Empirical evidence on the ownership and liquidity of real estate tokens

To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financial and economic consequences of tokenizing 58 residential rental properties in the US,particularly those in Detroit.Tokenization aims at fragmented ownership.We found that the residential properties examined have 254 owners on average.Investors with a greater than USD 5,000 investment in real estate tokens,diversify their real estate ownership across properties within and across the cities.Property ownership changes about once yearly,with more changes for proper-ties on decentralized exchanges.We report that real estate token prices move accord-ing to the house price index;hence,investing in real estate tokens provides economic exposure to residential house prices.

Research on the intelligent supervision and operation platform of railway real estate

Railway real estate is the fundamental element of railway transportation production and operation.Effective management and rational utilization of railway real estate is essential for railway asset operation.Based on the investigation of the requirements of railway real estate management and operation,combined with Beidou positioning,GIS(Geographic Information System),multi-source data fusion and other cutting-edge technologies,this paper puts forward the multi-dimensional dynamic statistical method of real estate information,the identification method of railway land occupation and the comprehensive evaluation method of real estate development and utilization potential,and build the railway real estate supervision and operation platform,design the function of the platform,so as to provide intelligent solutions for the railway real estate operation.

Architecting the Metaverse: Blockchain and the Financial and Legal Regulatory Challenges of Virtual Real Estate

There has been disagreement over the value of purchasing space in the metaverse, but many businesses including Nike, The Wendy’s Company, and McDonald’s have jumped in headfirst. While the metaverse land rush has been called an “illusion” given underdeveloped infrastructure, including inadequate software and servers, and the potential opportunities for economic and legal abuse, the “real estate of the future” shows no signs of slowing. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the long-term legal and regulatory considerations of capitalizing on the investment, as well as the manner in which blockchain technology can secure users’ data and digital assets, has yet to be properly investigated. With the metaverse still in a conceptual phase, building a new 3D social environment capable of digital transactions will represent most of the initial investment in time in human capital. Digital twin technologies, already well-established in industry, will be ported to support the need to architect and furnish the new digital world. The return on and viability of investing in the “real estate of the future” raises questions fundamental to the success or failure of the enterprise. As such this paper proposes a novel framing of the issue and looks at the intersection where finance, technology, and law are converging to prevent another Dot-com bubble of the late 1990s in metaverse-based virtual real estate transactions. Furthermore, the paper will argue that these domains are technologically feasible, but the main challenges for commercial users remain in the legal and regulatory arenas. As has been the case with the emergence of online commerce, a legal assessment of the metaverse indicates that courts will look to traditional and established legal principles when addressing issues until the enactment of federal and/or state statutes and accompanying regulations. Lastly, whereas traditional regulation of real estate would involve property law, the current legal framing of ownership of metaverse assets is governed by contract law.

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

A Concept about Guide on Hazards for the Real Estate Business-An Example from Bulgaria

The paper is a part of wider investigation related to the application of basic sciences to the sustainable development of society.It deals with the presentation of knowledge to the real estate(fast growing business)about the local natural and man-made hazards in the near vicinity of any structure(inhabitant,recreation area,land,etc.)and their influence to the social safety and human comfort of life.The structure,necessary information and knowledge base for visible or hidden hazards about a guide for the real estate business is included.An example of application the knowledge about seismic hazard and related phenomena simplified to be more available to the non-specialists(such as real estate agents and companies)targeted to Sofia(the largest urban center and capital of Bulgaria)can attract and improve the learning abilities of the real estate for the society’s sake.

Examining the Impact Factors and Strategies to Mitigate Economic Fluctuation in the Real Estate Sector

With the continuous growth of the economy and the rapid pace of urbanization,the real estate sector has assumed an increasingly substantial role within the national economy.Ensuring the stable and sustainable development of the real estate sector to maximize its societal and economic contributions has become a pressing issue.China,presently engaged in an extensive urbanization drive,places real estate development and sales as pivotal components in the broader real estate industry,significantly impacting the overall functionality of the real estate market.Real estate,being a comprehensive system encompassing land,housing,infrastructure,and other key elements,exerts a profound influence on people’s basic needs such as shelter,sustenance,and daily living.Its evolution directly shapes the trajectory of the national economy and social stability.Therefore,to foster the consistent and robust growth of China’s real estate economy,it is necessary to implement effective measures that entail a systematic and thorough analysis of the factors responsible for the fluctuations in China’s real estate economy.

A Review of Domestic and Foreign Research on Real Estate Financial Management

With the tightening of house purchase policies in recent years, the introduction of financial and land restriction policies, as well as the impact of the COVID-19 pandemic, real estate bombshells are common. Real estate is in the critical stage of transformation and upgrading, and industrial development is facing dire challenges and pressure for survival. As an important part of enterprise management, financial management is directly related to the success or failure of enterprise development. Facing the financial risks emerging in the financial management of the real estate industry at this stage, this review begins from financial management personnel training, investment calculation management, budget management, and asset management in the effort of optimizing the real estate financial management operating mechanism under the new situation and ensuring the healthy and stable development of real estate enterprises, while maintaining core competitiveness.

The Impact of Hot Money on Chinese Real Estate Price

Because of the expectation of RMB appreciation and the extremely high return rate of Chinese real estate market,more and more hot money rushed into China.As a result,the real estate price level is getting higher and higher,the bubble economy is getting worse,and the Chinese real estate is accumulating numerous risks.This study tried to find out the relation between the hot money and Chinese real estate price level with the help of empirical method.The study not only analyzed the impact of hot money on Chinese real estate price level and its harmful influence over the economy,but also proposed some suggestions to supervise the real estate market.

Real estate appraisal system based on GIS and BP neural network

For the inefficiency and inaccuracy of appraisal method of traditional estate appraisal theory, the real estate appraisal system based on GIS and BP neural network was established. The structure of the system was designed which includes appraisal model, trade case, GIS database and query analysis module. With the help of the L-M algorithm in MATLAB software, BP neural network was improved and the trade cases were trained, then the BP neural network which has already been trained was tested. At the same time, the BP neural and GIS were put together to construct the hedonic price estimate model. The C# and ArcGIS9.3 were used to achieve the system in VS2008. City basic geographic data and real estate related information were used as the basic data in practice. The results show that the functions of querying, adding and editing the spatial data and attribute data are achieved and also the efficiency and accuracy of real estate are improved, so that the new method of real estate is provided by the system.

Design of the Blockchain Smart Contract: A Use Case for Real Estate

Blockchain is a fast-disruptive technology becoming a key instrument in share economy. In recent years, Blockchain has received considerable attention from many researchers and government institutions. This paper aims to present the Blockchain and smart contract for a specific domain which is real estate. A detailed design of smart contract is presented and then a use case for renting residential and business buildings is examined.

A group consensus model for evaluating real estate investment alternatives

Background:Individual decision-making largely influences the effectiveness of decisions and benefits of investments.Methods:In this article,a consensus model for group decision-making(GDM),based on the analytic hierarchy process(AHP),is developed to gather group ideas and analyze the real estate investment environment under multi-criteria problems.Twelve evaluation procedures of the developed model,which increase the convergence of the opinions of multiple experts,are proposed.Results:An empirical case about the real estate investment environment is applied to certify the feasibility of this developed model.Conclusions:the evaluation procedures have been fully observed with several rounds of discussions,and have manifested the experiences of experts.Besides,the evaluation results are in accordance with real-world situations,which demonstrates that our developed model is a feasible analysis tool for real estate investors to obtain better profits and lower risk.

Research on Internal Control Information Disclosure of Real Estate Industry-Taking Taihe Group as an Example

After the outbreak of the Enron incident in the United States, China’s attention to internal control information disclosure has gradually increased. As a pillar industry of the national economy, real estate industry internal control system is sound, which has an important impact on social stability and healthy economic development. Therefore, this paper selects a company in the real estate industry, through the analysis of its internal control information disclosure, finds out its existing problems, and puts forward practical and feasible suggestions.

Research on the Effect of Artificial Intelligence Real Estate Forecasting Using Multiple Regression Analysis and Artificial Neural Network: A Case Study of Ghana

To transition from conventional to intelligent real estate, the real estate industry must enhance its embrace of disruptive technology. Even though the real estate auction market has grown in importance in the financial, economic, and investment sectors, few artificial intelligence-based research has tried to predict the auction values of real estate in the past. According to the objectives of this research, artificial intelligence and statistical methods will be used to create forecasting models for real estate auction prices. A multiple regression model and an artificial neural network are used in conjunction with one another to build the forecasting models. For the empirical study, the study utilizes data from Ghana apartment auctions from 2016 to 2020 to anticipate auction prices and evaluate the forecasting accuracy of the various models available at the time. Compared to the conventional Multiple Regression Analysis, using artificial intelligence systems for real estate appraisal is becoming a more viable option (MRA). The Artificial Neural network model exhibits the most outstanding performance, and efficient zonal segmentation based on the auction evaluation price enhances the model’s prediction accuracy even more. There is a statistically significant difference between the two models when it comes to forecasting the values of real estate auctions.

Application of the Option Game Theory to the Real Estate Enterprise Investment Decision

One of the remarkable characteristics of the current development of China's national economy is the increase of uncertainties, which makes the traditional method more and more unsuitable for the current economic development in the real estate investment process. Based on the option game theory, the investment decision making of real estate is analyzed here, the investment optimization mathematic model established, and Nash Equilibrium discussed. Through case studies, we analyze the application of game option in the real estate, which is put under symmetrical duopoly. The conclusions will contribute to both the theory on and practice of the present investment in the real estate enterprise.

Process-oriented organizational structure and its application in real estate development enterprises in China

This paper analyzes the shortcomings of the current organizational structure of real estate development enterprises in China. Integrating the idea of Business Process Reengineering (BPR) with organizational reformation, the authors bring out a process-oriented organizational structure. A further study on the application of process-oriented organizational structure in real estate development enterprises is carried out in a test case. Using residence-development process as an example, the authors illustrate the composition and operation of the business process system of real estate development enterprises.

The analysis of capital structure of Chinese real estate listed companies

Capital structure is the basis for assessing the efficiency of enterprise financing activity. The rational capital structure could reduce the cost of capital and plays an important role in managing a company. Thus this paper, based on the real estate listed companies on Shenzhen and Shanghai stock markets, analyzes the factors which influence capital structure, such as profitability, size, collateral value of assets, growth, stockholder’s equity, concentration degree of control power, ownership attribute, and applied statistics tools used to help the real estate listed companies optimize the structure of capital.

Analysis on using UPREITs in real estate finance in United States

This paper gave an overview introduction about umbrella partnership real estate investment trust (UPREIT) to the readers who are not related to real estate and accounting major. To show how UPREIT defer capital gain taxes,makes good cash flow and maximize profit in real estate finance,the paper included the theory and structure of UPREIT(real estate investment trust),partnership issues,advantage and disadvantage,and created a proforma to demonstrate how UPREIT works.

A Research on Government Regulations on High Price and High Vacancy in Real Estate: A Case Study of the Southern District of Qingdao City

Real estate plays a vital role in national economy and contributes a lot to social development. However, the rapid progress that has been made brings some problems, such as high price and high vacacy. This thesis takes Southern District of Qingdao City as an example to illustrate government regulation concerning real estate, and at the end some suggestions are provided.