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Advanced Forecasting Model on Land Market Value Based on USA Real Estate Market

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Release : 2019
Genre : Electronic dissertations
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Advanced Forecasting Model on Land Market Value Based on USA Real Estate Market by : Lei Wang

Download or read book Advanced Forecasting Model on Land Market Value Based on USA Real Estate Market written by Lei Wang. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: This research presents a time series estimation and prediction methods with the use of classic and advanced forecasting tools. Our discussion about di erent time series models is supported by giving the experimental forecast results, performed on several macroeconomic variables. Also, the main section deal with the experience of using such data in econometric analysis. Besides, the implementation of SAS and R software improve the parameter estimation and forecasting accuracy. The objective in providing crucial statistical techniques is to enable government and investors to make informed decisions regarding real estate. Most importantly, we obtain how to add value to business and apply skills set real estate in a real world environment. Eventually, the summary of various existing forecasting models can provide information to develop an appropriate forecasting model which describes the inherent feature of the series.

Development of a Forecasting Model to Predict the Downturn and Upturn of a Real Estate Market in the Inland Empire

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Release : 2011-04
Genre : Business & Economics
Kind : eBook
Book Rating : 944/5 ( reviews)

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Book Synopsis Development of a Forecasting Model to Predict the Downturn and Upturn of a Real Estate Market in the Inland Empire by : Thomas F. Flynn

Download or read book Development of a Forecasting Model to Predict the Downturn and Upturn of a Real Estate Market in the Inland Empire written by Thomas F. Flynn. This book was released on 2011-04. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Real Estate Modelling and Forecasting

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Release : 2010-04-15
Genre : Business & Economics
Kind : eBook
Book Rating : 167/5 ( reviews)

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Book Synopsis Real Estate Modelling and Forecasting by : Chris Brooks

Download or read book Real Estate Modelling and Forecasting written by Chris Brooks. This book was released on 2010-04-15. Available in PDF, EPUB and Kindle. Book excerpt: As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.

Market Analysis for Real Estate

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Release : 2020-08-06
Genre : Architecture
Kind : eBook
Book Rating : 16X/5 ( reviews)

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Book Synopsis Market Analysis for Real Estate by : Rena Mourouzi-Sivitanidou

Download or read book Market Analysis for Real Estate written by Rena Mourouzi-Sivitanidou. This book was released on 2020-08-06. Available in PDF, EPUB and Kindle. Book excerpt: Market Analysis for Real Estate is a comprehensive introduction to how real estate markets work and the analytical tools and techniques that can be used to identify and interpret market signals. The markets for space and varied property assets, including residential, office, retail, and industrial, are presented, analyzed, and integrated into a complete understanding of the role of real estate markets within the workings of contemporary urban economies. Unlike other books on market analysis, the economic and financial theory in this book is rigorous and well integrated with the specifics of the real estate market. Furthermore, it is thoroughly explained as it assumes no previous coursework in economics or finance on the part of the reader. The theoretical discussion is backed up with numerous real estate case study examples and problems, which are presented throughout the text to assist both student and teacher. Including discussion questions, exercises, several web links, and online slides, this textbook is suitable for use on a variety of degree programs in real estate, finance, business, planning, and economics at undergraduate and MSc/MBA level. It is also a useful primer for professionals in these disciplines.

Applied Quantitative Analysis for Real Estate

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Release : 2020-09-13
Genre : Business & Economics
Kind : eBook
Book Rating : 010/5 ( reviews)

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Book Synopsis Applied Quantitative Analysis for Real Estate by : Sotiris Tsolacos

Download or read book Applied Quantitative Analysis for Real Estate written by Sotiris Tsolacos. This book was released on 2020-09-13. Available in PDF, EPUB and Kindle. Book excerpt: To fully function in today’s global real estate industry, students and professionals increasingly need to understand how to implement essential and cutting-edge quantitative techniques. This book presents an easy-to-read guide to applying quantitative analysis in real estate aimed at non-cognate undergraduate and masters students, and meets the requirements of modern professional practice. Through case studies and examples illustrating applications using data sourced from dedicated real estate information providers and major firms in the industry, the book provides an introduction to the foundations underlying statistical data analysis, common data manipulations and understanding descriptive statistics, before gradually building up to more advanced quantitative analysis, modelling and forecasting of real estate markets. Our examples and case studies within the chapters have been specifically compiled for this book and explicitly designed to help the reader acquire a better understanding of the quantitative methods addressed in each chapter. Our objective is to equip readers with the skills needed to confidently carry out their own quantitative analysis and be able to interpret empirical results from academic work and practitioner studies in the field of real estate and in other asset classes. Both undergraduate and masters level students, as well as real estate analysts in the professions, will find this book to be essential reading.

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