Estimating Market Fundamentals from REIT data

2021 ◽  
Author(s):  
David Geltner ◽  
Anil Kumar ◽  
Alex Van de Minne
Keyword(s):  
Market Fundamentals

scholarly journals Using the Self-Organising Map to Identify Regularities across Country-Specific Housing-Market Contexts

10.1068/b3186 ◽  
2005 ◽  
Vol 32 (1) ◽  
pp. 89-110 ◽  
Author(s):  
Tom Kauko
Keyword(s):  
Housing Market ◽  
Semiparametric Regression ◽  
The Self ◽  
Cross Sectional ◽  
Public And Private ◽  
Institutional Differences ◽  
Market Fundamentals ◽  
Self Organising Map ◽  
Public And Private Sector ◽  
Housing Submarkets

The aim of exploring and monitoring housing-market fundamentals (prices, dwelling features, area density, residents, and so on) on a macrolocational level relates to both public and private sector policymaking. Housing market segmentation (that is, the emergence of housing submarkets), a concept with increasing relevance, is defined as the differentiation of housing in terms of the income and preferences of the residents and in terms of administrative circumstances. In order to capture such segmentation empirically, the author applies a fairly new and emerging technique known as the ‘self-organising’ map (SOM), or ‘Kohonen map’. The SOM is a type of (artificial) neural network—a nonlinear and flexible (that is, nonparametric or semiparametric) regression and ‘machine learning’ technique. By utilising the ability of the SOM to visualise patterns, one can analyse various dimensions within the variation of the dataset. Segmentation may then be detected depending on the resulting patterns across the map layers, each of which represents the data variation for one input variable. Utilising an inductive modelling strategy, the author runs cross-sectional and nationwide data on the owner-occupied housing markets of Finland (documentation presented elsewhere), the Netherlands, and Hungary with the SOM technique. On the basis of the resulting configurations certain regularities (similarities and differences) across the three national contexts are identified. In all three cases the segments are determined by physical and institutional differences between the housing bundles and localities. The exercise demonstrates how the inductive SOM-based approach is well-suited for illustrating the contextual factors that determine housing market structure.

scholarly journals Do natural rubber price bubbles occur?

2019 ◽  
Vol 65 (No. 2) ◽  
pp. 67-73 ◽  
Author(s):  
Chi-Wei Su ◽  
Lu Liu ◽  
Ran Tao ◽  
Oana-Ramona Lobonţ
Keyword(s):  
Time Series ◽  
Natural Rubber ◽  
Supply And Demand ◽  
Oil Prices ◽  
Climatic Changes ◽  
Price Bubbles ◽  
Augmented Dickey Fuller ◽  
Multiple Bubbles ◽  
Market Fundamentals ◽  
The Stability

In this paper, we employ the Generalized Supremum Augmented Dickey-Fuller test in order to identify the existence of multiple bubbles in natural rubber. This approach is practical for the using of time series and identifies the beginning and end points of multiple bubbles. The results reveal that there are five bubbles, where exist the divergences between natural rubber prices and their basic values on account of market fundamentals. The five bubbles are related to imbalance between supply and demand, inefficiencies of smallholders market, oil prices, exchange rate and climatic changes through analyses. Thus, the corresponding authorities are supposed to identify bubbles and consider their evolutions, which is beneficial to the stability of natural rubber price.

The stock market, fundamentals, cash flow, and private investment: evidence from Japan

2000 ◽  
Vol 12 (4) ◽  
pp. 295-310 ◽  
Author(s):  
Robert Dekle ◽  
Dale Henderson ◽  
Sebastian Thomas
Keyword(s):  
Stock Market ◽  
Cash Flow ◽  
Private Investment ◽  
Market Fundamentals
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