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This paper aims to test the hedging ability of housing investment against inflation in Japan and the USA during the period 2000–2020.

This study applies the deep learning method and The exponential general autoregressive conditional heteroskedasticity in mean (1, 1) model with breaks.

Within the asymmetric framework, it is found that housing returns (HR) can hedge against inflation in both these markets, which mentions that when investing in the housing market in Japan and the USA, investors are compensated for bearing from inflation. This result is consistent with Fisher’s hypothesis. Especially, the empirical results show that the risk-return tradeoff is available in Japan’s housing market and not available in the US housing market. Any signal of a high inflation rate – referred to as “bad news” – may cause a drop in HR in Japan and a raise in the USA.

To the best of the author’s knowledge, this is one of the first studies using the deep learning method (long short-term memory model) to estimate the expected/unexpected inflation rates.

By modelling China’s property price changes and their effect on GDP, this study aims to develop a more general model of the costs and benefits driving price bubbles.

The authors develop a five-sector dynamic model (using data from China and seven other comparator jurisdictions), resulting in a bubble risk factor. The authors then correlate this risk factor with changes in property prices and resulting changes in GDP.

The authors find that economic structures (the way GDP, property prices and other variables change relative to each other) can change during/after a financial crisis. The authors also find that price disequilibria can help predict the risk of a property price fall – which thus reverberates into GDP change.

To the best of the authors’ knowledge, no dynamic models of price bubbles exist (though many exist of financial bubbles). The authors provide both theoretical novelties (such as providing a model of risk using non-linear differential equations) and practical ones (showing when we can expect Chinese GDP to fall).

The purpose of this paper is to create an endurance index of housing investor sentiment and use it to forecast housing stock returns. This study performs not only in-sample and out-of-sample forecasting, like many previous studies did, but also a true forecasting by using all lag terms of independent variables. In addition, an evaluation procedure is applied to quantify the quality of forecasts.

Using a binomial probability distribution model, this paper creates an endurance index of housing investor sentiment. The index reflects the probability of the high or low stock price being the close price for the Philadelphia Stock Exchange Housing Sector Index. This housing investor sentiment endurance index directly uses housing stock price differentials to measure housing investor reactions to all relevant news. Empirical results in this study suggest that the index can not only play a significant role in explaining variations in housing stock returns but also have decent forecasting ability.

Results of this study reveal the considerable forecasting ability of the index. Monthly forecasts of housing stock returns have an overall accuracy of 51 per cent, while the overall accuracy of 8-quarter rolling forecasts even reaches 84 per cent. In addition, the index has decent forecasting ability on changes in housing prices as suggested by the strong evidence of one-direction causal relations running from the endurance index to housing prices. However, extreme volatility of housing stock returns may impair the forecasting quality.

The endurance index of housing investor sentiment is easy to construct and use for forecasting housing stock returns. The demonstrated predictability of the index on housing stock returns in this study can have broad implications on housing-related business practices through providing an effective forecasting tool to investors and analysts of housing stocks, as well as housing policy-makers.

Despite different investor sentiment proxies suggested in the previous studies, few of them can effectively predict stock returns, due to some embedded limitations. Many increases and decreases inn prices cancel out each other during the trading day, as many unreliable sentiments cancel out each other. This dynamic process reveals not only investor sentiment but also resilience or endurance of sentiment. It is only long-lasting resilient sentiment that can be built in the closing price. It means that the only feasible way to use investor sentiment contained in stock prices to forecast future stock prices is to detach resilient investor sentiment from stock prices and construct an index of endurance of investor sentiment.

This study presents a structured investigation of the most important causes for delay in commercial real estate transactions. It assesses the potential of digital technologies such as “Blockchain”, “Property Passports” or “Automated Valuation Models” to make transactions faster and cheaper.

The authors conduct a focus group interview to identify the individual steps and the parties involved in real estate transactions. Subsequently, the authors discuss the prospects of digital technologies based on semi-structured interviews with real estate professionals and PropTech executives, and a comprehensive screening of technological solutions offered by PropTech firms.

The lack of an up-to-date, single pool of standardised property information turns out to be the most critical cause for delay in real estate transactions. However, the most promising technologies to mitigate this problem, in particular digital property passports summarising all relevant building information, face substantial barriers to adoption. The real estate industry has so far not been willing to more openly share data, which is a pre-requiste for the successful introduction of property passports. In addition, the principle of caveat emptor makes a lengthy due diligence process essential for buyers.

The authors conclude that industry-wide collaborations are necessary to help major efficiency gaining technologies to break through. Insurance products should accompany property data log books to guarantee the quality of data provided.

This study considers the potential impact of technologies in the wider context of the complete real estate transaction process. It identifies the major phases of that process and the associated bottlenecks. The authors gather evidence both from industry experts and PropTech executives and contrast their views regarding the potential of digital technologies to remove those bottlenecks.

The purpose of this paper is to analyze the determinants and the operational aspects of real estate crowdfunding (RECF henceforth). It addresses RECF growth, drivers and platforms in light of modern digital technology.

A comparison with traditional real estate funding is provided, and the ease and advantages that RECF offers to real estate investors are analyzed. The risks and rewards of crowdfunding in general and RECF in particular are also addressed.

Inasmuch as RECF appears novel and disruptive, research in this paper dates RECF back to the seventieth century. The findings thus posit that RECF is an evolutionary process while it is currently transformative and disruptive.

This is a novel look into RECF, particularly in terms of data, analyses and evaluation of alternatives.

The development and testing of the hedonic methods for property valuation require statistical analysis and professional preparation of relevant databases. As a first step, the presumable relevant influencing variables (parameters) have to be determined. Previous studies have shown a large variety of parameters which overlap or deviate from each other. This study aims to collect, systematise and structure different parameters for the further development and testing of hedonic models.

The study comprises a detailed research and deeper analysis of previous studies regarding the hedonic valuation (mainly for residential properties). Flanking areas of examination serve, if they are appropriately suitable, as supplements (e.g. performance analysis and regression). Parameters are extracted from a wide range of literature, compared and integrated into an overall presentation of the results.

In total, 407 parameters were extracted from previous studies on hedonic valuation and performance analysis. Because of various definitions of some parameters in the literature, the current paper combined them in one meaning to avoid misunderstandings in further analysis. Higher-level (global) and lower-level (specific) parameters are contained/described in the final list. The result of this study identifies up to five levels of parameters (within the relevant hierarchy).

The parameters have not yet been statistically tested. The relevance of individual parameters has to be tested with relevant corresponding databases and statistical methods (e.g. correlation and regression).

To manage larger real estate portfolios, there is a need for regular property valuations. From this perspective, there is a great interest related to the optimisation of the valuation costs, valuation quality and valuation duration. Hedonic methods are considered as an efficient way of performing these valuation tasks. However, further suitable models and parameters are needed. The study describes parameters that can be appropriate for the development of relevant models and creates a structured parameters list, providing the technical basis for the latter. This structured parameter list is substantiated by the evaluation of the existing research.

Property values represent a significant asset for the national economy and for the individual wealth/welfare. The development of property value in a national economy is also relevant for politics, economy and society. The use of hedonic methods and the knowledge of important individual parameters can contribute towards assessing and substantiating the effect of political decisions on the value of real estate.

For the first time, a comprehensive and structured analysis on the value of the relevant parameters used in hedonic methods is performed. Thereby a large number of parameters were identified which question the stability of the results in respective individual studies. In addition, the newly developed hierarchy of parameters can serve as the basis for further research.

A quarter of a century has passed since Stonehill and Nathanson (1968) surveyed multinational companies to determine their foreign capital budgeting practices. Since then, research has not only refined its theoretical base on this subject but also expanded the knowledge of actual practices by multinational companies. This article summarizes the findings of major multinational capital budgeting studies for the last 25 years to ascertain whether companies followed theoretically prescribed approaches. Then, it suggests further research to advance the knowledge on this subject.

As Britain's shopping provision becomes increasingly centralised, the small local shop is becoming a rare feature of the retail grocery trade. Dr David A. Kirby examines the results of a pilot survey to discover the attitudes and opinions of failed retailers. He goes on to suggest that there is a real need for efficient and convenient local stores which may require special concessions from the Government, and certainly an injection of entrepreneurial talent, to survive.

This is an excerpt from a paper entitled ‘Some Industrial Applications of Metal Cleaning,’ which formed the chairman's address read before a joint meeting of the London sections of the Society of Chemical Industry and of the Royal Institute of Chemistry.

Discusses criteria for finding a microcosmic town, or group of town, which can provide a reasonable resemblance to the national market. Determines that available information for the setting‐up of test markets in the UK is somewhat unreliable. Describes and analyses exercises in town groupings designed to give more meaningful data. Concludes that the intention here has been to sketch some of the applications of a major breakthrough in numerical taxonomy to certain aspects of market ecology.