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i. Introduction
a. Objective of the Study
b. Rationale of the Study
c. Statement of the Research Questions
d. Limitations of the Study
ii. Literature Review
a. Terminology
b. Review of Previous Studies
c. Comments and Criticisms
iii. Methodology
a. Data Collection and Period
b. Tools of analysis Rationale for each
iv. Data Presentation Technique
v. Analytical Results, Discussions & Suggestions
vi. Conclusions
vii. References
i. Introduction
Understanding the return-risk in the real estate market is aided by intensive research to develop concepts that are logical and applicable in the real estate business. The studies done with respect to the risk in the real estate markets are the gateways to the comprehension of the operations and influence of the risks on the development of the business. There is a correlation between returns and risks in real estate. The two aspects are divided into several categories to apply to the different real estate ownership practices. The industry has different types of property, and each has its risks and returns that should be considered individually. Some of the general return-risks that affect the real estate markets include business risk, liquidity problems, financial challenges, and inflation risk. Other issues in the real estate market include variance risk that is related to the mentioned problems, considering it is based on the variability of the equity expected from the real estate market in terms of returns. Studies indicate that the risks and returns on equity of the real estate are influenced largely by the relationship between returns and risks. The real estate market, according to the studies, is vibrant and requires the understanding of the return-risk analysis for investors and owners of the property to ensure that markets remain reasonable and enticing for the buyer.
a. Objectives of the Research
The main purpose of the research is to investigate the return-risk analysis of real estate markets. It aims to explore the influence of the correlation of returns and risks to show the influence factors in the real estate market.
b. Rationale of the Study
The current study is justified because it highlights the effect of return-risk correlation on the real estate market in terms of equity. The research allows potential real estate investors to understand the market dynamics. The research highlights the effect of the value of equity on the market has on the risk and returns expected. It will advise individuals or companies in the real estate industry on the logical actions to take in the investment area. The research underwrites previous studies on the subject and offers insight to how the real estate market is emerging with respect to return-risk analysis of the market.
c. Statement of the Research Questions
Considering that the goal of the paper is to analyze the return-risk of the real estate market, the research provokes several questions that guide the study. They include
i. How does return and risk correlate to influence the real estate market?
ii. Does the amount of investment affect the return and risk on the residual equity?
iii. Is the return of investment in real estate worth the risks involved?
d. Limitations of the Study
An analysis of the real estate market requires investment of resources that help navigate through the information curve without hindrances. However, the limited resources made it difficult to acquire sufficient information. The amount of information used was not adequate to make a satisfactory general conclusion of the analysis. Another limitation of the study is that the real estate market is cyclical and it is difficult to discern the phase of the market, making it difficult to analyze the returns and risks effectively. The two elements of the real estate market are leasing and investing. However, the information available on the real estate market does not provide a distinction of the two elements.
ii. Literature Review
Section I: Operational definition of terms and concepts
Residual equity is a theory that posits that shared assets have great influence on the market.
Returns are the revenues from an investment.
Inflation risk is the chance that cash flows from an investment will drop in value as changes in purchasing power occur in the market.
Variance risk is an occurrence where the purchaser of variance loses on the trade, while the broker profits.
Risk is the improbability of a profit and the possibility for economic loss.
Liquidity risk is the risk, where an asset cannot be traded hastily in the market to evade a loss.
Business risk infers insecurity in profits due to the unexpected happenings in the future of a business.
Section II: Review of peer-reviewed journal articles
Return-risk of real estate market has been a subject of research across the globe. Some viewed the risks with respect to returns and how they affect the market. Others explored how different risks influence real estate investments and the returns earned from the funds.
The US News and World Report posit that real estate is the best asset class to invest in compared to others opportunities. The conclusion is based on the lucrative returns compared to lower risks of the real estate market in the US. McFarland (2015, p.1) in the article Why Real Estate could be a better Investment than Stocks analyses the risk versus returns in the real estate market and suggests that risk is limited to initial investment into the market. The author explains that real estate risks are difficult to quantify; and therefore, data on prices, single stock and index fund are significant factors to consider. Investors that are looking for high returns could evaluate index funds that guarantee high return in the real estate market. The risks incurred in index fund investment are reasonable compared to single stock investment. Therefore, it makes sense to invest in the market through index fund.
Similarly, Sagi (2015, p.3) in his research Asset-Level Risk and Return on Real Estate Investment implies that the risk in real estate markets is directly proportional to investment. Through using the illiquidity asset and holding period returns the author explains how the rigidity of the real estate market influences the risks and returns. He further asserts that the holding period price appreciation in the real estate market increases at the individual property level. The conclusion suggests that owning a property at an individual level yields returns to an extent that the risks involved are considered null. The illiquidity of asset in real estate is explained by a risk that could generate significant outcomes. However, according to Sagi (2015, p.12), the period that the asset is illiquid can help the owner renovate and present the property with new price quotations in the market, leading to high returns.
On the other hand, Theobald and his colleagues (2010, p.1) in the thesis on Risk and Return on Real Estate Investment Trusts in the US, Australia and France explores how different risk factors affect real estate markets. The article focuses on variability of the market and the inflation risk as some of the major factors in real estate. The inflation affects gross income that has a direct impact on the property acquisition rate. Inflation also influences interest rates, which are crucial in real estate. Theobald and his colleagues (2015, p.26) insist that the variance in the return of investment in real estate is determined by the risk. The returns earned for the three countries explored show that variance risk is instrumental in the overall return on real estate investment trusts.
In the same context, (Ross & Zisler 1991, p.175) in their research Risk and Return in Real Estate discover that residual equity influence the risk and return in the real estate market. The researchers explain that the equity in the real estate is volatile, which leads to overstatement of the risks involved. They continue to state that the fluctuation of the price indexes in the market is a risk on the returns on investment. Their conclusion is that the real estate market is influenced business risks that are unpredictable (Ross and Zisler 1991, p.186). Moreover, the risks involved change the market price of the property, making investment decisions difficult. Slight change in the market creates a risk that could either be negatively or positively significant to the return on investment in the real estate industry.
Section III: Summary, Comments and Criticisms
The investigations on the return-risk of real estate markets reveal different results. According to McFarland (2015) and Sagi (2015), return-risk of real estate market is explained through comparison per investment. They both assert that risks are directly proportional to returns, since the value invested attracts a risk that influences the performance of the property in the market and consequently return generated from its sale or lease. Theobald (2010), Ross and Zisler (1991) explain that there are different types of risks associated with real estate markets. They elaborate that variance, inflation, business, and liquidity risks determine the return generated from investment. Their conclusions reveal that they have an understanding of the different risks and how they affect different real estate investment practices. The risks for individual ownership are different from shared property in real estate markets. Furthermore, they agree that the variability of property ownership applies to all property types in the market.
In my opinion, the different results on return-risk analysis of real estate market are achieved because the researchers have dissimilar focal points in their investigations. The researchers that conclude that risk and returns are directly proportional focus on the general risk and return on investment, while the ones that assert that risks are individual for different types of investment focus on several risks and the two common types of investment. McFarland (2015) and Sagi (2015) generalized the research restricting their information that the risk correlation to return in the real estate market is presented as one entity. The researchers do not break down the risks that exist in the market. They look at the analysis from a generalized point of view. On the other hand, Theobald (2010), Ross and Zisler (1991) base their research on a wide view of the topic. They explore specific risks and their influence on returns in the market. They also highlight the different types of investment and how they contribute to risks that consequently affect returns. Their explanation of the returns-risk analysis of the real estate market is vast and detailed.
iii. Methodology
To study the return-risk analysis of real estate markets, several data is compared to give a comprehensive analysis of the investigation. In the following part of the paper, the risks of investment are examined from a general point of view, and specifically with respect to returns earned in each case.
a. Sampling and Data Collection Methods
In the research, secondary methods of gathering information are used to propel the study. The samples used in the project are drawn from different sources that include the National Association of Real Estate Investment Trusts (NAREITs) and the National Council for Real Estate Investment Fiduciaries (NCREIF). Other samples are derived from the housing prices dated 1900 to 2010. The wide range of years allows for a detailed analysis given that the real estate market is volatile.
b. Tools of Analysis Rationale for each
To study the return-risk of real estate markets, a t-STAT and P-value analysis of the data collected were conducted. The p-value is crucial for validity, since it indicates the mean of returns in the presence of risk. The p-value is generated from the t-STAT as its variance. From the generation of the p-value, the price indexes for each year are plotted on a graph against the year to indicate the changes in the real estate market. A graph showing how inflation risk influences real estate in terms of prices and thereby, return is displayed to show the adjustment.
iv. Data Presentation Technique
The study on return-risk analysis of real estate market presents the data by explaining the data axes. The data is illustrated by graphs, which have x and y variables that are explained during the presentation.
Table (1) and (2) below shows the (T-test) conducted for the US real estate and the P-value resulted for the period studied.
NCREIF Property Index Returns
Year |
Quarter 1 |
Quarter 2 |
Quarter 3 |
Quarter 4 |
1978 |
2.9% |
3.07% |
3.39% |
5.89% |
1979 |
3.81% |
4.32% |
4.75% |
6.19% |
1980 |
5.54% |
2.36% |
3.79% |
5.32% |
1981 |
2.96% |
4.23% |
3.21% |
5.29% |
1982 |
2.49% |
2.07% |
1.52% |
3.04% |
1983 |
1.75% |
2.54% |
2.96% |
5.31% |
1984 |
3.35% |
3.16% |
2.46% |
4.21% |
1985 |
2.08% |
2.6% |
2.39% |
3.73% |
1986 |
2.03% |
1.96% |
1.5% |
2.57% |
1987 |
1.83% |
1.19% |
2.09% |
2.67% |
1988 |
1.84% |
2% |
2.39% |
3.07% |
1989 |
1.75% |
2% |
2.05% |
1.75% |
1990 |
1.38% |
1.52% |
.84% |
-1.43% |
1991 |
.05% |
.01% |
-.33% |
-5.33% |
1992 |
-.03% |
-1.03% |
-.44% |
-2.81% |
1993 |
.77% |
-.24% |
1.1% |
-.25% |
1994 |
1.31% |
1.54% |
1.51% |
1.88% |
1995 |
2.11% |
2.08% |
2.06% |
1.09% |
1996 |
2.4% |
2.29% |
2.63% |
2.61% |
1997 |
2.34% |
2.82% |
3.38% |
4.71% |
1998 |
4.14% |
4.19% |
3.46% |
3.55% |
1999 |
2.59% |
2.62% |
2.81% |
2.89% |
2000 |
2.4% |
3.05% |
2.94% |
3.33% |
2001 |
2.36% |
2.47% |
1.6% |
.67% |
2002 |
1.51% |
1.61% |
1.79% |
1.67% |
2003 |
1.88% |
2.09% |
1.97% |
2.76% |
2004 |
2.56% |
3.13% |
3.42% |
4.66% |
2005 |
3.51% |
5.34% |
4.44% |
5.43% |
2006 |
3.62% |
4.01% |
3.51% |
4.51% |
2007 |
3.62% |
4.59% |
3.56% |
3.21% |
2008 |
1.6% |
.56% |
-.17% |
-8.29% |
2009 |
-7.33% |
-5.2% |
-3.32% |
-2.11% |
2010 |
.76% |
3.31% |
3.86% |
4.62% |
2011 |
3.36% |
3. 94% |
3.3% |
2.96% |
2012 |
2.59% |
2.68% |
2.34% |
2.54% |
2013 |
2.57% |
2.87% |
2.59% |
2.53% |
2014 |
2.74% |
2.91% |
2.63% |
3.04% |
2015 |
3.57% |
3.14% |
3.09% |
– |
Source:
FTSE NAREIT U.S. Real Estate Index
FTSE NAREIT U.S. Real Estate Index |
Value |
% Change |
All REITs |
187.34 |
0.81% |
Composite |
182.82 |
0.81% |
All Equity REITs |
624.00 |
0.78% |
Industrial / Office |
280.17 |
0.75% |
Industrial |
204.24 |
0.79% |
Office |
327.75 |
0.66% |
Mixed |
168.64 |
1.07% |
Retail |
324.55 |
0.92% |
Shopping Centers |
241.23 |
1.09% |
Regional Malls |
477.59 |
0.81% |
Free Standing |
315.30 |
0.94% |
Residential |
382.76 |
1.05% |
Apartments |
386.28 |
1.05% |
Manufactured Homes |
165.09 |
0.45% |
Diversified |
298.88 |
1.02% |
Lodging/Resorts |
382.76 |
1.05% |
Health Care |
98.10 |
0.73% |
Self-Storage |
1,259.06 |
0.67% |
Timber |
151.64 |
0.49% |
Infrastructure |
159.75 |
0.28% |
Equity REITs |
619.06 |
0.84% |
Real Estate 50 |
273.52 |
0.76% |
Mortgage REITs |
4.90 |
1.23% |
Home Financing |
48.63 |
1.24% |
Commercial Financing |
22.01 |
1.14% |
FTSE RAFI US 100 Real Estate Index |
4,596.73 |
0.78% |
Source:
The following graphs represent the influence of inflation on house prices and housing price index since 1900 to 2010 respectively.
v. Presentation of Data, Analysis and Discussion of Results
Understanding the history of real estate markets in the US is a crucial aspect of the analysis and consequently, the research (Greer & Kolbe 2003). The data is presented in graphs, since it is easy for the researcher to explain the findings through variables and how x axis variables affect y axis variables and vice versa. The data collected has a set of t-stat values that are calculated to generate the p-value to represent the return in the real estate market with respect to risks (Sirota 2004). The T-stat and p-values are used to show the justification of the thesis of the research. The p-value proves the thesis when it is at 0.05%. The 0.05% is a standard measuring value, and as such, the hypothesis is proven. The real estate indexes presented by NAREIT are over 0.05% value with the exception of manufactured houses, infrastructure and timber. The real estate indexes for the former are 0.45%, 0.28% and 0.49% respectively. The highest price index recorded from 1900 to 2010 was at 180% in 180. Considering data from NAREIT and NCREIF, price indexes fluctuate over the years. According to NCREIF the highest returns realized in the real estate market was in 1978 and 1979 with 5.89% and 6.19% respectively. In NAREIT, the FTSE RAFI US 100 Real Estate Index value was recorded as 4,596.73 (Imperiale 2006). A graph showing the risk of inflation and how it adjusts housing prices depicts that inflation negatively influences returns since the inflation affects income (Frankel 2015). The changes in the numbers reflect the returns earned in the market, suggesting that the risk value is subdued by the returns earned in the real estate market (Imperiale 2006).
vi. Summary and Conclusion
Return-risk analysis of real estate markets is vital for investors and owners of real estate. The research offers insight to how the returns are affected by the risks in the market. The literature reviewed is based on acquired data that has focused on the subject of research. The research materials used have different views of the return-risk analysis of real estate markets. The method of data collection used is secondary and the materials are reviewed to measure their relevance to the research. Data is presented in graphs explaining the variables on the x and y axes. Risks influence returns and the real estate market is affected by specific risks affecting specific real estate types of ownership.