scholarly journals Inefficiency of Indian Real Estate indicators: A Need for Regulatory Agency & Index based on market deal

2012 ◽  
Vol 1 (1) ◽  
pp. 61-67
Author(s):  
Muthupandian B ◽  
Velmurugan
Keyword(s):  
Real Estate ◽  
Secondary Market ◽  
Decision Making Process ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector ◽  
The People ◽  
Online Exchange ◽  
Market Transaction ◽  
Real Estate Prices

The real estate sector is a major employment driver in India and it contributes a significant level to the GDP. Besides, it is the main source of wealth for all section of the people. There is no transparency and efficiency in the pricing of real estate transaction in-spite-of some indices representing the price movement of the real estate sector. This is because the price is based only on the primary market transaction. It‟s completely excluding the secondary market transaction of the sector. This paper attempts to address this issue by proposing an online exchange for real estate transaction, for bringing in more liquidity and transparencyto the sector, along with an index, based on the price traded in that exchange. These will a high relative measure to indicate and represent the price moment of the sector. This kind of regular monitoring of the real estate prices may be fruitful input for the different stake holders like buyers, seller, mediators, developers, investors, banks, housing finance companies, FIIs, private equities, analysts and others in their decision-making process.

Calling the Shots

Urban Studies ◽  
2011 ◽  
Vol 48 (15) ◽  
pp. 3169-3184 ◽  
Author(s):  
Gary Armstrong ◽  
Dick Hobbs ◽  
Iain Lindsay
Keyword(s):  
Real Estate ◽  
Olympic Games ◽  
World Peace ◽  
Ordinary People ◽  
London Borough ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector ◽  
The People ◽  
Olympic Movement

The Olympic Games promise great things; world peace and the transformation of the host city are but two ambitions of the Olympic Movement. The benefits and changes that the 2012 Olympics are supposed to bring to the London Borough of Newham—which will host some 80 per cent of the Olympic events—have been much lauded by the Olympic apparatchiks who typically proselytise about the transformation of communities, countries and individuals via the staging of the Games. The local Organising Committee and others—typically within the real estate sector—are the people who shape these sentiments into particular land deals that will serve to justify the plethora of deals, contracts and developments. Whilst the Olympics are about transformations, ostensibly in the lives of athletes, ordinary people and communities, transformations of an even more lasting sort occur in the Olympic neighbourhood through massive construction and servicing contracts. The Olympics are also about discipline which plays out not only in terms of the preparation of athletes to perform at their utmost, but is imperative to all the arrangements required to host such a huge event. For the good of the Games, people living in the shadow of the 2012 Olympic stadium face having their movements and their neighbourhoods subjected to all manner of prohibitions and limitations.

scholarly journals Machine Learning House Price Prediction

2020 ◽  
Vol 6 (12) ◽  
pp. 186-189
Author(s):  
Manu Shahi, Abhay Singh, Amita Goel Vasudha Bahl and Nidhi Sengar
Keyword(s):  
Machine Learning ◽  
Real Estate ◽  
Learning Algorithms ◽  
House Price ◽  
Machine Learning Algorithms ◽  
Lasso Regression ◽  
The Real ◽  
The Real Estate ◽  
The People ◽  
Real Estate Prices

This document present the implementation of Machine Learning algorithms for the prediction of the house and the real estate prices. As the house and real estate prices are subject to change with the market conditions, so it become very difficult to predict the real estate prices with the conventional methods as it may sometimes gives some exaggerated result that may incur losses. To predict the prices more accurately and precisely we predict the prices based on the statics of that particular area which has all the trends and factors on which the price is dependent. To analyse these data , several algorithms are used namely random forest, linear regression , lasso regression etc. Use of these algorithms decreases the margin of error and more precise result are achieved. So,we at this point recommend the real estate agents and house vendors as well as the people to look into the model for better valuation of the house. This model can also be integrated with the real estates websites to give better recommendation based on the prices using Machine Learning Algorithms.

scholarly journals Role of Behavioral Biases in Real Estate Prices in Pakistan

2021 ◽  
Vol 29 (1) ◽  
pp. 41-53
Author(s):  
M Asad Saleem Malik ◽  
Muhammad Zafar ◽  
Saif Ullah ◽  
Atta Ullah
Keyword(s):  
Real Estate ◽  
The Real ◽  
The Real Estate ◽  
Behavioral Biases ◽  
Gambler’S Fallacy ◽  
Real Estate Sector ◽  
Gambler's Fallacy ◽  
Market Factors ◽  
Real Estate Prices ◽  
Regret Aversion

Abstract The study aims to explore the effect of behavioral biases on financial decision making in the real estate sector of Pakistan. The data of a sample of 244 real estate investors are collected through a survey carried out using different sources. The findings of the study show the relationship of different biases, including overconfidence, herding effect, gambler’s fallacy, and regret aversion on prices of real estate. Real estate prices are more affected by overconfidence and gambler’s fallacy than herding effect and regrets aversion bias in Pakistan. The findings furthermore reveal that these biases do not depend on gender, education, and demographics. It is recommended to carefully consider the market factors while making decisions in real estate, as the prices do not always show the real value of the property.

Information security in the South Australian real estate industry

2014 ◽  
Vol 22 (1) ◽  
pp. 24-41 ◽  
Author(s):  
Deepa Mani ◽  
Kim-Kwang Raymond Choo ◽  
Sameera Mubarak
Keyword(s):  
Risk Management ◽  
Information Security ◽  
Real Estate ◽  
South Australia ◽  
Security Threats ◽  
The South ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector

Purpose – Opportunities for malicious cyber activities have expanded with the globalisation and advancements in information and communication technology. Such activities will increasingly affect the security of businesses with online presence and/or connected to the internet. Although the real estate sector is a potential attack vector for and target of malicious cyber activities, it is an understudied industry. This paper aims to contribute to a better understanding of the information security threats, awareness, and risk management standards currently employed by the real estate sector in South Australia. Design/methodology/approach – The current study comprises both quantitative and qualitative methodologies, which include 20 survey questionnaires and 20 face-to-face interviews conducted in South Australia. Findings – There is a lack of understanding about the true magnitude of malicious cyber activities and its impact on the real estate sector, as illustrated in the findings of 40 real estate organisations in South Australia. The findings and the escalating complexities of the online environment underscore the need for regular ongoing training programs for basic online security (including new cybercrime trends) and the promotion of a culture of information security (e.g. when using smart mobile devices to store and access sensitive data) among staff. Such initiatives will enable staff employed in the (South Australian) real estate sector to maintain the current knowledge of the latest cybercrime activities and the best cyber security protection measures available. Originality/value – This is the first academic study focusing on the real estate organisations in South Australia. The findings will contribute to the evidence on the information security threats faced by the sector as well as in develop sector-specific information security risk management guidelines.

scholarly journals The Impacts in Real Estate of Landscape Values: Evidence from Tuscany (Italy)

2021 ◽  
Vol 13 (4) ◽  
pp. 2236
Author(s):  
Francesco Riccioli ◽  
Roberto Fratini ◽  
Fabio Boncinelli
Keyword(s):  
Real Estate ◽  
House Prices ◽  
Spatial Econometric ◽  
The Real ◽  
The Real Estate ◽  
Landscape Values ◽  
Individual Perception ◽  
Real Estate Prices ◽  
The Aesthetic ◽  
The Individual

Using spatial econometric techniques and local spatial statistics, this study explores the relationships between the real estate values in Tuscany with the individual perception of satisfaction by landscape types. The analysis includes the usual territorial variables such as proximity to urban centres and roads. The landscape values are measured through a sample of respondents who expressed their aesthetic-visual perceptions of different types of land use. Results from a multivariate local Geary highlight that house prices are not spatial independent and that between the variables included in the analysis there is mainly a positive correlation. Specifically, the findings demonstrate a significant spatial dependence in real estate prices. The aesthetic values influence the real estate price throughout more a spatial indirect effect rather than the direct effect. Practically, house prices in specific areas are more influenced by aspects such as proximity to essential services. The results seem to show to live close to highly aesthetic environments not in these environments. The results relating to the distance from the main roads, however, seem counterintuitive. This result probably depends on the evidence that these areas suffer from greater traffic jam or pollution or they are preferred for alternative uses such as for locating industrial plants or big shopping centres rather than residential use. Therefore, these effects decrease house prices.

scholarly journals Evaluation of the Applicability of Statistical Methods in Studies on Price Dynamics on the Real Estate Market

2013 ◽  
Vol 21 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Sebastian Kokot ◽  
Marcin Bas
Keyword(s):  
Real Estate ◽  
Traditional Approach ◽  
Real Estate Market ◽  
Price Dynamics ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
Time Period ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The specific character of the real estate market is the reason why observations of transaction prices seen as statistical variables are taken in a non-standard way. In the traditional approach each time period or specific moments of time are attributed with one observation of a studied variable per one object. In the case of the real estate market, this is not possible since transactions relate to different objects, i.e., properties, and occur at irregular, or even random, moments. This is why traditional methods used to examine the dynamics of economic phenomena must be adapted to specific conditions on the real estate market. Keeping that in mind, the aim of this paper is to adapt classical statistical examination methods of dynamics to specific conditions of the real estate market followed by the actual examination of the dynamics of real estate prices in three sub-segments of the housing market in Szczecin. On its basis, the authors evaluate various methods of examining real estate price dynamics in terms of their applicability in real estate appraisal procedures and, in a broader perspective, present characteristic phenomena that can be observed on the real estate market.

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