Do Different Price Points Exhibit Different Investment Risk and Return Commercial Real Estate

Geltner, David; Minne, Alex Van de

doi:10.2139/ssrn.2906955

Cited by 5 publications

(4 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From our results, we find that investors with little prior exposure in a market tend to purchase properties that are larger, green certified, high Q score, closer to the CBD and of low age. These properties are arguably more informationally efficient (Geltner and van de Minne 2017), and tend to be "safer"/core investments. This could also explain partly why larger investors tend to go with these larger properties.…”

Section: Robustness: Frailty and Prior Exposurementioning

confidence: 99%

See 1 more Smart Citation

Preferences of Institutional Investors in Commercial Real Estate

Cvijanović

Milcheva

Minne

2021

J Real Estate Finan Econ

View full text Add to dashboard Cite

In this paper we analyze market segmentation by firm size in the commercial real estate transaction process. Using novel micro-level data, we look at the probability distribution of investors acquiring a specific bundle of real estate characteristics, distinguishing between investors based on the size of their real estate portfolio. We find evidence of market segmentation by investor size: institutional investors segment across property characteristics based on the size of their real estate portfolio. The probability that a large (small) seller will sell a property to a similar-sized buyer is higher, keeping all else equal. We explore potential drivers of this market segmentation and find that it is mainly driven by investor preferences. During the Global Financial Crisis (GFC), large investors were less likely to buy the ‘average’ property, as compared to the period before or after the crisis, indicating time-varying investor preferences.

show abstract

Section: Robustness: Frailty and Prior Exposurementioning

confidence: 99%

“…This can result in market segmentation in commercial real estate markets. Some preliminary evidence by Geltner and van de Minne (2017) and Cvijanović et al (2020) suggests that the law of one price may be violated with different investors paying different prices for a comparable property.…”

Section: Introductionmentioning

confidence: 99%

Preferences of Institutional Investors in Commercial Real Estate

Cvijanović

Milcheva

Minne

2021

J Real Estate Finan Econ

View full text Add to dashboard Cite

show abstract

“…Finance theory argues that the price of assets traded in relatively frictionless markets reflect estimated risk-adjusted discount rates and future income streams (Geltner and van de Minne, 2017). The key macroeconomic and financial fundamentals underpinning the theoretical context of this paper relate to the interrelationship between yields, pricing, market sentiment and risk analysis in the property investment process.…”

Section: Literature Reviewmentioning

confidence: 99%

Pricing risk and its use in modelling real estate market yields

McGough

Berry

2020

JPIF

View full text Add to dashboard Cite

Purpose In the light of past financial and economic turmoil, there has been a marked increase in the volatility in real estate markets. This has impacted on the pricing of property assets, partly through market sentiment and particularly concerning risk. It also limits modelling accuracy model accuracy. The purpose of this paper is to create a new variable and model to enhance analysis of what drives real estate yields incorporating market sentiment to risk. Design/methodology/approach This paper specifically considers the modelling of property pricing within a volatile economic environment. The theoretical context begins by analysing the relationship between property yields and government bonds. The analytical context then moves on to specifically include a measurement of risk which stresses its role and importance in investment markets since the Global Financial Crisis. The model thus incorporates macroeconomic and real estate data, together with an international risk multiplier, which is calculated within the paper. Findings The paper finds the use of measurements of market sentiment and risk are more powerful tools for modelling yields than previous techniques alone. Research limitations/implications This is an initial paper outlining the creation of sentiment and risk measurements in the financial market and showing an example of its application to a commercial real estate market. The implication is that this could add a major new explanatory variable to modelling of yields. Practical implications The paper highlights the importance of risk in the pricing of commercial real estate, over and above normal variables. It highlights how this can help explain over and undershooting of yields within commercial real estate which would be of great importance in the investment world. Originality/value This paper attempts to explicitly measure market sentiment, pricing of risk and how this impacts real estate pricing.

show abstract

“…Price dynamics and yields affect investment risk and return (Geltner & Van De Minne, 2017), which are often evaluated using regression statistics (Barak et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Brazil nuts a non-timber potential: Uncertainties and investments

Rêgo

Soares

Isbaex

et al. 2021

RSD

View full text Add to dashboard Cite

The Brazil nut is one of the main non-timber forest products in Brazil, but its price fluctuations generate uncertainties and risks for both extractivists and investors. Econometric models or other simpler methods can estimate price changes and indicate the investment attractiveness of the Brazil nut. The objective of the present study was to analyze the risk-return relationship and the export price for both volatility of the Brazil nut over a 15 years period. The historical series of Brazil nut export prices, shelled and unshelled nuts, was evaluated from 2002 to 2016. The geometric growth rate and the variation coefficient indicate the return and risk respectively, associated with its price series. The price volatility of shelled and unshelled Brazil nuts was estimated with the standard deviation of the price series and with generalized models of ARCH (GARCH, EGARCH and TARCH). The shelled or unshelled Brazil nut coefficient increased over 15 years, with a low risk-return ratio. The shelled Brazil nut volatility was lower in the 2002 to 2006, 2007 to 2011 and 2012 to 2016 periods than for the unshelled nut when estimated by the standard deviation method than for the unshelled nut. The shelled Brazil nut price was higher from 2002 to 2016, with low volatility and persistent shocks. The estimate of the shelled and unshelled Brazil nut price volatility was better with the TARCH and the EGARCH models, respectively.

show abstract

Do Different Price Points Exhibit Different Investment Risk and Return Commercial Real Estate

Cited by 5 publications

References 27 publications

Preferences of Institutional Investors in Commercial Real Estate

Preferences of Institutional Investors in Commercial Real Estate

Pricing risk and its use in modelling real estate market yields

Brazil nuts a non-timber potential: Uncertainties and investments

Contact Info

Product

Resources

About