model and global test. Findings from this study certify that there is correlation between economical driving factors and the real estate cycle. These correlations illustrate patterns and trends, which can become a prediction model using statistics. By interpreting and examining the data, this study believes that the prediction model is best utilized through pinpointing an exact numerical location by running calculations through the established global equation, and recommends further research and regular update of quarterly trends and movements in the real estate cycle and specific variables in the formula.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 12397639-n
Anzahl: Mehr als 20 verfügbar
Anbieter: BargainBookStores, Grand Rapids, MI, USA
Paperback or Softback. Zustand: New. Development of a Forecasting Model to Predict the Downturn and Upturn of a Real Estate Market in the Inland Empire. Book. Bestandsnummer des Verkäufers BBS-9781599423944
Anbieter: PBShop.store US, Wood Dale, IL, USA
PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9781599423944
Anzahl: Mehr als 20 verfügbar
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9781599423944
Anzahl: Mehr als 20 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9781599423944_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
Paperback. Zustand: New. Bestandsnummer des Verkäufers 6666-IUK-9781599423944
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 12397639-n
Anzahl: Mehr als 20 verfügbar
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
Paperback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Bestandsnummer des Verkäufers C9781599423944
Anzahl: Mehr als 20 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Amidst the dramatic real estate fluctuations in the first decade of the twenty-first century, this study recognized that there is a necessity to create a real estate prediction model for future real estate ventures and prevention of losses such as the mortgage meltdown and housing bust. This real estate prediction model study sought to reinstall the integrity into the American building and development industry, which was tarnished by the sudden emergence of various publications offering get-rich-quick schemes. In the fast-paced and competitive world of lending and real estate development, it is becoming more complex to combine current and evolving factors into a profitable business model. This prediction model correlated past real estate cycle pinpoints to economical driving forces in order to create an ongoing formula. The study used a descriptive, secondary interpretation of raw data already available. Quarterly data was taken from the study's seven independent variables over a 24-year span from 1985 to 2009 to examine the correlation over two real estate cycles. Public information from 97 quarters (1985-2009) was also gathered on seven topics: consumer confidence, loan origination volume, construction employment statistics, migration, GDP, inflation, and interest rates. The Null hypothesis underwent a test of variance at a .05 level of significance. Multiple regression analysis uncovered that four of seven variables have correlated and could predict movement in real estate cycle evidence from previous data, based in the Inland Empire. GDP, interest rates, loan origination volume, and inflation were the four economical driving variables that completed the Inland Empire's real estate prediction model and global test. Findings from this study certify that there is correlation between economical driving factors and the real estate cycle. These correlations illustrate patterns and trends, which can become a prediction model using statistics. By interpreting and examining the data, this study believes that the prediction model is best utilized through pinpointing an exact numerical location by running calculations through the established global equation, and recommends further research and regular update of quarterly trends and movements in the real estate cycle and specific variables in the formula. Bestandsnummer des Verkäufers 9781599423944
Anzahl: 1 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 12397639
Anzahl: Mehr als 20 verfügbar