Encyclopedia of Finance Part 14 ppt

Chapter 25 REVIEW OF REIT AND MBS CHENG-FEW LEE, National Chiao Tung University, Taiwan and Rutgers University, USA CHIULING LU, Yuan Ze University, Taiwan Abstract In this article, the history and the success of Real Estate Investment Trusts (REITs) and Mortgage- Backed Securities (MBS) in the U.S. financial market are discussed. Both securities are derived from real estate related assets and are able to increase the liquidity on real estate investment. They also provide investors with the opportunity to diversify portfolios because real estate assets are relatively less volatile and less correlated to existing investment instruments. Therefore, REITs and MBS enhance the width and the depth of the financial market. Keywords: REIT; MBS; real estate; mortgage; FHA; VA; Fannie Mae; Ginnie Mae; Freddie Mac; prepayment; public securities association 25.1. Introduction The revolution in the American real estate market was enhanced by securitization. For real properties, public listed Real Estate Investment Trusts (REITs) create tradable and standardized securities for individuals and institutional investors while providing alternative investments for diversification. Through the capital market, real estate practitioners have more reliable funds, and no longer limit themselves to bank loans. For real estate related loans, Mortgage-Backed Securities (MBS) establish a capital conduit linking borrowers and lenders directly, bypassing financial intermediaries. MBS also release the burden of the bank from holding long-term mortgage debt and bearing credit risk. In addition, MBS create a secondary market of mortgage debt, and provide an alternative investment. Although, REITs and MBS are generated under different backgrounds and developed under different circumstances, they play a significant role in real estate financing. Nevertheless, challenges in real estate securitization have been important issues for the past four decades and will continue to do so in the future. In this chapter, the development of REITs and MBS for the past forty years in the United States is described. In addition, empirical findings in the literature are also examined. 25.2. The REIT Background A REIT is a creation of the federal tax code that permits an entity to own real properties and mortgage portfolios. REITs incur no corporate tax on transfers of profits to holders of beneficial interest given certain provisions within the Internal Rev- enue Code are met. To qualify as a REIT for tax purposes, the trust must satisfy many requirements including asset, income, distribution, and ownership restrictions. For example, a REIT must have a minimum of 100 shareholders; invest at least 75 percent of the total assets in real estate assets; derive at least 75 percent of gross income from rents, or interest on mortgages on real property; and pay at least 90 percent of the taxable income in the form of shareholder dividends. Basically, if any company fails to qualify as a REIT, the company cannot be taxed as a REIT until five years from the termination date. To know REITs better, this study begins with the origin of REITs, then dis- cusses the related regulation changes and current development, and finally examines relevant accounting and financial issues. REITs were created by the U.S. Congress in 1960 to enable small investors to become involved in real estate development which was previously limited to the affluent. However, for the first three decades, REITs were recognized as passively managed firms, and were not competitive with real estate limited partnerships. Until the Tax Reform Act of 1986, REITs were empowered to not only own, but also operate and manage their own assets. In addition, the Act reduced tax shelter opportunities for real estate partnerships. Thereafter, it was possible for REITs to be self-managed rather than managed by external advisors, and became more attractive to investors. For the distribution rule, REITs were required to distribute at least 95 percent of taxable income as dividends. However, in 1999, the REIT Modernization Act changed the minimum requirement to 90 percent, which was consistent with the rules from 1960 to 1980. According to the National Association of REIT (NAREIT), there are over 800 REITs and 171 of them were traded on the NYSE, AMEX, and NASDAQ during 2003. The market capitalization and the number of publicly traded REITs from 1971 to 2003 are illustrated in Figure 25.1. Since inception, REITs played a limited role in the capital market until the end of 1980s. At the end of 1980s, the combined effect of overbuilding, the savings and loan crisis, and the impact of the Tax Reform Act of 1986 led to the expansion of REITs. Investors realized that tradable and liquid real estate investment is crucial during recessions and REITs happened to fit these needs. Figure 25.1 shows that the total market capitalization of REITs amounted to more than US$224 billion as of December 31, 2003. Because real estate maintains greater residual value than other assets such as computers or ma- chinery, and real estate may appreciate at the same time, applying depreciation used in normal earnings measures resulted in underestimated cash flows for REITs. Bradley et al. (1998) observed that REITs’ depreciation expenses are roughly equal to net income, and cash flow available for distribution is about twice the required payout. Consequently, agency problems caused by free cash flows arise (see Lu and Shen, 2004). In order 0 50 100 150 200 250 1971 1975 1979 1983 1987 1991 1995 1999 2003 Year # of REITs 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000 220,000 240,000 Market Capitalization (millions) Market Capitalization # of REITs REIT equity market capitalization outstanding Figure 25.1. REIT equity market capitali zation outstanding Source: NAREIT REVIEW OF REIT AND MBS 513 to estimate cash flows and evaluate REITs’ performance more accurately, Funds From Oper- ations (FFO) is designed to be another supplemental measure relative to Earnings Per Share (EPS). The NAREIT defines FFO as net income excluding gains or losses from sales of property or debt restructuring, and adds back the depreciation of real estate. A high dividend yield (7 percent on average in 2002) is one attraction for investors to invest in REITs. Figure 25.2 shows the dividend payout ratios as a percentage of the FFO. This ratio de- creased in the 1990s, but has increased since 2000. This trend indicates that REITs reserved more cash at the end of 1990s. At the end of 2000, only 63 percent of the FFO was distributed to shareholders. This ratio increased to 81 percent at the end of 2003. Basically, the dividend policy of REITs is quite different from that of nonfinancial firms (see Lee and Kau, 1987) and is highly regu- lated by the IRS. Compared to income-producing commercial real estate, REITs are financed on a more conser- vative basis. Generally, REITs finance their pro- jects with about half debt and half equity. According to the NAREIT, the average debt ratio for equity REITs is 41.8 percent as of the fourth quarter of 2003 and about two-thirds of REITs with senior unsecured debt ratings are investment grade. Figure 25.3 shows that the average leverage ratio of REITs has increased from 1996 to 2003, but not more than 55 percent. The coverage ratios defined as dividing EBITDA by interest expenses is over 3, from 1996 to 2003. The valuation of REITs depends on several criteria including management quality, dividend coverage from FFO, anticipated growth in FFO, and economic outlook. Fortunately, because public REITs are traded everyday, stock prices reflect real time pricing. Therefore, a capital asset pricing model could be employed to calculate REITs’ expected returns and systematic risk. According to previous research, REITs underperform in the market on a nominal basis and earn fair returns on a risk- adjusted basis. Glascock and Hughes (1995) found that the REIT betas are consistently below the market (¼ 1) and equal to 0.377 for the entire period from 1972 to 1991. Figure 25.4 compares Q1 Q2 Q3 Q4 1994 Q1 Q2 Q3 Q4 1995 Q1 Q2 Q3 Q4 1996 Q1 Q2 Q3 Q4 1997 Q1 Q2 Q3 Q4 1998 Q1 Q2 Q3 Q4 1999 Q1 Q2 Q3 Q4 2000 Q1 Q2 Q3 Q4 2001 Q1 Q2 Q3 Q4 2002 Q1 Q2 Q3 Q4 2003 1994–1999 quaters are based on partial data for the Top 100 Equlty REITs 60 65 70 75 80 85 90 95 REIT payout rations, dividends as a percent of FFO (Quarterty, 1994–2003:Q4) Percent 89 88 85 83 90 88 86 84 88 83 82 79 81 78 75 74 74 72 72 69 71 68 68 67 68 65 66 63 68 65 72 73 68 68 71 72 74 78 81 86 Figure 25.2. REIT payout ratios, dividends as percent of FFO Source: NAREIT 514 ENCYCLOPEDIA OF FINANCE the dividend yield of REITs with a 10-year constant maturity treasury yield and indicates that the former was higher for most of time during the past 15 years. In addition, the difference between these two yields has increased in the 2000s. Real estate investment has been considered good for hedging inflation. Fortunately, REITs investment still pre- serves this function. Figure 25.5 shows the trend of Composite REIT leverage and coverage ratios (End of quarter, 1996:Q1 to 2003:Q4) Coverage Ratios 5.0 4.5 4.0 3.5 3.0 2.5 EBITDA/(Interest Expense) EBITDA/(Interest+Preferred) Debt/(Total Market Cap) (Debt ratio uses right scale) (Coverage ratios use left scale) Sorurce: SNL Securities, National Association of Real Estate Investemnt Trusts. 1996 1997 1998 1999 2000 2001 2002 2003 30 35 40 45 50 55 Percent Figure 25.3. Composite REIT leverage and coverage ratios Equity REIT dividend yield vs. 10-year constant maturity treasury yield January 1990−October 2004 Percent Equity REITs 10-Year treasury 12 11 10 9 8 7 6 5 4 12 2 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Figure 25.4. Equity REIT dividend yield vs. 10-year constant maturity treasury yield Source: NAREIT REVIEW OF REIT AND MBS 515 the NAREIT equity REIT price index versus the Consumer Price Index from 1990 to 2004. In the long run, the equity REIT price index was higher than the Consumer Price Index. Consequently, REITs are a viable inflation hedge instrument. REITs have helped increase the liquidity of the real estate market and have become viable investments for diversification purposes by institutional and individual investors. It is anticipated that this industry will continue to expand, and more coun- tries will follow this track. 25.3. The MBS Story The secondary mortgage market has evolved and grown in the United States for the last three decades. MBS provide mortgage originators with liquidity and facilitate a geographic flow of funds from places with a surplus of savings to where home mortgages are needed. The strong support of the federal government has played the most important role in the development of the MBS market. Therefore, the government’s sponsorship in the process and then the market structure and participants are examined. The MBS pricing and related risk will also be illustrated. 25.3.1. The Special Contributions of the Government-Sponsored Enterprises The three most important events in the evolution of the secondary mortgage market were the creation of Federal Housing Administration (FHA) in 1934, the chartering of the Federal National Mortgage Association (FNMA or Fannie Mae) in 1938, and the origination of Veterans Adminis- tration (VA) in 1944. The FHA and the VA helped set up the mortgage underwriting standard and provided mortgage default insurance or guarantees. The FNMA was transformed into a privately owned and managed organization under the Housing and Urban Development Act of 1968. After that, government ownership was eliminated and the FNMA became solely owned by private investors. This Act also created the Government National Mortgage Asso- ciation (GNMA or Ginnie Mae) to deal with sub- sidized mortgage purchases for special federal housing programs. Though the secondary mortgage market based on pools of FHA or VA home mortgages was well established, a market for conventional loans did not exist. The Federal Home Loan Mortgage NAREIT equity REIT price index vs. consumer price index (January 1961−October 2004) Indexed at December 1960 = 100.0 0 50 100 150 200 250 300 350 NAREIT equlty price index Consumer price index 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Figure 25.5. NAREIT equity REIT price index vs. consumer price index Source: NAREIT 516 ENCYCLOPEDIA OF FINANCE Corporation (FHLMC or Freddie Mac) chartered under Title III of the Emergency Home Finance Act of 1970 provided liquidity for conventional loans as well as for FHA–VA mortgages. 25.3.2. Market Participants Basically, there are four entities involved in the operation of the secondary mortgage market. The first entity is the mortgage originator such as mortgage bankers, thrifts, and commercial banks. They perform loan underwriting and establish loan terms in the primary market, and then sell mortgages to replenish funds. The second entity involved is the FHA and the VA, which perform credit enhancement functions by providing insurance or guarantees. The third entity in the process is the mortgage buyers. Prior to the mid-1950s, buyers were life insurance companies or thrifts. However, after the mid-1950s, both the FNMA and the FHLMC became the predominant pur- chasers. The FNMA and the FHLMC in turn created mortgage pools for securitization. The fourth entity is the end investors such as REITs, pension funds, mutual funds, IRAs, life insurance companies, or even the mortgage originators themselves. 25.3.3. MBS Pricing According to Bartlett (1989), MBS are a hybrid investment in which a portfolio holding of an MBS consists of one part a standard-coupon bond and one part a short-call option. Since the homeowner has the right to call (prepay) the mortgage at any time, the MBS investor is in effect short the implied call. Therefore, Bartlett defines the MBS price as follows: MBS Value ¼ Non-callable Bond Value À Call Option Value: Unlike traditional debt securities, the cash flow of MBS is unpredictable due to unexpected delayed payment, prepayment, or default. Because borrowers hold options, not only is the expected maturity of MBS more difficult to estimate relative to the other straight bond investments, but also the exact timing and amount of the cash flow is un- known in advance. Therefore, the valuation of the MBS turns out to be more complicated. The factors related to the pricing of MBS include but are not limited to interest rate risk, default risk, risk of delayed payment, and prepayment risk. Prepayment ratios most significantly effect the predication of cash flow. Therefore, several models have been developed to estimate this rate. Those models include the 12-year prepaid life (based on FHA data assumption), constant prepayment rate (CPR) assumption, FHA prepayment experience, the Public Securities Association (PSA) model, and the econometric prepayment models (see Brueggeman and Fisher, 2001). Kau et al. (1985, 1987, 1990a, 1990b, 1992, 1993, 1995) have developed several models to analyze different mortgages and MBS. The research is continuing on prepayment estimation, but no conclusive model has been developed as of yet. Figure 25.6 presents the outstanding volume of public and private bond market debt from 1985 to 2003. The outstanding level of mortgage related debt was US$5.309 trillion in 2003. US$3.526 trillion (66.4 percent) was debt related to Freddie Mae, Fannie Mae, and Ginnie Mae. The outstanding level of corporate debt and U.S. Treasury bonds was US$4.462 trillion and US$3.575, re- spectively. Obviously, MBS market-related securities were higher than the corporate bond and U.S. Treasury bond markets. This trend indicates the success and need for the mortgage secondary market. Figure 25.7 shows the Commercial MBS yield spread defined as the difference between AAA- rated 10-year CMBS and 10-year Treasuries. The spread once reached more than 200 basis points, but has declined to less than 80 basis points in 2004. The yield on CMBS is still higher than that of Treasuries even though the number had declined. Given similar risk level, mortgage-related securities do provide investors with better alternative investment. REVIEW OF REIT AND MBS 517 25.4. The Impact of Securitization on Financial Institutions The process of mortgage securitization helps financial institutions to manage their asset portfolios, interest rate exposure, capital requirement, and deposit insurance premiums. Saunders and Cor- nett (2003) state that asset securitization provides a mechanism for financial institutions to hedge the interest rate risk. They point out that the process of Outstanding level of public & private bond market debt 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Year Billion of dollars U.S. treasury Mortgage- related Corporate Figure 25.6. Outstanding level of public and private bond market debt Source: The Bond Market Association CMBS yield spreads (AAA-rated, 10-year CMBS less 10-year treasuries) Basis points 220 200 180 160 140 120 100 80 60 40 Dec-97 Jun-98 Dec-98 Jun-99 Dec-99 Jun-00 Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Figure 25.7. CMBS yield spreads Source: Morgan Stanley 518 ENCYCLOPEDIA OF FINANCE securitization not only makes asset portfolio of financial institutions more liquid, but also provides an important source of fee income. Saunders and Cornett (2004) indicate that by increasingly relying on securitization, banks and thrifts have begun to move away from being asset transformers to become asset brokers. Therefore, the differences between commercial banking and investment banking began to diminish as asset securitization expanded. 25.5 Conclusion Equity securities, debt instruments, and derivatives have become popular investment or hedging ve- hicles during the past century. However, real estate, which is the most conventional investment asset, lost favor to liquid and tradable securities among investors. Not until the 1970s did institutional investors start to show an interest in real estate in the United States (see Bernstein, 2003). The creation of REITs and MBS has changed the way of real estate financing in the United States and has also facilitated investment in real estate market. REITs and MBS were developed to com- plete the market, and indeed fulfill the objectives of an affordable housing policy for government and that of an asset allocation for the portfolio management purpose. REFERENCES Bartlett, W.W. (1989). Mortgage-Backed Securities: Products, Analysis, Trading. Englewood Cliffs, NJ: Prentice Hall. Bernstein, P. (2003). ‘‘Real estate matters.’’ The Journal of Portfolio Management: Special Real Estate Issue,1. Bradley, M., Capozz a, D., and Seguin, P. (1998). ‘‘Divi- dend Policy and Cash-flow Uncertainty.’’ Real Estate Economics, 26: 555–580. Brueggeman, W. and Fisher, J. (2001). Real Estate Finance and Investments. Irwin: McGraw-Hill. Glascock, J. and Hughes, W.T. (1995). ‘‘NAREIT iden- tified exchange listed REITs and their performance characteristics, 1972–1990.’’ Journal of Real Estate Literature, 3(1): 63–83. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epper- son, J.F. (1985). ‘‘Rational pricing of adjustable rate mortgages.’’ AREUEA Journal, 13(2): 117–128. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epper- son, J.F. (1987). ‘‘The valuation and securitization of commercial and multifamily mortgages.’’ Journal of Banking and Finance, 11: 525–546. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epper- son, J.F. (1990a). ‘‘Pricing commercial mortgages and their mortgage-backed securities.’’ Journal of Real Estate Finance and Economics, 3(4): 333–356. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epper- son, J.F. (1990b). ‘‘The valuation and analysis of adjustable rate mortgages.’’ Management Science, 36: 1417–1431. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epperson, J.F. (1992). ‘‘A generalized valuation model for fixed-rate residential mortgages.’’ Jour- nal of Money, Credit, and Banking, 24(3): 279–299. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epperson, J.F. (1993). ‘‘Option theory and floating rate securities with a comparison of adjustable- and fixed-rate mortgages.’’ Journal of Business, 66(4): 595–617. Kau, J.B., Keenan, D.C., Muller, III W.J., and Epperson, J.F. (1995). ‘‘The valuation at origination of fixed-rate mortgages with default and prepayment.’’ Journal of Real Estate Finance and Economics, 11: 5–36. Lee, C.F. and Kau, J.B. (1987). ‘‘Dividend payment behavior and dividend policy of REITs.’’ The Quar- terly Review of Economics and Business, 27: 6–21. Lu, C. and Shen, Y. (2004). ‘‘Do REITs pay enough dividends?’’ Unpublished working paper, Depart- ment of Finance, Yuan Ze University. Saunders, A. and Cornett, M.M. (2003). Financial Institutions Management. Irwin: McGraw-Hill, 733–768. Saunders, A. and Cornett, M.M. (2004). Financial Markets and Institutions, Irwin: McGraw-Hill, 645–667. REVIEW OF REIT AND MBS 519 Chapter 26 EXPERIMENTAL ECONOMICS AND THE THEORY OF FINANCE HAIM LEVY, Hebrew University, Israel Abstract Experimental findings and in particular Prospect Theory and Cumulative Prospect Theory contradict Expected Utility Theory, which in turn may have a direct implication to theoretical models in finance and economics. We show growing evidence against Cumulative Prospect Theory. Moreover, even if one accepts the experimental results of Cumulative Pro- spect Theory, we show that most theoretical models in finance are robust. In particular, the CAPM is intact even if investors make decisions based on change of wealth, employ decision weights, and are risk-seeking in the negative domain. Keywords: decision weights; prospect theory; cumulative prospect theory; certainty effect; expected utility; stochastic dominance; prospect stochastic dominance; value function; Markowitz stochastic dominance; configural weights 26.1. Introduction Theoretical models in finance are based on certain assumptions regarding the investors’ characteristics and their investment behavior. In particular, most of these models assume rational investors who always prefer more than less consumption (money), and who maximize von Neumann– Morgenstern (1944) expected utility. The main models in finance that we relate to in this paper are: (1) The Modigliani–Miller (1958) relationship between the value of the firm and its capital structure. (2) Black–Scholes (1973) option pricing. (3) Ross’s (1976) Arbitrage Pricing Model (APT). (4) The Sharpe–Lintner (1964 and 1965, respect- ively) Capital Asset Pricing Model (CAPM). (5) Stochastic Dominance—the various investment decision rules (for a review, see Levy 1992, 1998). (6) Market Efficiency – though recently some empirical studies reveal (short term) autocorrela- tions, most academic research still assumes that the market is at least ‘‘weakly efficient,’’ namely one cannot employ ex-post rates of return to establish investment rules that provide abnormal returns. Of course, if this is the case, there is no room for ‘‘technicians’’ and charterists who try to predict the market based on past rates of return. (For the market efficiency hypotheses see Fama, 1965, 1991). In this paper, we analyze the impact of recent experimental finding, and particularly the implication of Prospect Theory (PT) (see Kahneman and Tversky, 1979) (K&T), Cumulative Prospect The- ory (CPT) (see Tversky and Kahneman, 1992 (T&K), and Rank-Dependent Expected utility (RDEU) (see Quiggin 1982, 1993) on each of these subjects that are cornerstones in finance and in decision making under uncertainty. The structure of this paper is as follows: In Section 26.2, we deal with the main findings of PT and their implication regarding the above men- tioned topics. In Section 26.3, we cover experimental studies in finance focusing on some recent studies, which cast doubt on some of the results and claims of PT and CPT. In Section 26.4, we analyze the implication of the experimental findings to the theory of finance. Concluding remarks are given in Section 26.5. 26.2. Allias Paradox, PT, CPT, and RDEU: Claims and Implication to the Theory of Finance 26.2.1. Probability Distortions (or Decision Weights) Most models in economics and finance assume expected utility maximization. Probably the most famous example contradicting the expected utility paradigm is provided by Allias, and is known as the Allias paradox (1953). Table 26.1 provides two choices in both part I and part II. In part I most subjects would typically choose A, while in part II most of them choose D. Such choices constitute a contradiction to the classic EU paradigm because from the choice in part I we can conclude that: u(1) > 0:01u(0) þ 0:89u(1) þ0:10 u(5) This inequity can be rewritten as 0:11u(1) > 0:01 u(0) þ0:10 u(5), (26:1) and the choices in part II implies that 0:89u(0) þ0:11u(1) < 0:9u(0) þ0:10u(5) The last inequality can be rewritten also as 0:11u(1) < 0:01u(0) þ 0:10u(5) (26: 2) As Equations. (26.1) and (26.2) contradict each other for any preference u, we have an inconsist- ency in the choices in part I and II. How can we explain this result? Does it mean that the EU paradigm is completely wrong? And if the answer is positive, do we have a better substitute to the EU paradigm? The preference of D over C is not surprising. However, the preference of A over B in Part I seems to induce the paradox. The choice of A is well-known as the ‘‘certainty effect,’’ (see Kahne- man and Tversky, 1979), i.e. the ‘‘one bird in the hand is worth more than two in the bush’’ effect. The explanation for the contradiction in Equations (26.1) and (26.2) is due to the ‘‘certainty effect,’’ or alternatively, due to probability distortion in the case where probabilities are smaller than 1. Indeed, experimental psychologists find that subjects tend to subjectively distort probabilities in their decision making. To be more specific, one makes a decision using a weight w(p) rather than the objective probability p. In our specific case, w(0:01) > 0:01 – hence the attractiveness of B relative to A decreases, which explains the choice of A in this case. However, in such a case, the classical von Neuman–Morgenstern expected utility is rejected once decision weight w( p) is employed rather than objective probability p. Table 26.1. Allias paradox. All outcomes are in million $ Part I AB Outcome Probability Outcome Probability 1 1 0 0.01 1 0.89 5 0.10 Part II CD Outcome Probability Outcome Probability 0 0.89 0 0.90 1 0.11 5 0.10 EXPERIMENTAL ECONOMICS AND THE THEORY OF FINANCE 521 [...]... prospect G in terms of total wealth (W þ x) if only F 534 ENCYCLOPEDIA OF FINANCE dominates G with change in wealth (x) Thus, shifting from total wealth to change of wealth does not affect the dominance result The same is true with the Mean-Variance rules SD rules deal mainly with two distinct options and not with a mix of random variables, hence generally the issues of integration of cash flows does... that 82–96 percent of the choices (see Tasks II and III) are consistent with FSD Once again, by the results of Task IV we see that about 50 percent of the choices reject the assumption of risk aversion (SSD) Table 26.4 taken from Levy and Levy (2002b) reveals once again the results of another experiment showing that at least 62 percent of the choices contradict the S-shape preference of PT Wakker (2003)... decision weights does not violate FSD Namely, FÃ GÃ , T(F Ã ) T(GÃ ) (26:4) 524 ENCYCLOPEDIA OF FINANCE (See Levy and Wiener, 1998 For a survey of SD rules, PT, and the impact of decision weights on choices, see Levy, 1998) In PT and CPT frameworks, probabilities are also distorted in the uniform case However, the advantage of PT over CPT is that with PT all probabilities with the same size, e.g pi ¼... THEORY OF FINANCE one can test the CAPM with ex-ante parameters Lintner (1969) found that subjects typically diversify in only 3–4 assets (out of the 20 available risky assets), yet the CAPM, or the m À b linear relationship was as predicted by the CAPM with an R2 of about 75 percent Thus, Levy found a strong support to the CAPM with ex-ante parameters 26.4 Implication of the Experimentalfindings to Finance. .. to the use of decision weights To sum up, the equity risk premium puzzle can be explained either by loss aversion, which is consistent both with an S-shape function and a reverse S-shape function, or by decision weights, even in the absence of loss aversion 26.3.3 The Shape of Preference Risk aversion and a positive risk premium are two important features of most economic and finance models of assets... ‘‘Violations of monotonicity in judgment and decision making.,’’ In A.A.J Marley (Eds.), Choice, decision, and measurement: Essays in honor of R Duncan Luce (pp 73–100), Mahwah, NJ: Erlbaum Black, F and Scholes, M (1973) ‘‘The pricing of options and corporate liabilities.’’ Journal of Political Economy, 81: 637–654 Edwards, W (1955) ‘‘The prediction of decisions among bets.’’ Journal of Experimental... Review, 59: 25–34 EXPERIMENTAL ECONOMICS AND THE THEORY OF FINANCE Hanoch, G and Levy, H (1969) ‘‘The efficiency analysis of choices involving risk.’’ Review of Economic Studies, 36: 335–346 Kahneman, D and Tversky, A (1979) ‘‘Prospect theory of decisions under risk.’’ Econometrica, 47(2): 263–291 Kroll, Y and Levy, H (1992) ‘‘Further tests of separation theorem and the capital asset pricing model.’’... weighting functions.’’ Journal of Risk and Uncertainty, 16: 147 –163 Levy, M Levy, H., and Solomon, S (2000) Microscopic Simulation of Financial Markets: from Investor 539 Behavior to Market Phenomena San Diego, CA: Academic Press Lintner J (1965) ‘‘Security prices, risk, and maximal gains from diversification.’’ Journal of Finance, 20: 587–615 Machina, M.J (1994) ‘‘Review of generalized expected utility... Markets New York: Basil Blackwell Modigliani, F and Miller, M.H (1958) ‘‘The cost of capital corporation finance and the theory of investment.’’ American Economic Review, 48: 261–297 Odean, T (1998) ‘‘Are investors reluctant to realize their losses.’’ Journal of Finance, 53: 1775–98 Plott, C.R (1979) ‘‘The application of laboratory experimental methods to public choice,’’ in C.S Russell (ed.) Collective... (1948) ‘‘An experimental study of the auction-value of uncertain outcomes.’’ American Journal of Psychology, 61: 183–193 Quiggin, J (1982) ‘‘A theory of anticipated utility.’’ Journal of Economic Behavior and Organization, 3: 323–343 Quiggin, J (1993) Generalized Expected Utility Theory: The Rank Dependent Model Boston, MA: Kluwer Academic Publishers Rapoport, A (1984) ‘‘Effects of wealth on portfolio under . percent of FFO Source: NAREIT 514 ENCYCLOPEDIA OF FINANCE the dividend yield of REITs with a 10-year constant maturity treasury yield and indicates that the former was higher for most of time. until the end of 1980s. At the end of 1980s, the combined effect of overbuilding, the savings and loan crisis, and the impact of the Tax Reform Act of 1986 led to the expansion of REITs. Investors. consumer price index Source: NAREIT 516 ENCYCLOPEDIA OF FINANCE Corporation (FHLMC or Freddie Mac) chartered under Title III of the Emergency Home Finance Act of 1970 provided liquidity for conventional loans