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1 – 4 of 4This paper aims to investigate the repercussions and impact of corporate real estate on the returns of non-real-estate equities in a time-series setting. While the ownership of…
Abstract
Purpose
This paper aims to investigate the repercussions and impact of corporate real estate on the returns of non-real-estate equities in a time-series setting. While the ownership of real estate constitutes a considerable proportion of most listed firms’ balance sheet, in the existing literature, whether or not the benefits outweigh the risks associated with corporate real estate, is the subject of controversy.
Design/methodology/approach
The role of corporate real estate ownership in the pricing of returns is examined, after taking well-documented systematic risk factors into account. Employing a data sample from 1999 to 2014, the conditions and characteristics faced by firms with distinct levels of corporate real estate holdings are identified and analyzed.
Findings
The findings reveal that corporate real estate intensity indeed serves as a priced determinant in the German stock market. Among other results, the real-estate-specific risk factor shows countercyclical patterns and is particularly relevant for companies within the manufacturing sector.
Practical implications
The findings provide new insights into the interpretation of corporate real estate and expected general equity returns. Thus, the present analysis is of particular interest for investors, as well as the management boards of listed companies.
Originality/value
To the best of the author’s knowledge, this is the first paper to investigate the ownership of corporate real estate as a priced factor for German equities, after accounting for the well-documented systematic risk factors, namely, market (market risk premium), size (small minus big) and book-to-market-ratio (BE/ME) (high minus low).
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Alexander Scholz, Karim Rochdi and Wolfgang Schaefers
The purpose of this paper in this context is to examine the impact of asset liquidity on real estate equity returns, after taking well-documented systematic risk factors into…
Abstract
Purpose
The purpose of this paper in this context is to examine the impact of asset liquidity on real estate equity returns, after taking well-documented systematic risk factors into account. Due to their unique characteristics, real estate equities constitute an inherently low degree of underlying asset liquidity.
Design/methodology/approach
Following the Fama-French time-series regression approach, the authors extend the conventional asset pricing model by a real estate-specific asset liquidity factor (ALF), using a sample of 244 real estate equities.
Findings
The results, based on monthly data for the period 1999-2012, reveal that asset liquidity is a relevant pricing factor which contributes to explaining return variations in real estate equity markets. Accordingly, investors expect a risk premium from listed real estate companies with a low degree of asset liquidity, which is especially the case for companies facing financial constraints and during economic downturns. Furthermore, an investment strategy exploiting differences in the underlying asset liquidity yields considerable average excess returns of upto 8.04 per cent p.a.
Practical implications
Considering the findings presented in this paper, asset liquidity should receive special attention from investors, as well as from the management boards of listed real estate companies. While investors who ignore the magnitude of asset liquidity may systematically misprice real estate equities, management can influence the firm’s cost of capital by adjusting the underlying asset liquidity.
Originality/value
This is the first study to examine the role of an ALF in a real estate asset pricing framework.
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Karim Rochdi and Marian Dietzel
– The purpose of this paper is to investigate whether there is a relationship between asset-specific online search interest and movements in the US REIT market.
Abstract
Purpose
The purpose of this paper is to investigate whether there is a relationship between asset-specific online search interest and movements in the US REIT market.
Design/methodology/approach
The authors collect search volume (SV) data from “Google Trends” for a set of keywords representing the information demand of real estate (equity) investors. On this basis, the authors test hypothetical investment strategies based on changes in internet SV, to anticipate REIT market movements.
Findings
The results reveal that people’s information demand can indeed serve as a successful predictor for the US REIT market. Among other findings, evidence is provided that there is a significant relationship between asset-specific keywords and the US REIT market. Specifically, investment strategies based on weekly changes in Google SV would have outperformed a buy-and-hold strategy (0.1 percent p.a.) for the Morgan Stanley Capital International US REIT Index by a remarkable 15.4 percent p.a. between 2006 and 2013. Furthermore, the authors find that real-estate-related terms are more suitable than rather general, finance-related terms for predicting REIT market movements.
Practical implications
The findings should be of particular interest for REIT market investors, as the established relationships can potentially be utilized to anticipate short-term REIT market movements.
Originality/value
This is the first paper which applies Google search query data to the REIT market.
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The purpose of this study is to analyze the effect of off-balance sheet activities on the credit risk of African banks.
Abstract
Purpose
The purpose of this study is to analyze the effect of off-balance sheet activities on the credit risk of African banks.
Design/methodology/approach
The theory about the relationship between off-balance sheet activities and bank risk was used to construct a conceptual model of the effect of off-balance sheet on credit risk in an African context. The accounting approach is chosen by collecting accounting data extracted from the annual reports of 24 private and conventional African banks during the period 2010–2019. Both statistical and empirical studies are conducted. The statistical study aims to give a description of sample banks in terms of off-balance sheet activities and key financial indicators. The empirical study has the goal of exploring the correlations between, on the one hand, credit risk and, on the other hand, off-balance sheet ratio and control variables (bank- and country-specific variables). This study is based on dynamic panels using the two-step generalized method of moments technique to estimate regressions between credit risk and the explanatory variables.
Findings
The statistical study reveals that sample banks use moderately off-balance sheet activities; most of them use essentially guarantees and letters of credit, have satisfactory financial indicators and are slightly exposed to credit risk. The empirical results from the two-step generalized method of moments technique disclose that off-balance sheet activities have an intensifying effect on the credit risk of African banks. However, the increasing effect can be minimized when African banks use moderately off-balance sheet activities.
Practical implications
Using judiciously off-balance sheet activities does not exacerbate the exposure of African banks to credit risk. Therefore, managers of African banks are recommended to maintain a moderate level of off-balance sheet activities, especially guarantees and letters of credit.
Originality/value
The findings of this study eliminate the opacity about the effect of off-balance sheet activities on credit risk. Moreover, this study fulfills the huge gap in the related literature by completing the scarcity of recent studies, considering all items of the off-balance sheet, focusing on the African context, describing off-balance sheet activities and financial indicators of sample banks due to a statistical study and estimating regressions of dynamic panels between credit risk and both bank-specific and country-specific variables due to a two-step generalized method of moments technique.
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