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Real estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. The purpose of this paper is to investigate how real estate firms use big four auditors to signal quality.

The authors use Swedish firm level data containing all limited liability real estate companies in the country to determine the determinants of big four auditors. The data set consists of 34,306 observations and is analyzed through logit regressions.

The results show that big four companies are primarily contracted by large and mature companies, rather than new firms or firms with volatile financial records, although the latter could be expected to have a large need to signal quality. The authors also find that firms listed on the stock market and firms targeting public use real estate are more inclined to use big four companies.

Real estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. No prior study of this area has been detected.

This study aims to investigate the association of demographic characteristics, market conditions and risk taking with the disposition effect using data on Brazilian individual investors.

This study uses a unique data set with monthly data from June 2007 to February 2017 provided by one of the largest asset management firms in Brazil. This paper computes the proportion of gains realized and the proportion of losses realized to see if investors incur the disposition effect. This paper then performs logistic regressions to verify the association between investors’ disposition effects and demographic and portfolio characteristics. This paper analyses the prevalence of cognitive biases depending on market conditions (bull or bear markets) and include regressions by asset class as robustness checks.

This paper finds evidence that risk averse investors are more prone to the disposition effect, male subjects are less prone to this cognitive bias and age is not associated with the disposition effect. This paper observes that the tendency to incur the disposition effect decreases during bull markets but increases during bear markets. Also, this paper finds that sophisticated investors are more prone to selling winning assets and holding on to losses.

First, paper gains and losses are based on the highest and lowest prices of the month and not on the price at the moment the sale occurred. Second, this paper had access only to end-of-month information, not to actual daily trading records. Third, because the data set relates to individual investors who trade investment funds, this paper cannot determine whether firm size is associated with the disposition effect. Fourth, age may not necessarily be a proxy for investor experience, so one should interpret the lack of significance for age in terms of generational differences.

This paper demonstrates that the disposition effect is prevalent even among wealthier and more educated investors with delegated asset classes. This paper also presents evidence on the association between demographic characteristics and cognitive biases considering a liquidity-constrained, highly volatile and developing market.

This paper demonstrates that gender is an important characteristic to understand cognitive biases and that investor sophistication may not necessarily be an attenuation factor for the disposition effect in a liquidity-constrained market.

This is the first study to analyse the role of demographic characteristics and risk taking to explain the disposition effect using real information at the individual level about Brazilian investors. It is also the first to analyse the intensity of cognitive biases during bull and bear markets in the Brazilian economy.

This paper start from the question that value of right which is arose from real asset trade. First, organizing option portfolio using this right, then we investigate the correlation about real assets and contracted prices. The results are as follows. When a market is in equilibrium, the call-option value which is owned by seller is greater than the put-option value which is owned by buyer. As a result, present value of contract price is lower than the true value of the asset. Furthermore, this phenomenon is getting deepen when volatility of real estate is greater, expiration date is longer and interest rate is higher.

The application of smart contract can greatly reduce transaction costs and improve transaction efficiency. The existing smart contract are expensive, single application scenario and inefficient. This paper aims to propose a new smart contract model to solve these problems.

By investigating the research history, models and platforms, this paper summarizes the shortcomings of existing smart contracts. Based on the content and architecture of traditional contract, a smart contract model with wider application scope is designed.

In this paper, several models are used to describe the operation mechanism of smart contracts. To facilitate computer execution, a decomposition method is proposed, which divides smart contracts into several sub-contracts. Then, the advantages and deployment methods of smart contract are discussed. On this basis, a specific example is given to illustrate how the application of smart contract will change our life.

Smart contract is gradually applied to more fields. In this paper, the structure and operation mechanism of smart contract system in reality are given, which will be beneficial to the application of smart contract to more complex systems.

The purpose of this study is to identify the key data categories and characteristics defined by asset information requirements (AIR) and how this affects the development and maintenance of an asset information model (AIM) for a blockchain-based digital twin (DT).

A mixed-method approach involving qualitative and quantitative analysis was used to gather empirical data through semistructured interviews and a digital questionnaire survey with an emphasis on AIR for blockchain-based DTs from a data-driven predictive analytics perspective.

Based on the analysis of results three key data categories were identified, core data, static operation and maintenance (OM) data, and dynamic OM data, along with the data characteristics required to perform data-driven predictive analytics through artificial intelligence (AI) in a blockchain-based DT platform. The findings also include how the creation and maintenance of an AIM is affected in this context.

The key data categories and characteristics specified through AIR to support predictive data-driven analytics through AI in a blockchain-based DT will contribute to the development and maintenance of an AIM.

The research explores the process of defining, delivering and maintaining the AIM and the potential use of blockchain technology (BCT) as a facilitator for data trust, integrity and security.

This paper aims to propose a liquidity management solution for Islamic financial institutions (IFIs) that concurs with sustainable development and financial stability.

The study is a qualitative research. It uses the exploratory research methodology, specifically the content analysis approach, to gather primary data and identify and interpret relevant secondary data and Sharīʿah concepts. The purpose is to develop a liquidity management solution for IFIs. The proposal is based on the Unleveraged Green Investment Trust (UGIT) model, which is consistent with Basel III regulatory requirements. In developing the UGIT model, the exploratory research was complemented by a case study to examine the UGIT solution for the particular case of renewable energy.

The model demonstrates how financial innovation can meet both financial stability and sustainable development objectives, thereby achieving the spirit of Islamic finance. The structure further highlights the importance of regulatory and fiscal frameworks to enhance liquidity management and investor appeal for green financial instruments.

This study suggests a structure of UGIT to enable IFIs to meet their liquidity management needs while promoting sustainable development.