Department of Business Administration Bachelor of Business and Economics Degree Project, 15 Credits, Spring 2020
Diversification benefits and
risks of real estate investments
in a mixed-asset portfolio
A study concentrating on theHelsinki area
Abstract
This thesis investigates the diversification benefits of real estate in a mixed-asset portfolio within the Helsinki area. The object is to find out whether including direct residential real estate in an investment portfolio reduces the volatility and thus the risk of the portfolio, while enhancing the risk-adjusted return. The authors also aim to construct an optimal portfolio, maximizing the Sharpe ratio. In addition, the study focuses on introducing the risks regarding real estate investing and ways to control them. The study was conducted as a quantitative research and the empirical part of the study was carried out by analysing the returns and volatility of the residential real estate, OMXH25 stock index and Finnish long-term government bonds during the time period of 2010-2018. In addition, the different risks of real estate investing, including economical, rental and other less controllable risks, were scrutinised.
In Finland, the number of residential real estate investments has grown by 40% since the financial crisis started in 2008. (Suomen Hypoteekkiyhdistys, 2018) The increasing popularity results from the volatile stock returns and from the low interest rates that has allured household investors to take advantage of the leverage. Moreover, the continued urbanisation and the trend of decreasing household sizes has pushed the demand of the apartments, increasing the prices.
TABLE OF CONTENTS
1 INTRODUCTION ... 1 1.1 BACKGROUND ... 1 1.2 PROBLEMATISATION ... 2 1.3 RESEARCH QUESTIONS ... 3 1.4 RESEARCH PURPOSE ... 3 1.5 CONTRIBUTION ... 3 1.6 DELIMITATIONS ... 4 1.7 DISPOSITION ... 4 2 METHODOLOGY ... 6 2.1 RESEARCH PHILOSOPHY... 6 2.1.1 Ontology ... 6 2.1.2 Epistemology ... 62.2 RESEARCH STRATEGY AND METHODOLOGICAL CHOICE... 7
2.3 RESEARCH APPROACH ... 7
2.4 RESEARCH DESIGN ... 8
2.5 LITERATURE SEARCH AND SOURCE CRITICISM ... 9
2.6 ETHICAL CONSIDERATIONS ... 9
3 FINANCIAL INSTRUMENTS ... 11
3.1 STOCKS AS INVESTMENTS ... 11
3.2 BONDS AS INVESTMENTS ... 12
3.3 REAL ESTATES AS INVESTMENTS ... 13
4 THEORETICAL FRAMEWORK... 15
4.1 LITERATURE REVIEW ... 15
4.2 RISK, RETURN AND DIVERSIFICATION ... 17
4.3 MODERN PORTFOLIO THEORY ... 18
4.4 RISKS IN DIRECT REAL ESTATE INVESTING ... 19
4.4.1 Economic risks ... 19
4.4.2 Risks in renting ... 20
4.4.3 Other risks ... 21
5 DESCRIPTION OF THE DATA ... 23
5.1 DATA ON REAL ESTATE ... 23
5.2 DATA ON FINANCIAL INSTRUMENTS ... 26
6 RESEARCH METHODS ... 29
6.1 CALCULATING THE RETURN ... 29
6.2 CALCULATING RISK AND VOLATILITY ... 29
6.3 CALCULATING COVARIANCE AND CORRELATION ... 30
6.4 SHARPE RATIO AS A MEASURE OF PERFORMANCE ... 30
7 RESULTS AND ANALYSIS ... 32
7.1 DESCRIPTIVE STATISTICS ... 32
7.2 CORRELATION BETWEEN THE RETURNS ... 33
8 CONCLUSION ... 37 8.1 FUTURE STUDIES ... 38 8.2 QUALITY CRITERIA ... 39 8.2.1 Reliability ... 39 8.2.2 Validity ... 40 9 REFERENCE LIST ... 41
List of figures
Figure 1. Process of deduction ... 8Figure 2. Diversification effect... 17
Figure 3. Efficient frontier ... 19
Figure 4. Price index of old dwellings 2010=100 ... 24
Figure 5. Price development of old dwellings ... 24
Figure 6. Rent index 2010=100 ... 25
Figure 7. Rent price development ... 25
Figure 8. Index price performance ... 26
Figure 9. Annual averages of long-term government bond yields ... 27
Figure 10. Development of 12-month Euribor rates ... 27
Figure 11. Portfolio frontier ... 35
List of tables
Table 1. Annual return percentages during years 2010-2018... 32Table 2. Correlation of the returns ... 33
1 Introduction
This chapter begins with introducing the topic and providing a background to the study. Thereafter, the research question and aim of the research are defined. The introduction also includes specifying the structure, content and the delimitations of the study.
1.1 Background
During the past years real estate investing has become increasingly popular in Finland. The volatility of the stock returns and the historically low interest rates after the
financial crisis started in 2008 and the European debt crisis have been among the main factors boosting the growth of the residential real estate investment markets in Finland (Suomen Hypoteekkiyhdistys, 2018; Alho et al, 2018). The uncertainty regarding stock returns has caused some investors to search for alternative investment classes, where real estate seems to be an attractive option.
Real estate can be considered a fairly low risk investment asset with a steady return, but also expensive and time-taking. Many can associate real estate with illiquidity and requiring a high initial investment. Usually the individual household investor needs to put some effort to become familiar with the aspects of the apartment and become aware of the risks related. These matters decrease the number of real estate investors in the market and may allow individuals to receive higher returns than the market price i.e. the real estate market is inefficient (Orava & Turunen, 2016). Hudson-Wilson et al in their article “Why real estate?” (2005) provide numerous reasons of why real estate should be part of the efficient investment portfolio. They name low and negative correlation between other financial assets, good return and risk relation compared to other asset classes and real estate being a hedge against unexpected inflation or deflation. Lastly, they mention the steady cash flows received from rents. These factors make investing in real estate attractive, especially considering the turbulent times at stock market caused by the recent developments of COVID-19.
Two growing trends have been distinct during the previous years in Finland;
urbanisation and decreasing household size. According to KTI, the population growth in Helsinki area has been the fastest growing of Finland and is expected continue being that way. Furthermore, the household size has been steadily growing smaller in Finland. In 1985, the share of a single households accounted for about 28%. In 2017 the
percentage had grown to about 44%. In the larger cities, the household sizes tend to be smaller and in Helsinki the percentage of single households is approximately 48% (KTI, 2019).
survey called ‘’Emerging Trends in Real Estate’’ in the European markets. The survey assesses the most attractive property markets in Europe. Helsinki is placed on the 8th
place in the survey with the investment prospects said to be good in 2019 (PwC & The Urban Land Institute, 2018).
1.2 Problematisation
The previous studies in Finland regarding the subject of direct residential real estate investing were set in the earlier years of the 21st century and around the years of the financial crisis in 2008. These studies mainly concentrate on Finland as a whole. Kuosmanen studied the optimal allocation percentages of the different assets and the diversification effect provided by real estate investments around the whole of Finland in 2002. Oikarinen in 2007 concentrated on the price developments between stocks, bonds and real estate in Finland and looked into the portfolio diversification in the Helsinki area. An important thing to notice is that the above-mentioned studies have not taken into account the rental payments, that can be regarded as the dividends of the real estate investments. Falkenbach (2009) on the other hand looked into the commercial real estate in Finland and the correlations as well as the diversification effects of having different assets in the portfolio.
However, the financial crisis in 2008 affected the financial markets and especially the real estate markets. The impact of the low interest rates has caused an increase in residential real estate investing in Finland and thus a more up-to-date study regarding the real estate returns and the potential diversification effects provided by the real estate investments is needed. With this type of investing increasing in popularity, an analysis of the risks related is needed.
In addition, the demographics of Finland are changing constantly, as more and more people are wanting to live closer to big cities with better services. Moreover, the number of university students has steadily grown during the years 2009 to 2018, (Tilastokeskus, n.d.) The students usually live in smaller apartments in apartment houses, thereby increasing the demand for them. Due to these changes in the economy of Finland, the authors consider the research to be relevant.
Though studies in this field have been made in other areas of the world, the results of those studies may not be directly generalisable and comparable to the Helsinki area, as real estate and financial markets are unique. Hoesli and Hamelink (2002) committed a study within the same field, while concentrating on the markets in Geneva. The
variables they used included Swiss real estate, bonds and stocks. Similarly, Kallberg et al (1996) study used the U.S. variables while for Lee (2002) the setting of the study was U.K. The authors are aiming to create an optimal portfolio of assets, using Finnish government bonds, OMX Helsinki 25 stock index and real estate located in the Helsinki area, and due to this reason, the findings might be different compared to other countries or even cities in Finland. Furthermore, the financial market changes and evolves
1.3 Research questions
Are there diversification benefits to be derived from investing in real estate in Helsinki area?
What are the risks related to real estate investing?
What are the ideal asset allocations in the optimal portfolio? 1.4 Research purpose
The aim of the research is to study the risks related to real estate investing and the diversification benefits derived from having real estate in the mixed-asset portfolio, concentrating on the Helsinki area. Diversification in the context of investing implies decreasing the volatility of an investment portfolio as a result of investing in assets that are negatively correlated, while keeping the expected return at the same level. In other words, the risk of the investment portfolio can be reduced by having invested in different financial instruments, such as stocks and bonds, that react individually to changes in the economy. The aim is thus to analyse whether investing in real estate provides any diversification benefits in the Helsinki area, which consists of the metropolitan area surrounding the city of Helsinki, the capital of Finland with population around 1,5 million people.
Furthermore, the authors aim to find an optimal portfolio consisting of mixed assets that maximises the Sharpe ratio.
1.5 Contribution
From the theoretical perspective, this thesis seeks to shed light on the correlations between the different assets as well as the potential diversification benefits that can be derived from investing in direct residential real estates in the Helsinki area. Also, the study contributes to the prior literature by providing evidence on the test of the modern portfolio theory by Markowitz (1952), that centres around the concept of diversification, functions in the chosen setting.
Since the Finnish market is quite unique compared to previously studied markets, as discussed in the problematisation part, the findings of this study can provide new insights to this research field.
Furthermore, in Finland, the average age of a residential real estate investor is over 50 years (Mansikkamäki, 2016). This might be due to the reason that younger people perceive real estate investing requiring too much resources in the form of time and money and being riskier than it is. However, using leverage and getting to know the risks as well as the real estate in hand, more people should consider this type of
investors. Moreover, with the help of the study, the investors hopefully better understand and are prepared for the risks that arise from real estate investments. 1.6 Delimitations
Regarding aspects such as the time frame and the extent to which the authors would be able to conduct a study, there are certain delimitations that have to be made to the topic of the study. Delimitations meaning the decisions purposely made by the authors to narrow down the topic to an achievable degree considering different aspects.
The primary focus of this study is dwellings, specifically old dwellings, located in the Helsinki area. The authors made the decision to exclude other types of apartments (i.e. apartments in rowhouses) and offices with the purpose to avoid ambiguity of the results. Thereafter the authors further restricted the research to only old dwellings in block of flats where people reside instead of including the whole spectrum.
This study will only include direct property investing. This means that other “means of investing in real estate” i.e. real estate investment funds known as REITs will be
excluded for practical reasons and as they are not really comparable to direct real estate that can be rented out or in the sense of them having different risks and returns. In institutional investors are also excluded from this study, meaning that the focus is entirely on household investors.
As mentioned in the background, the population in the Helsinki area has been the fastest growing of Finland along with increasingly decreasing household sizes. The authors have therefore chosen to conduct this study only within the Helsinki area for this reason, along with it including the capital of Finland, as it is a very sought-after area to live in and therefore of interest to the authors.
For the securities market, OMX Helsinki 25-price index has chosen to represent the annual stock price developments and the bond returns are derived from the long-term Finnish government bond yields.
Lastly, this study will only include the years of 2010 up until 2018. This is because the authors found sufficient and reliable data for this time period. The authors would have wanted to include the years 2007-2019, but the Statistics Finland has changed the way the data was calculated thus not allowing for comparisons. All other areas outside of the delimitations are beyond the scope of this paper.
1.7 Disposition
The study consists of 7 chapters and the layout where the content of each chapter is introduced follows below.
Introduction
In the first chapter of the thesis the authors went through the background of the study and introduced the topic to the reader. After this, the research questions were provided before stating the purpose and motivation for the study. Delimitations were discussed in the first chapter.
Methodology
In the second chapter of the study, the methodology, different and relevant paradigms and methodological assumptions are presented and explained. The chosen paradigm and methodological outlook on the research are argued for and their implications on the research is presented. Additionally, source criticism for literature used in the study is presented and reflected upon.
Theoretical framework
Theoretical framework provides an introduction to the previous studies made in the area of scope. The authors also present the relevant concepts and theories used in the study, the most important being the modern portfolio theory by Harry Markowitz (1952). In the third chapter, the risks related to real estate investing are also introduced.
Descriptive statistics
The fourth chapter focuses on presenting the data of the empirical part of the study and how it is derived. The development of the different data is illustrated in the forms of graphs.
Research methods
This chapter concentrates on describing the methods used to calculate and analyse the data. The formulas that are used in the study are introduced as well as the key ratios enforced to examine the results.
Results and analysis
In the sixth chapter, the authors go through and analyse the results derived from the study. Test statistics for evaluating the normality of the data are also presented and discussed. The authors reflect back to the previous studies and theories for the purpose of comparing and assessing the findings.
Conclusion
2 Methodology
In this chapter we will present and argue for the selected research strategy, approach and design made in this study. Furthermore, the ontological and epistemological stance will be defined. Lastly, criticism of the sources used will be reflected upon.
2.1 Research philosophy
The research philosophy of a scientific study is the idea regarding how and which data about the research subject should be collected, used and applied (Research
Methodology, 2019). Research philosophy also harbours a number of different assumptions one makes when conducting a research. These assumptions refer to
epistemological, ontological and methodological assumptions that guide the researchers in conducting a coherent and cohesive research project (Saunders et al. 2009, p. 124-125). Considering ontology, epistemology and methodology harbour a directional relationship as they precede each other in the order mentioned (Hay, 2002: cited in Johansson & Fahlén, 2019, p. 8), this is the most logical order for the authors to present the methodology.
2.1.1 Ontology
The ontological assumption is a concept concerned with how the nature of reality is perceived as objective or subjective. It can be summarised as “the nature of reality” (Research Methodology, 2019). The subjective narrative is the belief that the social reality is inseparable from our own perception and actions. According to this assumption there are multiple realities consequential of people perceiving reality differently (Burrell & Morgan, 2016: cited in Saunders et al., 2019, p. 137). The
objectivist belief is the assumption that the research is external from the social actors as well as independent of our knowledge about it. This narrative assumes that there is only one truth, one result and one reality regardless of us as social entities (Saunders et al., 2019, p. 135).
As this research is conducted quantitatively with the goal to find the optimal investment portfolio, there would be no point of a subjectivist assumption. It would only be logical to assume an objectivist view as this study does not take social actors, different
perceptions and multiple realities into consideration.
2.1.2 Epistemology
Epistemology deals with knowledge and what is regarded as true knowledge, such as where does the knowledge come from, what is the nature, possibilities and limitations of the knowledge (Research Methodology, 2019). There are two types of epistemology that are the most common within social sciences, positivism and interpretivism.
research (Collis & Hussey, 2014, p. 44-45).
Positivism holds a more objective and singular view of reality and considers the
researcher separate from what is being researched. Human interests are unimportant, as it is focusing on facts and has a value-free outlook on the research (Research
Methodology, 2019). Positivism originated from the natural sciences and is used with a deductive method with an aim to provide explanatory theories to social phenomena (Collis & Hussey, 2014, p. 43). As this is a quantitative study with an objectivist ontological assumption, the most common combination would be the positivist epistemology (Bryman, 2012, p. 36). As the impression the authors have gotten from previous research this is also what would fit the topic of this study the most.
2.2 Research strategy and methodological choice
According to Saunders et al., (2009, p. 125) the research strategy and methodological choice are closely intertwined. There are multiple different research strategies, but the two most common ones are qualitative and quantitative (Bryman & Bell, 2017, p. 58), the latter being what the authors chose for this study.
Qualitative research, according to Collis & Hussey (2014, p. 6,10) is when experiences, themes and patterns are analysed in an interpretive manner. In other words, qualitative research revolves around words, meanings and in-depth understandings of subjects that are not easily understood with calculations and concrete facts. Simply put, the core idea of this methodology is to collect information to understand something rather than to test a theory (Streefkerk, 2019).
On the contrary, a quantitative methodology is about numbers and facts. Usually done under a positivist paradigm (MacIntosh & O’Gorman, 2015), quantitative research has to do with numbers, statistics and graphs to display the statistics. When conducting this type of study, it is important to have a large sample as that helps with generalising the results and increasing the applicability to the population. The core idea within this methodology is to, through statistical tests, confirm or dismiss a theory or hypothesis (Streefkerk, 2019).
The most natural combination for an objective ontology and positivist epistemology according to MacIntosh & O’Gorman is the quantitative methodology (MacIntosh & O’Gorman, 2015, p. 59). This is supported by earlier studies on topics related to our own such as Falkenbach (2009), Pietiläinen (2009) and Hagängen & Najafzadeh (2005). Since all these researches have been done by using the quantitative method, the authors chose to go with that as well, as the aim is to test the theories numerically.
2.3 Research approach
There are two different options for the research approach, the inductive and the
deductive approaches. The fundamental difference between these two methods are that the inductive approach aims to develop a theory through observation while the aim of the deductive theory is to analyse existing theories (Streefkerk, 2019).
then is tested with empirical evidence acquired through data collection (Bryman, 2012 p. 24).
Figure 1. Process of deduction
Source: Bryman, 2012, p. 24
The last step of the process of deduction harbours some inclusion of the inductive approach as the confirmed or rejected hypotheses are added to the theory and knowledge surrounding it (Bryman, 2012, p. 24). While still in an early stage of this study, the authors realised that the deductive approach would be more suitable than the inductive. This is considering the time frame as well as the sufficient number of pre-existing theories that the authors were able to find and use as a basis for this study.
2.4 Research design
When choosing the research design, it is important to know what type of data is of interest regarding the topic in order to help the researcher understand the research subject (Blomkvist & Hallin, 2015, p. 62). The concept of the research design has to do with devising a plan to answer the research question (Saunders et. al., 2012, p. 159) as well as provides some ground for the process of data collection and analysation
(Bryman & Bell, 2011, p. 40). According to Saunders et al. (2012 p. 160), the different classifications of research designs are exploratory, descriptive and explanatory.
explanatory research is built upon descriptive research and goes beyond describing and explaining phenomena, and in addition focuses on finding new causal relationships between variables (Collis & Hussey, 2014, p. 5). Since the descriptive research is focusing on finding the mean, median and frequency of the topic of interest the authors concluded this research design to be best suited for investigating real estate investing. 2.5 Literature search and source criticism
According to Grewal et al. (2016) literature search is a “a systematic and well-organised search from the already published data to identify a breadth of good quality references on a specific topic”. The initial literature search is conducted with the goal to identify research gaps in already existing research.
This thesis is written using secondary sources. This is because the authors considered the time frame and the type of data needed for the topic. The numbers included are all taken from official statistics of the Finnish property, bond and stock market. Another source deemed credible for finding the numbers for the risk-free rate in order to calculate the Sharpe ratio is Statista. The risk-free rate used in the study is 12-month Euribor. Euribor stands for Euro Interbank Offered Rate and contains important reference rates within the European money market that Finnish banks use to borrow to each other. Regarding other sources used, such as peer-reviewed literature and previous research are found using trustworthy databases such as Umeå University’s official database and google scholar. Articles or webpages found elsewhere and included in this research are cross-checked with other sources to ensure credibility of the information.
Some of the theories used in the research have been developed as early as in the 1950s but are still considered relevant as the theories themselves have not changed and thus are not regarded as outdated.
2.6 Ethical considerations
Ethical and societal issues have to do with morals, values and principles within the code of conduct, which are concerned with the way results are disclosed as well as how the research is conducted (Collis & Hussey, 2014, p. 30). Steneck (2007, p. 69) identifies four important principles that upholds the integrity of the research: objectivity, honesty, efficiency and accuracy. The meaning of these principles is to avoid any researcher bias, disclose impartial, authentic and reliable information, prevent wasteful use of resources as well as reporting reliable and trustworthy findings. As this is a quantitative study conducted by using secondary data the authors are obligated to follow and maintain these ethical principles throughout the entirety of the research.
The authors will ensure these ethical values are followed throughout the entirety of this study. The sources used for the data are secondary sources like Statista and Thomson Reuters Eikon Datastream. This indicates that ethical issues such as privacy, data
would arise, they will be highlighted and solved immediately in order to ensure and uphold the integrity of the research.
Furthermore, according to Leinonen (2018), the selection of the research topic is already an ethical issue, as it has to do with the consideration of the benefits and
3 Financial instruments
This chapter introduces the financial instruments used to construct the optimal portfolio in this study. Some of the most central risks related to the stocks and bonds are briefly discussed.
Financial instruments can be categorized in many different ways. One way to categorise the instruments can be done by looking at the maturities of the assets. Maturity in this context means the period until the instrument expires or is due. Usually the short-term instruments have a maturity of less than one year, while the long-term instruments have a maturity of one year or more. The instruments can also have different valuation methods and be evaluated by looking at them. Often times financial instruments are divided into debt capital, such as bonds, and into equity, being stocks, as well as to derivatives (Nikkinen et al, 2002, p. 11).
Mishkin et al (2013, p. 27) divide financial markets into money and capital markets. Money market consists of short term and less risky assets that can be traded in the secondary market. Capital market in turn consists of instruments with longer maturity and thus higher risk. The capital market provides a plethora of financial instruments, such as long-term government and corporate bonds bank loans as well as stocks. Moreover, mortgages are part of the main capital market instruments.
In addition to the above-mentioned categories, the instruments can be divided into financial assets and real assets. Real assets include tangible objects, such as property and land, while financial assets include claims on real assets such as bonds and stocks as well as derivatives (Pedersen, n.d.). In this study, the instruments are divided into stocks, long-term government bonds and direct residential real estate.
3.1 Stocks as investments
Stocks are regarded as equity, giving the investor a share of the assets and income of the company. In case the company runs into trouble, it has no obligation to repay the
investors and in the event of bankruptcy, the stockholders are the last ones to receive any funds. The company can acquire new funds by organising an equity offering. It can also obtain financing by means of issuing stocks if it is listed in the stock exchange through initial public offering (IPO) or through share issue (Nikkinen et al, 2002, p. 12-13). In initial public offering, the company sells its stocks for the first time to investors and after the IPO, the company is listed in the stock exchange. The share issues are carried out via investment banks who underwrite the stocks, meaning that they purchase the stocks from the companies at a certain price and then sell them forward to investors (Miskin et al, 2013, p. 26). The aim can be to oversubscribe the share issue to be able to sell all of the stocks, which leads to some subscribers not receiving the amount of stocks they wanted (Sijoitustieto, 2017).
Companies that are large in size are usually listed in one or more stock exchanges (Beers, 2019). This implies that the stocks of the company can be purchased and sold in the stock exchange. However, some of the limited liability companies are not listed, meaning that the stocks might not be available for the public. Stock indexes on the other hand measure the price developments of stock markets. Each index includes a specified amount of stocks and can be used as indicators when measuring the performance of funds or stock markets. In this study, OMX Helsinki 25 is used that includes the 25 most exchanged stocks in the Helsinki stock exchange. The weight of each stock is limited to 10% (Nasdaq, n.d.).
According to Nikkinen et al (2002, p. 12, 128), stocks differ from other financial instruments by their maturity. The maturity of the stocks can be considered to be eternal, as they do not expire unless the company becomes bankrupt and the invested funds are returned. In addition, the valuation of stocks is different than that of debt assets. As the future returns of the stocks are not known, the valuation is based on expectations. There are multiple models and ratios for stock valuation, which are in general based on future cash flows. The future cash flows made out of the possible dividends that the company is paying out for the investors. In addition, stocks can be considered highly liquid as they are traded in the stock market continuously.
Nikkinen et al (2002, p. 29-30) introduce risks related to investing in stocks. Market risk refers to the volatility in the asset returns caused by the changes in the market and it affects above all to the stock returns. Market risk arises from the external factors of the company, such as from war, consumer behaviour or changes in the economy. The stock returns of a company are also affected by the business risk and the country risk.
Business risk influences only a certain industry while the country risk is specific to a certain country. The country risk arises from the political situation and economic stability of the different countries and are important to consider when investing in abroad. The investor also needs to take into account the inflation risk, that can cause depreciation in the value of the currency invested as well as the financial risk that arises from the companies financing their investments with debt.
3.2 Bonds as investments
Bond markets consist of long-term debt instruments that have a maturity more than one year. An investor can purchase government bonds, that can be considered fairly low risk, as well as corporate bonds with a higher level of risk. Bonds usually offer the owner a stable cash flow, as the issuer of the bond pays the investor a predetermined coupon payment. In addition to the coupon payments, the issuer of the bond pays the owner of the bond the face value of the bond at the time of the maturity. However, zero-coupon bonds also exist, that do not pay any zero-coupon payments to the owner and are instead sold at a lower price than the face value of the bond (Mishkin et al., 2013, p. 54). In the loan terms of the bond, the maturity is determined. The maturity determines when the last coupon is paid, and the capital is returned.
The bond prices and interest rates have an inverse relationship as when interest rates go up, the bond prices go down and vice versa (Mishkin et al, 2014, p. 76).
There are also risks related to bond investments. Even though bonds can be often regarded as risk-free investments, the following risks are associated with them. The credit risk implies the risk arising from the issuer of the bond not being able to pay back obligations regarding the bond as it matures. Another risk related to bonds is the interest rate risk that comes from the changes in the interest rates. As the interest rates increase, the returns of the bonds decrease in relation to other financial assets. The price of the bond also falls as the interest rates increase. Moreover, the liquidity risk also needs to be mentioned and it indicates the risk arising from the investor not being able to resell the bond in the secondary markets. This can be due to the bond having a poor credit rating (Mishkin et al, 2013, p. 73, 110, 114; Merrill Edge, n.d.). However, in contrast to stocks, the bondholders are entitled to get their funds back in case the company or country defaults.
3.3 Real estates as investments
Real estate as an investment differs fundamentally from the stock and bond investments. Unlike real stocks and bonds, investing in direct real estate includes buying an actual, tangible property. As mentioned in the introduction chapter, this study does not investigate indirect real estate investing, such as REITs.
Real estate investing is an important form of investing among other assets. In Finland, the amount of residential real estate investments was about 200 000 in 2017, while in 2006 it was 115 000. In percentage, the increase is 77%. During the same period the increase of available housing stock was 11% (Kannisto, 2019).
There are many features that are specific to real estate investments, in addition to it being tangible. Unlike stocks, every real estate is unique due to the size, location and age of the real estate. The location is one of the main factors affecting the value of the investment. Different areas often have different reputations, services as well as infrastructure, which all can positively and directly impact the value of the apartment (Taipale, 2019). The location may affect the value of the real estate in a such way that buyers are willing to pay price above rational price just due to the psychological reasons. According to Paunonen (2019), a more central and better location implies higher purchase price and a smaller return in the form of rents but higher expected value increase. An apartment with a better location is usually easier to rent out and resell, while the apartment in a less popular area ties up less capital. The rental payments can be considered as the dividends of real estate investments.
or management. An investor can also invest in funds that are managed by an analyst, thus shifting the control to another person (TalousSuomi, 2020).
The two last attributes that are particular to real estate investing include the way real estates are valued as well as the illiquidity of them. The stock markets can be
considered highly efficient, with the prices determined by the demand and supply. Real estate markets contrarily can be inefficient, due to the unsymmetrical information and smaller markets, that are not concentrated on one certain place. Moreover, the amount of transactions is relatively small. In Finland, the selling and purchase prices of the real estates are not public information, which makes it harder to analyse the actual market price and may cause the investor to pay a higher price. Finally, real estate investments are much more illiquid compared to other financial instruments. While stocks and bonds can be traded constantly with relatively low costs, the trading costs and selling times are higher for the real estate investments (Haataja, 2017).
4 Theoretical framework
In this chapter the authors provide a literature review by going through the previous studies. Afterwards, the central theories and concepts used in the study and in financial research are introduced. The concepts of risk and return, as well as diversification effect known as the free lunch of the financial world are being described before going through the most central theory called Modern Portfolio Theory (MPT). The chapter ends in presenting the risks in direct real estate investing and renting.
4.1 Literature review
The diversification advantages that come from having real estate in the investment portfolio have been studied over the years. A common finding in many papers is that the risk of the portfolio decreases when having included real estate. The benefits arise from real estate being an asset class that has a low correlation with stocks and bonds, in addition to it being used as a hedge against inflation (Hoesli & Hamelink, 2002; Seiler et al, 1999; Hudson-Wilson et al, 2005). However, some researchers have received opposite results depending on the holding period of the assets.
There has been varying results of the optimal allocation percentages of the different financial assets in the portfolio. Fogler (1984) argues that 15 to 20% in real estate is the optimal amount to be allocated in real estate. Hoesli and Hamelink (2002) on the other hand looked into the real estate market in Geneva and the benefits of having property in the Swiss mixed-asset portfolio. They came to the conclusion that the optimal portfolio consisted of 20% of stocks, 53% of bonds and 27% of real estate in Swiss markets. In a study done by Kallberg et al (1996) the optimal real estate allocation in a U.S. portfolio is concluded to be only 9%. However, in the study they noted that having smaller sized real estate in the portfolio would have a positive effect, as they have weaker correlation with other assets combined with better returns compared to bigger real estates. In the same study, the authors state that having bonds in portfolio containing real estate is not ideal.
Stephen Lee in his study called “Is there a “Case for Property” all the Time?” (2002) has looked into the benefits of including direct property into a portfolio containing equity and bonds in the U.K. According to his study, the inclusion of direct property always reduces the risk of the portfolio. However, Lee states that the positive effect on the portfolio return can only be seen when the allocation is more than 10%. In the study, Sharpe ratio was used as a measure of the performance of the portfolio and the greatest impact was received then the real estate allocation was 15-20%.
Finnish studies regarding real estate and the diversification effect have also been made. Kuosmanen (2002) in his doctoral thesis writes about the risk and return in the real estate markets. The aim was to create an optimal portfolio when investing into real estate in Finland. In addition, he looked into the returns of different sized apartments. As a result, allocating most of the funds to one-room apartments and 3-bedroom apartments yielded the highest return. In the more recent studies though, and especially in Helsinki area, one room apartments have been the most profitable residential real estate class (Mikko Laitila, 2013). Kuosmanen’s findings include that investing in real estate in Finland is a good way to improve the risk and return relation in the investment portfolio. He states that investing in real estate may offer an effective way to decrease the risk of the portfolio without needing to decrease the required return. However, the result was derived from long-term holdings. When looking into the allocation of the different assets, Kuosmanen came to the conclusion that the optimal portfolio had over 50% allocated in real estate, however, the portfolio did not consist of any bonds. Oikarinen (2007) in his doctoral thesis studied the housing prices in Finland,
concentrating on the central areas. He found that the stocks and real estate prices are correlated in Finland and an investor can achieve diversification benefits mostly during a short-term period. This finding differs from Kuosmanen’s study. When it comes to the bonds, the correlation between other financial instruments was significantly weaker, thus yielding good diversification effects. According to him, using quarterly correlation data can be deceiving due to the lead and lag relation and recommends using more long-term data. Oikarinen also states that the price developments of real estate in Finland can be forecasted rather accurately. Other findings include that the changes in the prices of real estate in the Helsinki area cause changes in the prices of real estates in other areas of Finland. Furthermore, the price increases in the outskirts of Helsinki have caused price increases in the city centre.
In the article called “Diversification benefits in the Finnish commercial property market” written by Falkenbach (2009), she found that the return of the direct real estate was between the two asset classes – bonds and stocks. She also noticed that the bonds of Finland’s government correlated negatively with other financial assets in the created portfolio, indicating that one can be better off by including bonds in the portfolio. However, the direct property and stocks had a positive correlation, meaning that benefits derived from diversification were not substantial.
A more recent research has been done by Känsäkoski (2019), who has studied the dynamics of investment property markets in the growing centres of Finland, Helsinki being one of them. He states that real estate investing has been increasingly popular during the past years in Finland. According to his study, the rents have been steadily growing and the economic shocks have rarely affected the rents. In addition, the real estate investors can expect the rents to grow in the future as well. Känsäkoski also says that investors should monitor the price developments of the Helsinki real estate markets, as they work as a forecast for the real estate market developments in other growing centres of Finland (Känsäkoski, 2019).
also discuss the advantages of investing into real estate in comparison to stocks. The newest edition of the book, published in 2016, has been used as a source in this paper.
4.2 Risk, return and diversification
Risk is a concept that can be defined in many different ways. Common words associated with risk include uncertainty, probability and variability. According to the International Organization for Standardization (2009), risk is “the effect of uncertainty on
objectives”. Kaplan and Garrick (1981) define risk being equal to the sum of
uncertainty and damage “risk=uncertainty+damage”. Harry Markowitz (1952) defines risk as “variance of return” or “an undesirable thing”. Another definition offered by Karen A. Horcher is that risk is the “probability of loss” (Horcher, 2005, p. 1). In finance, risk is defined and measured by the volatility of the returns. The volatility equals the standard deviation, which measures the variance of the returns from the mean. The higher the standard deviation, the more changes in the value of the
investment and thus the riskier the investment (Berk & DeMarzo, 2017, p. 355-356). In the modern portfolio theory by Harry Markowitz (1952), risk is divided into two types: unsystematic risk and systematic risk. Unsystematic risk is particular to the stock and the company and can be diversified away by investing into multiple assets with different correlations. An example of an unsystematic risk is the change of the CEO of a company. The risk that is left is called systematic risk. This type of risk affects
systematically to all companies in the economy and cannot be eliminated (Outreville, 1998). Examples of systematic risks are inflation and changes in the exchange rates.
Figure 2. Diversification effect
Return can defined as “the difference between the selling price and purchasing price of an asset plus the cash flows expressed as a percentage of the buying price” (Berk & DeMarzo, 2017, p. 1125) or as the profit derived from the asset in excess to what was initially invested, expressed as a percentage. (Cambridge Dictionary, n.d.) The return of the investment tells how well the investment has performed and due to the percentual returns, the performance of different investments can be compared. In direct real estate investing, the return can arise from two sources; rental payments and real estate
increasing in value (Orava & Turunen, 2016, p. 50).
4.3 Modern portfolio theory
The modern portfolio theory and the principles of asset diversification created by Harry Markowitz (1952) has long been used for optimal investment portfolio creation. The main idea of the theory is to create a portfolio made out of multiple assets in order to receive maximum level of return to a given level of risk. According to the theory, the unsystematic risk can be diversified away by investing into multiple different financial assets with different level of risk, while still keeping the same level of return.
The theory assumes that all investors are rational, and the market is efficient. The rationality of the investors means that they use the available information to form expectations about the future, in order to achieve maximum capital gain. The investors are also considered to be risk averse, meaning that they try to avoid risk and uncertainty, while wanting to maximise the expected return (Markowitz, 1959).
Markowitz observed that when there is large enough number of uncorrelated assets in the portfolio, the volatility of the portfolio decreases. When combining assets that are negatively correlated, they move into different directions making it possible to
compensate the loss of a one asset with the gain of the other asset. This minimises the risk while keeping the expected return on a same level. As mentioned in the subchapter above, the only risk that is left is the systematic risk, the one that cannot be diversified away (Markowitz, 1959). However, if the assets in the portfolio are correlated, even increasing them in number would not yield the diversification effect.
Figure 3. Efficient frontier
Figure 3 shows the efficient frontier as well as the optimal portfolio. The lower corner on the left of the efficient frontier shows low risk and low return portfolios and when moving up along the line the portfolios increase in risk and return. The capital market line (CML) goes from the risk-free investment through the optimal portfolio, that is, when the CML is tangent to the efficient frontier curve (Berk & DeMarzo, 2017, p. 419).
4.4 Risks in direct real estate investing
In this subchapter, the typical risks related to real estate investing are introduced. Even though real estate can be generally considered as a fairly low risk investment, there is a great deal of matters to be kept in mind. Among other things, the risks depend on the experience and knowledge of the investor, the amount of leverage, location of the apartments as well as the tenants. According to Orava and Turunen, acknowledging risks and reacting to them in correct ways is a part of successful real estate investing (Orava & Turunen, 2016, p. 245-246).
The risks have been divided into three groups. The first group includes the economic risks – price, interest rate, inflation and liquidity risks. The second group has to do with renting and tenants. Finally, some other risks are being introduced that include
renovation and political risks as well as the risk of a natural disaster.
4.4.1 Economic risks
When investing into a real estate, the investor bears the risk of the real estate decreasing in value and the price falling below the purchasing price. This is known as the price risk and is especially relevant to the investors having the “flipping strategy”, meaning that they renovate and sell the apartment in a short time period. The price risk is realised at the point of time when the real estate is being sold. A good example of the realisation of the price risk happened during the financial crisis in 2008, when many investors
loans. The properties lost most of their value and the investors were left with loans higher than the value of the real estate. However, if the investor has a long-term investment period and is concentrated on the cash flows from the apartments, the price volatility does not affect the investor. Even if the prices of the real estate would fall during a short time period, the rent payments would still continue to arrive. In time, the prices would most likely increase again and thus make the capital losses minimal. To shelter from the price risk, the investor should have the cash flow strategy and long-term time frame. The leverage should also be kept at a low level (Orava & Turunen, 2016, p. 247-249). Furthermore, the location, size and condition of the apartment are also important to consider before buying the apartment. In Finland, the prices of the apartments in the growing centres (Helsinki area, Tampere and Turku) have been growing at the steadiest rate. According to Orava and Turunen (2016, p. 336) the smaller the apartment, the better it is as an investment. This is due to the high demand of small apartments and the households being small in size.
The interest rate risk arises from the changes in the interest rates. Interest rates affect the return of the investment and especially in the case of high leverage, the changes in the rates can have great impacts on the returns. In addition, the risk increases the more leverage has been used. In case the interest rates increase, the monthly payment usually increases as well. An option is extending the maturity of the loan. Measures that can be taken to shelter from the interest rate risk include fixed interest rate, interest rate cap, moderate leverage and having a buffer of liquid assets that should be more than 30% of the total value of the real estate. However, no measure is enough to fully cover for the risk. Even if the investor would have a fixed interest rate, the increases of the rates might decrease the price of the property others are willing to pay. According to Orava and Turunen (2016, p. 251), moderate leverage means that the loan is less than 50% of the market value of the apartment.
The interest rate is connected to the inflation risk, as when the expected inflation increases, the interest rates tend to increase as well (Mishkin et al, 2013, p. 91). However, real estates can be considered as a hedge against inflation (Hoesli, 1994, p. 52). Usually the investor has the possibility to increase the rent as the inflation increases.
When investing into real estate, the investor needs to bear in mind the illiquidity and the higher transaction costs of the asset (Damodaran, 2005, p. 34, 59). Liquidity can be defined as “the relative ease and speed with which an asset can be converted into cash” (Mishkin et al, 2013, p. 605). The selling times of the apartments are longer in
comparison to financial instruments such as stocks and bonds that are traded
continuously. For real estate, it might take time before someone is willing to pay an acceptable price, as buying an apartment is usually considered to require much more commitment as well as resources, which decreases the number of investors in the market (Orava & Turunen, 2016, p. 20).
4.4.2 Risks in renting
general level or having bought an apartment from an area with little demand. The risk can be reduced by investing in apartments that are located in the growing centres of Finland, university cities and buying apartments that are small in size. In Finland, 58% of the households renting apartments were single-person households in 2010 (Juntto et al, 2010). According to a study done by KTI, the demand for one-bedroom apartments is high in Helsinki and the demand is expected to continue growing. In the same study it is stated that the demand for larger apartments has decreased (KTI, 2019, p.18, 56, 61). If the investor however invests in apartments that are further away from the city centres and universities, it is important to check that good connections are offered by the public transportation and that the area provides good services in the form of grocery stores, pharmacies and leisure activities.
Another risk that is included in renting is the risk of having a bad tenant. Juntto et al (2010) were commissioned by the Ministry of the Environment of Finland
(Ympäristöministeriö) to do a study about rental apartments as investments in Helsinki. In the study they found that 61% of the sample of 462 investors renting out apartments have had some troubles with the tenants. Most often the troubles were related to the tenants not paying rents in time or them only renting the apartments for a short time. Some had had troubles with the tenants not maintaining the apartment well. Orava and Turunen offer three ways of minimising the risk of a bad tenant: screening the credit ratings, asking for a deposit and talking with the potential tenants beforehand (Orava & Turunen, 2016, p. 254). The Finnish Landlord Association in an article published by Suomen Kiinteistölehti (2019) recommends that the lessor always checks the income level of the tenant and asks for references from the previous lessors in addition to the tips provided by Orava & Turunen.
4.4.3 Other risks
The investor may encounter other risks that are harder to forecast. One of these risks is political risk that includes the government raising taxes, introducing new legislation, cutting down the housing and studying allowances or decreasing the deductibility of the interest expenses. They are almost impossible to avoid and even more difficult to forecast (Orava & Turunen, 2016, p. 259).
Renovation risk is also something that the investor needs to be aware of. Especially the older houses are at some point in the need of a renovation that can become expensive. Renovation are usually the largest expense items in a residential real estate. Large renovations during long-time frame can cost as much as the value of the apartment, so it is absolutely vital to prepare for them to be able to calculate the expected return
correctly. In addition, the apartment might not be inhabitable during the renovation, leading to a decrease of revenues. The risk can be minimised by investing into newly built apartments and familiarising oneself with the housing cooperative (Orava & Turunen, 2016, p. 258). The Limited Liability Housing Companies Act obligates the housing cooperatives to provide a report on maintenance needs that is an estimate of the renovations that are to come during the next 5 years (Finlex, 2009). This is something the potential investor should familiarise oneself with.
acknowledge. The biggest natural phenomenon risks in Finland include the risks of storms, lighting and floods (Orava & Turunen, 2016, p. 210). It usually is impossible to predict these, but luckily it is possible to prepare for the economic losses caused by them. Most of the home insurances in Finland cover for the losses caused by the exceptional natural disasters (If, 2020). The investor should thus take an insurance for the rented apartment in addition to the home insurance taken by the tenant, to make sure the apartment is insured the whole time.
5 Description of the data
The historical data used in the research is presented in this chapter. The development of the prices of the dwellings and the rents as well as the development of OMXH25-index and interest rates are illustrated in the form of graphs.
The authors are using yearly averages, as they are aiming to compare the annual returns of the assets and portfolios. The reasoning behind this is that the prices of the real estates and rents do not develop and change in a such manner as the other financial assets. Thus, it is more reasonable to use the annual data.
5.1 Data on real estate
The material and data for the real estate markets is derived from Statistics Finland (Tilastokeskus). Statistics Finland is a Finnish public authority that publishes and produces majority of official statistics. The data describes the price development of the old dwellings in the Helsinki area and for comparison, the data from the rest of Finland has also been included. The authors have decided to concentrate only on old dwellings in apartment buildings, however, all sizes of dwellings were included in the research. Furthermore, Statistics Finland provides the average monthly maintenance cost per square meter. To get the yearly average, the monthly cost is multiplied by twelve.
The development of the rents is also obtained from Statistics Finland. The authors have decided to exclude the government subsidised apartments and only look into the
unsubsidised rental dwellings. Investing in the subsidised apartments is not profitable, as the government controls the rents, and thus they are not included in the study. The data derived is expressed annually, making it possible to compare the prices and calculate returns. Using the above-mentioned data, the return on real estate can be calculated.
Figure 4. Price index of old dwellings 2010=100
Figure 5. Price development of old dwellings
From figure 4 it can be noted that the prices of the old dwellings have been quite steadily increasing in the Helsinki area. Between the years 2013 and 2015, the prices stayed approximately on the same level. From 2010, the prices of the old dwellings have increased by 22,3%. If looking at the rest of country, the development has been slow. The prices have increased by only 2,5% during the same period (Tilastokeskus, n.d.).
in 2018. In the rest of Finland, the price increased from 1485€/m2 in 2010 to 1598€/m2 in 2018 (Tilastokeskus, n.d.).
The development of the prices of the unsubsidised rental dwellings in Helsinki area and the rest of Finland is illustrated in figures 6 and 7. Figure 6 shows how the rent index has developed between 2010 and 2018, while figure 7 describes the rent development in terms of price per square meter during the same time frame.
Figure 6. Rent index 2010=100
When examining the rent index in figure 6, it can be seen that rents in the Helsinki area are steadily increasing, but the difference compared to the whole Finland is narrower. In the Helsinki area, the increase has been 26,9% from 2010 to 2018, while for the rest of the country it has been 25,8%. However, a distinction can be seen in the average rents per square meter (figure 7). In the Helsinki area, the rent price per square meter in 2018 was 18,80€, while the price for the rest of the Finland was only 11,98€ (Tilastokeskus, n.d.).
5.2 Data on financial instruments
The data used for the securities markets in the research has been derived from Statista and from a database called Thomas Reuters Eikon Datastream. For the stock market, the OMX Helsinki 25-index provided by Thomas Reuters Eikon is used. The price index contains the stocks of the 25 most traded stocks in Finland with the maximum weight of each stock being 10% (Nasdaq, n.d.).
Figure 8. Index price performance
Figure 8 describes the development of the OMXH25-index between the years 2010-2018. From the graph it can be seen that the trend has been upward sloping, however, the average returns have been negative in the years 2011 and 2013. In the calculations, the authors have used annual return percentages (Thomson Reuters, n.d.).
Figure 9. Annual averages of long-term government bond yields
Figure 10 represents the evolution of average annual 12-month Euribor rates. Euribor is the rate at which European banks can borrow funds from one another. The 12-month Euribor is the most commonly used rate in mortgages in Finland (Osuuspankki, n.d.). The rates have stayed at very low levels in the previous years, which has attracted investors to use leverage and invest in apartments. The number of people receiving cash flows from rental activities in Finland has increased from 269542 in 2010 to 317852 in 2016 (Alho et al., 2018).
6 Research methods
In this chapter the authors introduce the quantitative methods applied to analyse data from real estate and securities market. The formulas used to calculate return, volatility and correlation as well Sharpe’s ratio used to measure the performance of the financial assets and portfolios are reviewed.
6.1 Calculating the return
To calculate the return of the real estate investments, the formula used to compute the return of stocks has been utilised (Berk & DeMarzo, 2017, p. 311). The dividend payment has been replaced by the cash flows from renting and the price of the stock by the price of the dwellings. Therefore, the formula of the average return percentage of the real estate investments is the following:
𝑅𝑡 = 𝑁𝑅𝐼𝑡 𝑃𝑡−1 +𝑃𝑡 − 𝑃𝑡−1 𝑃𝑡−1
where Rt is return percentage. Pt and Pt-1 are the prices of the dwellings (€/m2) at times t
and t-1. NRIt is the net rental income at time t, from which the maintenance expenses have been deducted (€/m2). The term on the right side of the formula represents the capital gain derived from the dwelling increasing in value. The middle term is the income return component, paid for the investor in the form of rents.
The average return for the stock index has been calculated by using the formula below:
𝑅 = ln 𝑃𝑡 𝑃𝑡−1
where R is the quarterly return of the stock index and ln is the natural logarithm. Pt
represents the starting price of the stock index at time t and pt-1the ending price at t-1. To get the average annual return percentages, the values were added up and divided by four. The same formula has been utilised to calculate the return percentages for bonds and Euribor interest rates.
6.2 Calculating risk and volatility
where STD is the standard deviation for the return, Rt is the return at time t, 𝑅̅ is the average return during the whole period and n is the number of observations during the whole time period. To remove the degree of freedom due to using average return, n-1 is used as denominator (Berk & DeMarzo, 2017, p. 361).
6.3 Calculating covariance and correlation
Covariance measures the association between two variables and the deviations from their means. If covariance is positive, when the other variable, for example stock price, increases above the average, the other variable tends to increase as well. In case the covariance is negative, the variables move in opposite directions (Berk & DeMarzo, 2017, p. 392). In this research, the following formula was used to calculate the covariance of the returns of different assets:
𝐶𝑜𝑣 (𝑅𝑥, 𝑅𝑦) = 𝜎𝑥𝑦 = 1 𝑁 − 1∑ (𝑅𝑥,𝑡− 𝑅̅̅̅̅)(𝑅𝑥 𝑦,𝑡− 𝑅̅̅̅̅𝑦 𝑁 𝑡 )
In the formula, σxy is the covariance of the returns of x and y. Again, N-1 is used to remove the degree of freedom.
Correlation has an alike definition, as it also measures how the variables or returns are associated. The values can be between 1 and -1, and when the correlation is 1, the variables always move in the same direction. If the correlation is -1, the variables move to the opposite direction by the same amount. 0 correlation indicates that there is no correlation and thus no relation between the variables (Berk & DeMarzo, 2017, p. 393). As discussed in the theoretical part, the investor should compose the portfolio of assets that are negatively correlated to take advantage of the diversification benefits. The correlation of the assets is calculated by dividing the covariance of the returns by the standard deviation of each return and in the research the formula below was used:
𝐶𝑜𝑟𝑟 (𝑅𝑥, 𝑅𝑦) = 𝜌𝑥𝑦= 𝐶𝑜𝑣 (𝑅𝑥, 𝑅𝑦) 𝑆𝑇𝐷(𝑅𝑥) 𝑆𝑇𝐷(𝑅𝑦)
where, ρxy is the correlation of xy and STD (Rx) and STD (Ry) are the standard
deviations of the returns of x and y.
6.4 Sharpe ratio as a measure of performance
When calculating with the Sharpe ratio, an assumption that is made includes that investors are able to invest in risk-free assets as well as borrow at the risk-free rate. The higher the Sharpe ratio, the more return the asset or the portfolio has generated in relation to its risk (Sharpe, 1966). The Sharpe ratio can be calculated by using the formula below:
𝑆 = (𝑅𝑝− 𝑟𝑓) 𝑆𝑇𝐷 (𝑅𝑝)
where Rpis the return of the asset or portfolio and rf is the risk-free rate, and the
difference between these two is the excess return. STD (Rp) is the standard deviation of the asset or the portfolio. Further, as mentioned earlier, the authors have used 12-month Euribor as the risk-free rate.
7 Results and analysis
In this chapter, the authors present the findings of the research and connect them to the previous studies. First, the annual average returns on the different assets are being introduced. Thereafter, the diversification benefits are analysed with the help of the correlation matrix. Lastly, the performance of the different assets and constructed investment portfolios measured by the Sharpe ratio are being examined. All of the calculations have been performed with using Excel and its add-ons.
The purpose of the study is to find out the diversification benefits that can be achieved by investing in real estate among other assets in Helsinki area. Further, the aim is to identify the optimal portfolio that can be constructed during the period of 2010-2018. Moreover, the risks included in real estate investments are also being introduced.
7.1 Descriptive statistics
The returns of the different assets during the period 2010-2018 are being represented in table 1. As annual returns are being examined, the number of observations is 9.
Table 1. Annual return percentages during years 2010-2018
the Helsinki area have been constantly increasing. The result differs from Falkenbach’s (2009) study, as she found that the return of the real estate was between stocks and bonds. However, the real estate she studied was commercial property and the data covered a different time period.
The development of the returns has not been following an increasing trend though. This is due to the average maintenance costs being higher on some years than others. The standard deviation of the real estate returns is fairly low at 2,06%, meaning that the returns do not greatly differ from the average. The low standard deviation also indicates that the risks in real estate investing have been relatively low. In addition, the median is close to the mean.
The data concerning the security returns is also represented in table 1. It can be observed that the stock index returns have been far more volatile compared to the average returns on real estate and bonds. For the stock returns, the median differs greatly from the mean. The difference can be explained by looking at the minimum and maximum returns as well as the standard deviation of 15,74%. The highest individual observation of the returns was received from stocks, but the extremely negative return of -32,3%, caused by the Euro crisis in 2011, led to the mean value to decrease
(Niskakangas, 2020). For the bonds, the median is almost equal to the mean and the standard deviation is less than 1%. However, the average annual stock returns have been higher than the average returns on bonds by more than 4%. Bonds yielded the lowest return of the asset classes during the period of 2010-2018.
7.2 Correlation between the returns
The correlation of the average annual returns of the assets can be seen in the table 2.
Table 2. Correlation of the returns
When looking at the table 2 it can be stated that the correlation between real estate and stocks has been negative during the period. This finding is in line with the previous researches concluding that real estate has a low correlation with other assets (Hoesli & Hamelink, 2002). The same applies for the returns on stocks and bonds as the
correlation has been even more negative with the value being -0,169.
