Futures markets and real estate public equity: Connectivity of lumber futures and Timber REITs

Clements, Sherwood; Tidwell, Alan; Jin, Changha

doi:10.1016/j.jfe.2017.06.003

Cited by 6 publications

(7 citation statements)

References 33 publications

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“…Similarly Lee et al (2014) conclude that European RES futures contracts are effective hedging instruments (with a variance reduction of 64%) for the underlying assets. Furthermore Zhou (2016) corroborates the effectiveness of REIT futures contracts by documenting their efficacy in hedging REITs in Australia, Europe, Japan and Australia (see also Zhou, 2017;and Clements et al, 2017).…”

Section: Introductionsupporting

confidence: 52%

Cross Hedging Effectiveness of Real Estate Securities Exchange Traded Funds

Addae‐Dapaah

Abdullah²

2020

Journal of Real Estate Portfolio Management

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The analyses cover different full sample periods from 2000 to 2010 inclusive, the global financial crisis (GFC) period and four phases of the GFC depending on data availability to document the performances of the hedge during times of high and low volatility. The results show that the real estate ETFs were very effective in hedging EREIT and all the sampled real estate securities in Europe and Asia. Secondly, VECM hedge marginally outperformed OLS hedge when the ETFs and the real estate securities returns were cointegrated. Thirdly, we find that hedging effectiveness evidenced by variance reduction does not necessarily equate to economic viability. Therefore it is advisable to use VR and UIs together to determine viability of hedging effectiveness. Finally, given different levels of risk aversion vis-à-vis expected utility, it was, and therefore may be concluded that it could be, advisable/inadvisable to use the ETFs to hedge during periods of high/low volatility.

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Section: Introductionsupporting

confidence: 52%

Cross Hedging Effectiveness of Real Estate Securities Exchange Traded Funds

Addae‐Dapaah

Abdullah²

2020

Journal of Real Estate Portfolio Management

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“…Other more recent work has included investigations on foreign buyers' impacts on cap rates (McAllister and Nanda, 2016) and analysis of the cointegration between lumber futures and timber land value (Clements et al , 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

The determinants of capitalisation rates: evidence from the US real estate markets

Larriva¹,

Linneman²

2021

JPIF

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PurposeEstablishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalization rates in both the US office and multifamily sectors.Design/methodology/approachThe authors specifies a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.FindingsUsing a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.Practical implicationsThis has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.Originality/valueThis study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).

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“…4 Juselius (2006) recommends this binary variable-based procedure, which focuses on achievement of Haavelmo's (1944) well-known conditions that use "statistical devices" that clear the data of extraneous exogenous effects not of direct theoretical Following Juselius (2006), an event that occurred over short-run subsamples was considered potentially extraordinary if its standardized residual exceeded 3.0 in absolute value. We followed recent procedures applied by Clements, Tidwell, and Jin (2017) and designed this rule on the effective sample size of T observations (126 observations in our analysis) using the Bonferoni criterion programed in Estima (RATS package, Version 8.2): INVNORMAL(1 − 1.025) T . INVNORMAL is a function for the normal distribution that returns the variable for the cumulative density function as a standard normal distribution and suggested that the absolute value of the Bonferoni value was 3.54.…”

mentioning

confidence: 99%

“…INVNORMAL is a function for the normal distribution that returns the variable for the cumulative density function as a standard normal distribution and suggested that the absolute value of the Bonferoni value was 3.54. Following Clements, Tidwell, and Jin (2017), having seen that there were some short-term events with potentially extraordinary effects with absolute standardized residuals that fell between 3.0 and 3.54, we chose a more conservative absolute value criterion of 3.0 rather than 3.54. Four short-run binary variables were specified and are herein identified by the defining event dates for which they take unity values (zero otherwise), and they were then included in differenced form in the short-run component of equation (1).…”

mentioning

confidence: 99%

See 1 more Smart Citation

A Methodology to Empirically Assess National and Farm-Specific Damages from Contamination of Grain Supply by a Genetically Engineered Strain

Capps

Babula

2019

J. Agric. Appl. Econ.

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On May 29, 2013, the U.S. government announced that contamination of non–genetically engineered wheat supplies occurred. We provide a methodology to empirically assess the impacts of this contamination event on national prices and on farm-specific prices and receipts for spring red hard wheat. Results suggest that U.S. spring red hard wheat farmers in the aggregate had lost receipts ranging from $32.77 million to $131.06 million and incurred a drop of 3.83% in wheat price equivalent to $0.27 per bushel. At the farm level, a hypothetical farmer received $0.31 less per bushel culminating in $4,807 in lost receipts.

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Futures markets and real estate public equity: Connectivity of lumber futures and Timber REITs

Cited by 6 publications

References 33 publications

Cross Hedging Effectiveness of Real Estate Securities Exchange Traded Funds

Cross Hedging Effectiveness of Real Estate Securities Exchange Traded Funds

The determinants of capitalisation rates: evidence from the US real estate markets

A Methodology to Empirically Assess National and Farm-Specific Damages from Contamination of Grain Supply by a Genetically Engineered Strain

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