Tenant Industry Sector and European Listed Real Estate Performance

Abstract

This paper extends the empirical evidence on the relationship between the performance of public real estate companies (PRECs) and the industrial sector of their tenants. By investigating the performance of a large sample of European real estate firms from 2010 to 2019 and information pertaining to the firms’ tenants, we find that the systematic risk in the tenants’ industry sectors is capitalized in real estate company equity returns. Our results remain robust after correcting for stock beta modifications, tenant sector alpha, tenant anchor effects, and other tenant characteristics. We consider a hypothetical trading strategy that assumes a long position on PRECs whose occupier base is dominated by tenants belonging to riskier sectors, while the trading strategy shortens PRECs whose tenants belong to less risky sectors. The adoption of this strategy yields benchmark-adjusted annual returns of 3.68%.

Keywords:

• Public real estate companies
• listed real estate
• tenants
• industry
• sector
• systematic risk

JEL CODES:

• R33
• G12
• G11

Notes

1 It should be noted that the tenant information has not been collected for Multi-family, Hotel, Speciality, and Self-Storage PRECs. Multifamily property firms, for example, do not disclose tenants due to the fact that they usually do not have any major tenants. Instead, the occupancy structure for these assets is typically characterized by smaller and therefore unreported tenants.

2 A survivor bias should be negligible. Since we only need the tenants’ industry sector, rather than detailed performance data, the information for firms that are not operating today can still be obtained, because we can find such information on the internet. The database Orbis by Bureau van Dijk also provides information on the non-operating firms.

3 Our analysis is based on local currency; however, in order to ease the comparison of PREC market sizes internationally, we denominate market caps in U.S. Dollars.

4 ICB includes 19 supersectors: Oil & Gas, Chemicals, Basic Resources, Construction & Materials, Industrial Goods and Services, Automobiles & Parts, Food & Beverage, Personal & Household Goods, Health Care, Retail, Media, Travel & Leisure, Telecommunications, Utilities, Banks, Insurance, Real Estate, Financial Services, and Technology.

5 Because of the low risk of the public sector, its beta is set to 0. However, in the robustness test, we also drop the tenants from the public sector and the results remain robust.

6 We thank an anonymous reviewer for suggesting this.

7 As an alternative to our base model, we ran a model with different geographic parameters including a geographic diversification measure (${\mathit{HHI}}_{\mathit{Country}}$), a country specific risk variable, and country fixed effects instead of country shares of portfolios. Country specific risk variable is defined as:

$${\beta }_{i,t}^{\mathit{country}}=\sum _{c=1}^C{\omega }_{c.i,t}{\beta }_c$$

Based on the property portfolio of each firm, we calculate the average systematic risk of all countries where the firms’ properties are located. ${\beta }_c$ is the country beta, and ${\omega }_{c.i,t}$ represents the share of properties of firm i in each country at period t. ${\omega }_{c.i,t}$ is calculated as the size of properties located in country c to the total size of properties. The results are similar to the base model and the coefficient for the variable of interest is significantly positive. Detailed results are available upon request.

8 We winsorize the annual return of our sample at the 0.5% level. Nevertheless, our results stay robust without winsorizing. Detailed results are available upon request.

9 Our findings are further strengthened by a series of other robustness tests. As an alternative to ${\mathit{HHI}}_{\mathit{SECTOR}},$ we construct a single tenant sector dummy and an anchor tenant sector variable, similar to the variables SINGLE TENANT and ANCHOR. The significance of our variable of interest remains strongly positive. Detailed results are available upon request.