22nd ERES Conference, June 24-27, 2015, Istanbul/TR

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1 22nd ERES Conference, June 24-27, 2015, Istanbul/TR
Session: P-1 (Real Estate Portfolio Management), Taskisla Room 216, 25.JUN :30-16:00 Comparative Study on REIT Returns In Borsa Istanbul By Using Single Index And Fama-French Methods*  S. Kestel (METU), Y. Coşkun (CMB), and B. Yılmaz (METU) * Senior Expert, Capital Markets Board of Turkey, 1995- PhD MRICS/FBHPA Member of Education and Research Committee of The Association of Appraisal Expert of Turkey (TDUB) (2015-) Member, Asset Management Committee of Investor Compensation Center of Turkey (2015-) Visiting Lecturer, Izmir University of Economics, 2012- Visiting Lecturer, University of Sarajevo School of Economics and Business (SEBS), 2012- Consultative Member, RICS Sustainability Task Force Europe, 2012- Presented by Y. COSKUN* Senior Specialist, Capital Markets Board of Turkey Also Presented, EconAnadolu International Conference June 10-12, 2015, Eskişehir, Turkey, June 10, 13:30-15:30, Lecture Room H

2 Research Overview Motivation/Contribution
Stylized Facts for Turkish REITs Market Literature Review Data Construction&Methodology&Model Outcomes Conclusion&Discussion&Implications

3 Motivation Paper explores -for the period 2008-2013-
(1) Diversification effects of Turkish REICs stocks in asset allocation by comparing REICs/Banks/Trust stocks in Borsa Istanbul (BIST) (2) To find best measure to observe REICs return by comparing single index (CAPM) and Fama-French three factor models Soru: Neden BIST 100 ile de compare etmiyoruz bank/trust stocks’a ilaveten?

4 Contributions (1) Fill the literature gap First comprehensive study on
Return variability/enhancement risk reduction analysis of Turkish REICs portfolio Utilizes innovative research methodology CAPM/Fama-French (FF) models comparision (2) Practical Contributions to local/Int’l PM Industry Input for REICs portfolio management (PM) for asset managers.

5 Stylized Facts for Turkish REITs Market

6 Real Estate and REICs in Turkey
Importance of Real Estate Economy Real estate economy has made positive contributions to GDP, employment, and mortgage credit volume etc. in last decade Weak Linkage Between RE and Finance Volume of housing credit/GDP ratio: 6.5%. Underdeveloped secondary mortgage market Underdeveloped mortgage-related insurance products Emerging REITs industry greater importance to improve RE-finance linkage in Turkey among its several other contributions.

7 Real Estate Investment Companies (REICs)
----In General Financial intermediary focusing to connect RE and fin. markets Establishes to invest income producing real estate assets as the public joint stock company at Borsa Istanbul (BIST). ----Prohibited Activities NOT perform construction works of real estates, operate real estates for profit, offer project development and supervision, lend credit, and permanently deal with short-term trading of real estates. REITs are grouped into these three categories: equity, mortgage, and hybrid. Equity REITs engage in a wide range of real estate activities, including leasing and development of property and tenant services. Mortgage REITs are engaged in lending money to real estate owners and operators or extend credit indirectly through the acquisition of loans or mortgage-backed securities. Hybrid REITs engage in equity and mortgage-related activities (Chaudhry et al., 2010: 225).

8 REICs in Turkey: Facts Book value may deviate from market value because of accumulated depreciation (Chiang et. al., 2006: 100)

9 REICs in Turkey: Facts TMV: total market value of REITs
(industry-level data deriving from aggregated outstanding shares*stock price calculation for each REIT) TA: total assets of REITs REP: proportion of real estates and real estate projects in the portfolio. According to explanation for the period of , REP covers aggregated proportion of real estates and real estate projects in the aggregated industry portfolio and the rest of the portfolio consist of debt instruments, reverse repo, and money market instruments. Statistics for the period of /9 involves three main portfolio instruments, namely proportions of real estates, real estate projects and rights, money and capital market instruments and affiliates. The REP statistics in the table consecutively involves these statistics for the /9 period. Real estates, real estate projects and rights in this period is in the first inner column of the relevant row.

10 WHY REICs HAVE BEEN BOOMING?
Tax Advantage REICs are exempt from corporate (20 %) tax& dividend withholding tax rate is % 0 for REICs. At investor level, sale of shares is subject to a 0% of withholding tax for all investors Dividend Policy REICs have no dividend payout requirements and hence have authority to define its own dividend policy. Regulation favors REICs Regulation Minimum ratio of issued capital declined to 25%, from 49 % in 2009 December.

11

12 LITERATURE REVIEW Asset Allocation/Diversification Benefits of REITs
Hudson-Wilson et al. (2003: 13) states that RE was initially viewed as a portfolio diversifier or risk reducer. Chandrashekaran (1999: 111) found ex-ante benefits of the diversification of REITs and REIT stocks have an important role to play in dynamic asset allocation strategies. Ciochetti et al. (2002: 568) found that institutional investors prefer larger/liquid REIT stocks. Chun et al. (2004: 317) found that RE diversification may pay off when consumption growth opportunities are low Lee and Stevenson (2005: 67) found that the benefits of REITs  appear to come from both its return enhancement and risk reduction benefits. Chen et al. (2005: 52) find that REITs do augment the mean-variance frontier and enlarge the investment opportunity set …economic significance of REIT investment from the perspective of asset allocation… Lu et al. (2013: 294) discusess that diversification benefits exist in internationally-mixed real estate portfolios. TC’de 2 tane tez vardı sanki lit olrk!!!

13 LITERATURE REVIEW Asset Allocation/Diversification Benefits of REITs
Booth and Broussard (2002: 121) found that portfolios consisting solely of bonds or REITs tend to exhibit lower return and less risk than 100 % stock portfolios. Fugazza et al. (2009: 375) find positive ex post welfare effects deriving from the inclusion of equity REITs in the asset menu. Chang and Chang (2013: 13) discuss that the size effect  is one of the reasons to explain portfolios of REITs outperform portfolios of common stocks Huang and Zhong (2013: 154, 190) diversification benefits of the asset classes of Commodity, REITs, and Treasury inflation-protected securities (TIPS) should be examined in a dynamic setting.

14 Literature Review Fama-French Model
FF (1995) showed stocks of small firms and those with high book to market ratio have provided above average returns (Brealey et al., 2008: 225) Observation of FF (1996) suggest that size or the book-to-market ratio may be proxies for exposures to sources of systematic (undiversifiable/market) risk not captured by CAPM beta, and thus result in return premiums. Fama and French point out that firms with high ratios of B/M value are more likely to be in financial distress and that small stocks may be more sensitive to changes in business conditions (Bodie et al., 2008: 212) -Fama and French add firm size and book-to-market ratio to the market index to explain average returns. -unsystematic(diversifiable/residual/specific) risk -Beta is a measure of the volatility, or systematic risk, of a security or a portfolio in comparison to the market as a whole. In other words, beta gives a sense of a stock's market risk compared to the greater market. Beta is also used to compare a stock's market risk to that of other stocks. Investment analysts use the Greek letter 'ß' to represent beta. Beta is calculated using regression analysis, and you can think of beta as the tendency of a security's returns to respond to swings in the market. A beta of 1 indicates that the security's price will move with the market. A beta of less than 1 means that the security will be less volatile than the market. A beta of greater than 1 indicates that the security's price will be more volatile than the market. For example, if a stock's beta is 1.2, it's theoretically 20% more volatile than the market. Read more: Follow on Twitter

15 FF & REITs Portfolio Reasons of Using FF model in REITs Portfolio
Its empirical usefulness is well-documented Its popularity makes it an ideal tool to check the robustness of existing results It is widely used in RE including Hsieh and Peterson (2000) and He (2002) The Fama-French (1993) three-factor model, while subject to endless criticism for lacking a theoretical foundation, has nevertheless taken on a greater role in describing the time-series of equity mutual fund returns and REIT returns (Peterson and Hsieh, 1997; Buttimer et al., 2005; Chiang et al., 2004, 2005; among many others). (Chiang et al, 2006: 96) Chiang, Kevin C.H., Kirill Kozhevnikov, Ming-Long Lee and Craig H. Wisen. (2006). REIT Mimicking Portfolio Analysis . INTERNATIONAL REAL ESTATE REVIEW Vol. 9 No. 1: pp

16 Studies Applying FF to return analysis in REITs
Xiao et al. (2012: 581) discuss that REITs returns  have been extensively studied to understand return generating process and time-series property of REITs Peterson and Hsieh (1997 : 323) find that mortgage REIT risk premiums are significantly related to the three stock market factors end two bond market factors in returns. Chiang et al. (2005) found, consistent with the findings of Peterson and Hsieh (1997), that the three-factor model is more useful than the single-factor model in explaining the variation in equity real estate investment trust EREIT returns and in providing stable estimates of market betas. Chiang et al. (2008: 54) discuss that ability of the CAPM or the Fama-French model to describe REIT returns is rather low Xiao et al., 2012 (581) found that REITs return exhibit the greatest sensitivity to market return, followed by large- and small-cap stock index, bond index and real estate index. Fama and French (1992) shows that covariance of portfolio return and market return does not explain changes on portfolio excess returns. They find that covariance has little or no power in terms of explaining cross-sectional variations in equity returns. First in the literature, beta may not fully capture cross-sectional differences in stock return Banz (1981: 16) found size effect as on average small NYSE firms have had significantly larger risk adjusted returns than large NYSE firms over a forty year period and this shows CAPM is misspecified. Then Fama and French (1992: 429) found that size and book-to-market equity provide a simple and powerful characterization ofthe cross-section of average stock returns. Crain (2011: 3) indicates that size effect varies over time or even disappears, especially since the 1980s.

17 DATA SOURCES/CONSTRUCTION MODEL CONSTRUCTION Diversification Benefits, CAPM&FF Models
-Theoretical Background -Applications to REITs Portfolio

18 DATA SOURCES/ CONSTRUCTION
DSM: debt securities market

19 CAPM ---The CAPM says that the expected return of a security or a portfolio equals the rate on a risk-free security plus a risk premium. If this expected return does not meet or beat the required return, then the investment should not be undertaken. A model that describes the relationship between risk and expected return and that is used in the pricing of risky securities. ---The general idea behind CAPM is that investors need to be compensated in two ways: time value of money and risk. The time value of money is represented by the risk-free (rf) rate in the formula and compensates the investors for placing money in any investment over a period of time. The other half of the formula represents risk and calculates the amount of compensation the investor needs for taking on additional risk. This is calculated by taking a risk measure (beta) that compares the returns of the asset to the market over a period of time and to the market premium (Rm-rf).

20 CAPM

21 CAPM ----CAPM’in özelliĞİ gereği bir menkul kıymetin beklenen getirisi risksiz faiz oranına, pazar risk primine ve menkul kıymetin betasına balıdır. ----CAPM’de bir kıymetin sistematik riski beta ile ölçülür. Beta katsayısı belirli bir hisse senedinin ne ölçüde pazarla birlikte hareket ettiini gösteren bir ölçüttür. CAPM Formülü E(ri) = rf + i [ E(rM) – rf ] E(ri) : Beklenen Getiri rf : Risksiz Faiz Oranı i : Beta [ E(rM) – rf ] : Risk Primi ---Risk ve beklenen getiri arasındaki değiş tokuş ilişkisini ölçme finansal ekonominin en önemli sorunlarından biridir(Campbell vd., 1997, s.181). 1960’lı yıllarla birlikte Markowitz tarafından ortaya konan Portföy Teorisi Sharpe, Lintner ve Tobin tarafından geliştirilmiş ve finansal bir varlığın riski ile beklenen getirisi arasındaki ilişkilerin daha kapsamlı olarak bilimsel tabana oturtulması sağlanmıştır. Bu teori finans literatüründe “Finansal Varlık Fiyatlama Modeli (Capital Asset Pricing Model-CAPM)” olarak adlandırılmaktadır.

22 CAPM- Portfolio of n-assets

23 Fama-French Methodology
------The first strategy is an analog to the Fama-French (1993) small-minus-big (SMB) strategy. --The mimicking portfolio SMBREIT is calculated as the difference between the return on the three small size REIT portfolios and the return on the three large size REIT portfolios. Following Fama and French, the three small and large sized portfolios are equally weighted in the construction of the monthly returns. The second strategy is an analog to the Fama-French value-minus-growth strategy, also referred to as high-minus-low (HML) strategy ---The mimicking portfolio of HMLREIT is calculated as the difference between the return on the three high book-to-market REIT portfolios and the return on the three low book-to-market REIT portfolios. The three high book-to-market and the three low book-to-market portfolios are equally weighted in the construction of the monthly returns. (Chiang et al, 2006: 100).

24 Fama-French Factors Indicators to determine
average difference of three big (B) and small (S) on small returns proportional to high (H), medium (M) and low (L) values  Small minus Big (SMB) average difference of two B and S portfolios proportional to H and L return values  High minus Low (HML) ---BIST senetlerinin aylık getirileri; en üst ve an alt % 25’lik dilimleri H, M, L olarak sınıflandı (Seza Danışoglu Hoca’nın yöntemi); sonra da Yukarıdaki işlem yapıldı. S ve B ise; yine BIST senetlerinin özsermaye/piyasa değeri endeksi oluşturuldu ve yarısı big ve diger yarısı da small olarak sınıflandı. KURAMSAL TEMEL - FF Fama ve French (1992) oluşturduğu portföyler aracılığı ile firma büyüklüğü, defter değeri/piyasa değeri oranı (DD/PD) finansal kaldıraç oranı fiyat kazanç oranı gibi değişkenler ile hisse senedi getirisi arasındaki ilişkiyi incelemiş ve büyüklük (piyasa değeri) ve DD/PD oranının getiriyi etkileyen önemli birer değişken olduğunu ortaya koymuştur. Buna göre büyüklük (PD) arttıkça hisse senedi getirisi azalmakta, DD/PD oranı arttıkça getiri artmaktadır. Diğer bir ifade ile yüksek DD/PD oranına sahip “değer” portföyleri, düşük DD/PD oranına sahip “büyüme” portföylerine göre daha fazla getiri elde etmektedirler. Bu çalışma temel alınarak daha sonraki çalışmalarda üç faktör varlık fiyatlama modeli geliştirilmiş ve bu iki değişken de modele dahil edilmiştir ( Fama ve French, 1993; Fama ve French, 1996). Bu modele göre hisse senedi getirisindeki değişim; piyasanın risksiz faiz oranı üzerindeki fazla getirisi, ölçek ve DD/PD oranları tarafından açıklanabilmektedir. Üç Faktör Fiyatlama Modelinin temel formu şu şekildedir: E (Ri) – Rf = βim (E(Rm) - Rf) + βis E(SMB) + βih E(HML) İncelenen portföyün risksiz faiz oranı üzerindeki beklenen getirisi, piyasanın risksiz faiz oranı üzerindeki getirisine (E(Rm) - Rf), piyasa değeri küçük hisse senetlerinden oluşturulan portföyün getirisi ile piyasa değeri büyük hisse senetlerinden oluşturulan portföyün getirisi arasındaki farka (SMB) ve DD/PD oranı yüksek hisse senetlerinden oluşturulan portföyün getirisi ile bu oranın düşük olduğu hisse senetlerinden oluşturulan portföyün getirisi arasındaki farka (HML) bağlı olarak değişmektedir. -CAPM’den-FF’ye geçiş teori; Varlık fiyatlamada yaygın bir şekilde kullanılan sermaye varlık fiyatlama modeli (CAPM) (Sharpe 1964, Lintner 1965 ve Mossin 1966) bir menkul kıymetten beklenen getiriyi, pazarın beklenen getirisi ile hisse senedinin betasına (hisse senedinin riskinin ölçüsü) bağlı olarak açıklamaktadır. Ancak yapılan birçok araştırmada sermaye varlık fiyatlama modelinin hisse senedi getirilerini açıklama gücü test edilmiş ve betadan başka değişkenlerin de açıklama gücüne sahip olduğu sonucuna ulaşmıştır (Canbaş ve Arıoğlu, 2008). Örneğin beklenen getiri ile fiyat-kazanç oranı arasındaki pozitif ilişki olduğu (Basu, 1983), piyasa değeri küçük olan firmaların daha yüksek getiriye sahip (Bhandari, 1988), defter değeri/piyasa değeri oranının hisse senedi getirisini açıklamada önemli bir açıklayıcı değişken olduğu (Chan ve diğerleri, 1991; Fama ve French, 1992) yapılan çalışmalarda tespit edilmiştir. Ülkemizde de benzer çalışmalar yapılmış ve ölçek, defter değeri/piyasa değerioranı, fiyat/kazanç oranı, finansal kaldıraç gibi değişkenlerin hisse senedi getirisini açıklamada önemli olduğu tespit edilmiştir (Er ve Vuran, 2012:112). CAPM’in hisse senedi getirilerini açıklamakta yetersiz kalması üzerine firmaya özgü özellikleri de kapsayan çok faktörlü modeller oluşturulmuştur. Ender COŞKUN& Önal ÇINAR (2014). ÜÇ FAKTÖR VARLIK FİYATLAMA MODELİNİN GEÇERLİLİĞİ: BORSA İSTANBUL’DA BİR İNCELEME. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, Cilt: 28, Sayı: 4,

25 EMPRICAL RESULTS

26 Descriptive Statistics
Mean Median Standard Deviation Skewness Kurtosis ALGYO 1.577 1.948 12.390 -0.020 1.001 AVGYO 4.259 0.000 24.334 0.592 4.447 DGGYO 3.596 1.266 18.010 2.912 13.643 ISGYO 1.988 2.299 10.732 -0.014 1.728 NUGYO 3.895 -1.081 18.675 1.714 4.761 OZGYO 1.039 -1.282 18.004 2.680 14.947 PEGYO -1.382 -1.613 13.161 0.061 2.191 VKGYO 3.834 0.707 18.769 0.851 2.648 YGYO 0.479 -1.493 18.472 0.937 2.938 YKGYO 1.075 1.869 14.767 -0.963 3.826 SAFGY 1.859 0.741 15.364 1.492 5.441 Mean (average return); observation period’da mean genelde düşük. En yüksek AVGYO; onun da S’i coşmuş. High standart deviation

27 -Return behaviour; highly volatile&similar patterns
-AVGYO has the highest oscilation (volatility) -İSGYO has lower return volatility

28 Correlation and Skewness
ALGYO AVGYO DGGYO ISGYO NUGYO OZGYO PEGYO VKGYO YGYO YKGYO SAFGY Market 1 0.184 0.371 0.011 0.606 0.151 0.337 0.470 0.120 0.114 0.355 0.377 0.097 0.166 0.347 0.221 0.502 0.240 0.304 0.465 0.410 0.530 0.353 -0.125 0.157 0.266 0.259 0.079 0.176 0.356 0.254 0.159 0.456 0.245 0.345 0.558 0.121 0.561 0.057 0.447 0.617 0.406 0.279 0.581 0.288 0.459 0.566 0.238 0.207 0.359 0.287 0.372 0.420 0.243 0.380 0.565 0.142 0.322 0.706 0.455 0.440 0.605 0.163 0.511 0.630 0.401 -Tablo: Market ile korelasyon; ISGYO (0.706), PEGYO ve YKGYO en yuksek. Genel olarak market return ile secilen 11 GYO’nun korelasyonu genelde yuksek. - Box Plot: ALGYO, IS GYO, PEGYO normal dağılıma yakın (approximately normal distribution)

29 Diversification Effects of REICs
Sistematik (market) risk elimine edilemiyor. 10 adet senetten oluşan banka, MKYO ve GYO portföylerinde için senetlerin riskleri büyükten küçüğe doğru eşit ağırlıklı sıralanarak portföye dahil edildiğinde portföy riski en fazla MKYO’da azalırken, GYO senetlerinin risk azaltıcı etkisi banka hisselerinin üstünde kalmaktadır. Bu durum GYO senetlerinin portföy yönetiminde getiri artırıcı etkisine işaret etmektedir. -Since e_i s are independent, and all have zero expected value, the law of averages can be applied to conclude that as more and more stocks are added to the portfolio, the firm-specific components tend to cancel out, resulting in ever-smaller nonmarket risk. Such risk is thus termed diversifiable. - Because the e i s are uncorrelated, 𝜎_𝑝^2=1/𝑛 𝜎^2 (𝑒_𝑖). Average of the companies variance. (Karekökünü alırsak standard sapmasını buluruz.) - as diversification increases, the total standard deviation of a portfolio approaches the systematic standard deviation The impact of diversification is analyzed in three industries. If an investor considers only one market such as banks or Trust company. With the number of stocks the risk (sigma) reduces but does not get closer to zero because of the systematic risk. REITs which are composed of equally weighted portfolio yield a better risk diversification compared to the banks, yet remains above the trust company performance slightly.

30 CAPM Outcome of REITs p-value Ajd R^2 t Stat Beta Beta t stat alpha
p-value Ajd R^2 t Stat Beta Beta t stat alpha alpha Company Structure ALGYO 0.0000 31.03% 6.083* 0.852 0.3682 0.424 defensive AVGYO 0.2055 0.78% 1.277 0.420 1.2631 3.420 DGGYO 0.0034 9.23% 3.023* 0.705 1.3291 2.549 ISGYO 49.17% 8.853* 0.919 0.9208 0.786 NUGYO 19.70% 4.541* 1.029 1.4024 2.614 aggressive OZGYO 18.35% 4.356* 0.962 -0.194 PEGYO 35.81% 6.755* 0.974 -2.623 VKGYO 0.1448 1.44% 1.473 0.372 1.4583 3.029 YGYO 25.22% 5.290* 1.148 -0.888 YKGYO 38.97% 7.217* 1.136 -0.284 SAFGY 0.0002 15.06% 3.896* 0.750 0.4926 0.780 * t-stat>2 Agresive if Beta>1 Defensive if Beta<1 P Value; 0.05’den büyükse model anlamsız oluyor. AVGYO ve VKGYO modelleri anlamsızdır. Statistically insignificant. Adjusted R2; Parametrelerin modeli açıklama gücünü veriyor. Genelde düşük, en yüksek İSGYO. T-Stat beta; 2’den küçükse CAPM’deki bagımsız degisken olan market return degiskeni anlamsız oluyor (2’den buyukse Statistically significant). AVGYO ve VKGYO Statistically insignificant Beta; market return’un katsayısı, genelde kağıtların defensive oldugunu gosteriyor. T Stat Alpha; ıntercept’ın istatistiğini gosteriyor. 2’den buyukse Statistically significant. Olagan dışı getirisi yok GYO senetlerinin anlamına geliyor bu. Alpha; ıntercept Company Structure

31 CAPM to Fama-French Model: Outcome
Significance F t stat beta t stat alpha alpha t stat SMB t stat HML ALGYO 0.0000* 36.4 5.548* 0.909* 0.168 0.237 1.918 0.604 -0.033 -.011 AVGYO 0.3851 0.2 0.740 0.288 0.877 2.952 1.400 1.045 0.342 0.259 DGGYO 0.1056 5.5 2.440* 0.686 1.217 2.954 -0.312 -0.168 0.100 0.055 ISGYO 52.5 7.981* 0.941 0.502 0.510 1.201 0.272 1.494 0.343 NUGYO 0.0016* 19.4 3.540* 0.970 1.627 3.852 2.083* 1.097 1.308 0.698 OZGYO 0.0002* 25 3.571* 0.938 -.490 -.111 3.046* 1.538 1.533 0.784 PEGYO 42.6 5.990* 1.015 -.518* -3.68 3.103* 1.011 2.162* 0.714 VKGYO 0.0847 6.31 2.171* 0.576 1.626 3.727 0.490 0.250 -0.840 -.434 YGYO 36.5 4.698* 1.156 -.847 -.798 3.609* 1.7056 1.379 0.660 YKGYO 47.7 6.838* 1.216 -.979 -.495 2.977* 1.0172 1.169 0.405 SAFGYO * 22.55 3.749 0.792 -.049 -.0898 2.314* 0.939 0.878 0.361 Temel Soru: CAPM’den (single index model), FF’e (three factor model) geçilmesi durumunda her bir REIT stock return’ünü daha mı iyi açıklıyoruz, açıklama gücü arttı mı? (modele daha fazla değişken eklenince modelin açıklama gücü artıyor mu). R2 analizi kritik. Ozet: AVGYO, DGGYO ve VKGYO modelleri F’den ötürü anlamsız. Bütün kağıtlar için alfa (intercept) anlamsız (t Stat Alpha’ya göre). HML için (t Stat HML sonucuna göre) sadece PEGYO ve SMB için de (t stat SMB’ye göre) NUGYO, OZGYO, PEGYO, YGYO, YKGYO, SAFGYO anlamlı. Yani F, t stat SMB ve t Stat HML’ye göre SADECE PEGYO ANLAMLI. Significance F (p degeri); 0.05’den büyükse statistically insignificant). AVGYO, DGGYO ve VKGYO anlamsız. Adj R2; Genelde artıyor. Ama parametreler istatistiksel olarak genelde anlamsız. Dolayısıyla return değişimini açıklamak için iyi değişkenler değil. FF İŞLEMİYOR!! T-Stat beta;2’den büyükse anlamlı. T-stat alpha; 2’den büyükse anlamlı. Hepsi anlamsız, beklenen bir durum. Cunku normal getiri dısı getiri beklentimiz yok. Kırmızı. T-stat beta SMB; 2’den büyükse anlamlı. T-stat beta HML; 2’den büyükse anlamlı.

32 CAPM & Fama-French Comparision
CAPM Fama- French alpha Beta Error SMB HML ALGYO 0.424 0.852 10.32 31.03 0.237 0.909* 0.604 -0.011 10.81 36.4 AVGYO (Insignificant CAPM&FF) 3.420 0.420 24.27 0.78 2.952 0.288 1.045 0.259 25.73 0.2 DGGYO (Insignificant FF) 2.549 0.705 17.19 9.23 2.954 0.686 -0.168 0.055 18.55 5.5 ISGYO 0.786 0.919 7.65 49.17 0.510 0.941 0.272 0.343 7.77 52.5 NUGYO 2.614 1.029 16.71 19.70 3.852 0.970 1.097 0.698 18.08 19.4 OZGYO -0.194 0.962 16.28 18.35 -0.111 0.938 1.538 0.784 17.34 25 PEGYO (Significant CAPM&FF) -2.623 0.974 10.63 35.81 -3.680 1.015 1.011 0.714 11.20 42.6 VKGYO (Insignificant CAPM&FF) 3.029 0.372 18.62 1.44 3.727 0.576 0.250 -0.434 17.51 6.31 YGYO -0.888 1.148 15.99 25.22 -0.798 1.156 1.7056 0.660 16.25 36.5 YKGYO -0.284 1.136 11.60 38.97 -0.495 1.216 1.0172 0.405 11.74 47.7 SAFGY 0.780 0.750 14.19 15.06   0.792   0.939 0.361  13.94 22.55  Sonuçlar 1) CAPM’den FF’ye geçerken; sadece PEGYO anlamlı bir model oluşumu veriyor. Kırmızı. AVGYO ve VKGYO (CAPM&FF’de) ve DGGYO’da (FF’de) anlamsız oluyor. Morlular. Önceki slayttaki mavili olan NUGYO, OZGYO, PEGYO, YGYO, YKGYO, SAFGYO da FF’de sadece SMB için (t stat SMB’ye göre) anlamlı; ama bunlar arasında sadece PEGYO model olarak anlamlı. d) Nafile bir yorum olarak; Both models (CAPM & FF) yield similarities and differences. Non-market return parameters illustrates that AVGYO, DGGYO, NUGYO, PEGYO, VKGYO contribute around the same amount on the returns with similar signs. 2) İlave Açıklama The firms found to be “aggressive” have beta(SMB) over 1, and beta(HML) around 0.70. CAPM detects the agressivity of the firms which is detected by F&F by distress state.

33 Conclusion & Discussion
(1) Diversification effect is well captured by REICs compared to banks (2) Best Measure (CAPM vs. FF); CAPM informs agressivity of firm agreement with the company structure captures the significance almost all, except AVGYO&VKGYO Overall CAPM model expresses the market effect significantly Fama & French Informs on size & state of firms (disclosure is subject to confidentiality) Found some evidences FF improves R2 values in most stocks SMB is the most significant variable in the models compared to HMB Only PEGYO is expressed fully by the model So,FF model is not significant for each stock prob. because of certain characteristics of firm So, which one is better? It depends on firm specific analysis. But, it seems that CAPM works in most cases.

34 Practical Implications for PM
The study provides significant inputs for PM Providing trend analysis for the industry Providing info on time series features of selected REICs Classifiying REICs based on agressivity, size, B/M Providing PM strategy based on REICs diversification Providing firm specific analysis on return variability (CAPM&FF effects)

35 Thank you very much for your attention
For Discussion/More Information: Personel web-sites, you may contact with Y. COSKUN E: P: ( ) A: Eskişehir Yolu 8.Km No: Ankara/Turkey. W:

36 Some Points - Analyses of Turkish REIT market based on data between Single index model yields information on market and non-market indicators Fama-French 3-factor models yields the impact of the average difference of the extremes on the return. Market and non-market parameters give more specific knowledge on the assets available in system

37 Selected REITs REIT CODE ATAKULE GAYRİMENKUL YATIRIM ORTAKLIĞI AGYO
SAF GAYRIMENKUL YATIRIM ORTAKLIGI AS SAFGY ALARKO GAYRİMENKUL YATIRIM ORTAKLIĞI A.Ş. ALGYO AVRASYA GMYO AVGYO VAKIF GAYRİMENKUL YATIRIM ORTAKLIĞI A.Ş. VKGYO PERA GAYRIMENKUL YATIRIM ORTAKLIGI AS PEGYO DOĞUŞ GAYRİMENKUL YATIRIM ORTAKLIĞI A.Ş. DGGYO NUROL GAYRIMENKUL YATIRIM ORTAKLIGI A.S NUGYO YAPI KREDİ KORAY GAYRİMENKUL YATIRIM ORTAKLIĞI A.Ş. YKGYO IS GAYRIMENKUL YATIRIM ORTAKLIGI AS ISGYO YESIL GAYRIMENKUL YATIRIM ORTAKLIGI AS YGYO - REITs are selected based on data availability.

38 BANKS & TRUST COMPANİES
AKBANK ARTI ALBRK ATAGY ALNTF ATLAS ASYAB COSMO DENİZ ECBYO FNBN ETYAT GARAN FNSYO HALKB GRNYO ISBNK ISGSY KLNMA ISYAT SKBNK OYAYO TEBNK RHEAG TEKST TCRYO TESKB VKBYO VAKBN YKBNK

39 Fama-French Model REITs
Significance F t stat beta t stat alpha alpha t stat SMB t stat HML Firm size Firm State  Size match ALGYO 0.0000* 36.4 5.548* 0.909* 0.168 0.237 1.918 0.604 -0.033 -.011 S ND  ☺ AVGYO 0.3851 0.2 0.740 0.288 0.877 2.952 1.400 1.045 0.342 0.259 D DGGYO 0.1056 5.5 2.440* 0.686 1.217 2.954 -0.312 -0.168 0.100 0.055 ISGYO 52.5 7.981* 0.941 0.502 0.510 1.201 0.272 1.494 0.343 NUGYO 0.0016* 19.4 3.540* 0.970 1.627 3.852 2.083* 1.097 1.308 0.698 OZGYO 0.0002* 25 3.571* 0.938 -.490 -.111 3.046* 1.538 1.533 0.784 PEGYO 42.6 5.990* 1.015 -.518* -3.68 3.103* 1.011 2.162* 0.714 VKGYO 0.0847 6.31 2.171* 0.576 1.626 3.727 0.490 0.250 -0.840 -.434 B YGYO 36.5 4.698* 1.156 -.847 -.798 3.609* 1.7056 1.379 0.660 YKGYO 47.7 6.838* 1.216 -.979 -.495 2.977* 1.0172 1.169 0.405

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