The effect of leverage on the performance of real estate companies

2018 ◽  
Vol 11 (3) ◽  
pp. 284-318 ◽  
Author(s):  
Giacomo Morri ◽  
Karoline Jostov
Keyword(s):  
Real Estate ◽  
Risk Premium ◽  
Market Risk ◽  
Local Market ◽  
Cross Sectional ◽  
Content Type ◽  
Crisis Period ◽  
Market Risk Premium ◽  
Fama And French ◽  
The Impact

Purpose This paper aims to investigate the impact of leverage on the total shareholder return of European publicly traded real estate vehicles in three periods: Crisis Period (2007-2009), Rebound Period (2009-2014) and the Whole Period. Design/methodology/approach Cross-sectional analysis is used and the leverage effect on the performance is controlled for seven other independent variables (local market risk premium, size, book-to-market, short-term debt, cash); moreover, regional differences are accounted for. Findings It is established that during the Crisis Period, leverage levels are negatively associated with performance: this relationship also holds throughout the Whole Period, implying that for real estate securities, the cost of financial distress is larger than the potential gain from taxation, although the economic significance of it is limited. The Fama and French (1992) three factors, including size, book-to-market and local market risk premium, are found to be relevant, which is consistent with the literature. In addition, the UK and Sweden regions are identified as significant. Originality/value Even if there is sizeable body of literature on determinants of leverage and determinants of asset returns, little work has been done on how leverage affects the returns of European real estate companies. In addition, this paper takes advantage of observations from a full economic cycle and the possible effects of the crisis period.

The Cross Section of Expected Returns with MIDAS Betas

2011 ◽  
Vol 47 (1) ◽  
pp. 115-135 ◽  
Author(s):  
Mariano González ◽  
Juan Nave ◽  
Gonzalo Rubio
Keyword(s):  
Cross Section ◽  
Risk Premium ◽  
Market Risk ◽  
Ordinary Least Squares ◽  
Mixed Data ◽  
Expected Returns ◽  
Data Sampling ◽  
Cross Sectional ◽  
Market Risk Premium ◽  
The Cross

AbstractThis paper explores the cross-sectional variation of expected returns for a large cross section of industry and size/book-to-market portfolios. We employ mixed data sampling (MIDAS) to estimate a portfolio’s conditional beta with the market and with alternative risk factors and innovations to well-known macroeconomic variables. The market risk premium is positive and significant, and the result is robust to alternative asset pricing specifications and model misspecification. However, the traditional 2-pass ordinary least squares (OLS) cross-sectional regressions produce an estimate of the market risk premium that is negative, and significantly different from 0. Using alternative procedures, we compare both beta estimators. We conclude that beta estimates under MIDAS present lower mean absolute forecasting errors and generate better out-of-sample performance of the optimized portfolios relative to OLS betas.

The asymmetric impact of rational and irrational components of fear index on S&P 500 index returns

2017 ◽  
Vol 9 (3) ◽  
pp. 278-291 ◽  
Author(s):  
Gökçe Soydemir ◽  
Rahul Verma ◽  
Andrew Wagner
Keyword(s):  
Risk Factors ◽  
Risk Premium ◽  
Var Model ◽  
Impulse Responses ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Market Risk Premium ◽  
Economic Fundamentals ◽  
The Impact

Purpose Investors’ fear can be rational, emanating from the natural dynamics of economic fundamentals, or it can be quasi rational and not attributable to any known risk factors. Using VIX from Chicago Board Options Exchange as a proxy for investors’ fear, the purpose of this paper is to consider the following research questions: to what extent does noise play a role in the formation of investors’ fear? To what extent is the impact of fear on S&P 500 index returns driven by rational reactions to new information vs fear induced by noise in stock market returns? To what extent do S&P 500 index returns display asymmetric behavior in response to investor’s rational and quasi rational fear? Design/methodology/approach In a two-step process, the authors first decompose investors’ fear into its rational and irrational components by generating two additional variables representing fear induced by rational expectations and fear due to noise. The authors then estimate a three-vector autoregression (VAR) model to examine their relative impact on S&P 500 returns. Findings Impulse responses generated from a 13-variable VAR model show that investors’ fear is driven by risk factors to some extent, and this extent is well captured by the Fama and French three-factor and the Carhart four-factor models. Specifically, investors’ fear is negatively related to the market risk premium, negatively related to the premium between value and growth stocks, and positively related to momentum. The magnitude and duration of the impact of the market risk premium is almost twice that of the impact of the premium on value stocks and the momentum of investors’ fear. However, almost 90 percent of the movement in investors’ fear is not attributable to the 12 risk factors chosen in this study and thus may be largely irrational in nature. The impulse responses suggest that both rational and irrational fear have significant negative effects on market returns. Moreover, the effects are asymmetric on S&P 500 index returns wherein irrational upturns in fear have a greater impact than downturns. In addition, the component of investors’ fear driven by irrationality or noise has more than twice the impact on market returns in terms of magnitude and duration than the impact of the rational component of investors’ fear. Originality/value The results are consistent with the view that one of the most important drivers of stock market returns is irrational fear that is not rooted in economic fundamentals.

Political uncertainty and the US market risk premium

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Richard P. Gregory
Keyword(s):  
Risk Premium ◽  
Design Methodology ◽  
Market Risk ◽  
The Other ◽  
Political Uncertainty ◽  
Delayed Effect ◽  
Content Type ◽  
Market Risk Premium ◽  
The Us ◽  
Negative Effect

PurposeThe purpose of this study is to examine the bi-directional causality between political uncertainty and the market risk premium in the US.Design/methodology/approachI use a theoretical model to motivate signs and then check signs based on a vector autoregression.FindingsI find that political uncertainty has a small positive, delayed effect on the market risk premium. The market risk premium, on the other hand, has a large permanent, negative effect on political uncertainty.Originality/valueThis is the first research paper to consider the bi-directional effects of political uncertainty on the market risk premium and vice versa. It also finds interesting empirical results.

Intellectual capital in tangible intensive firms: the case of Brazilian real estate companies

2014 ◽  
Vol 15 (2) ◽  
pp. 333-348 ◽  
Author(s):  
Daniel Pitelli Britto ◽  
Eliane Monetti ◽  
Joao da Rocha Lima Jr
Keyword(s):  
Real Estate ◽  
Intellectual Capital ◽  
Value Creation ◽  
Market Value ◽  
Fair Value ◽  
Market Risk ◽  
Cross Sectional ◽  
Content Type ◽  
Physical Assets ◽  
Using Data

Purpose – The purpose of this paper is to clarify whether value created by real estate (RE) companies (tangible intensive firms) can be evaluated better using intellectual capital (IC) elements (human, structural and physical assets) or traditional accounting measures of efficiency (ROIC and profit margins). Design/methodology/approach – Correlations and cross-sectional OLS regressions with robust standard errors were used to find relationships between variables explaining value creation. Data were collected from 2007 to 2011 for Brazilian RE firms. To measure market risk, the authors used a new approach to deal with low liquidity. VAIC and I j ratios were used as IC proxies even though both have limitations. Findings – IC has a significant inverse relationship with market value. The more valuable companies showed lower levels of IC except for CEE which explains value as much as ROIC. Also, IC does not influence market risk caused by size and leverage and does not explain ROIC. Research limitations/implications – The limitations of this study result from time and proxy variables. IC was measured by a VAIC model using data from a period of intense volatility. To increase the robustness of the conclusions, other variables should be used as proxies for IC and the results compared. The VAIC model has certain deficiencies in measuring IC. Practical implications – Managers and investors in the RE sector need to change the way they create value and measure value creation. The low level of HC explaining either ROIC or market value is a signal of low innovation which, combined with high CEE, induces a short-term outlook. Originality/value – This study opens discussion of IC in the Brazilian RE sector. A new methodology for identifying value creation is necessary for better evaluation and determining the fair value of firms.

International listed real estate returns: evidence from the global financial crisis

2019 ◽  
Vol 37 (1) ◽  
pp. 72-91
Author(s):  
Alain Coën ◽  
Patrick Lecomte
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Serial Correlation ◽  
Global Financial Crisis ◽  
Publicly Traded ◽  
Content Type ◽  
Real Estate Returns ◽  
Fama And French ◽  
And Performance ◽  
The Impact

PurposeThe purpose of this paper is to analyze and revisit the risk and performance of publicly traded real estate companies from 14 countries over the period 2000–2015, marked by the unprecedented Global Financial Crisis, in presence of errors-in-variables (EIV) and illiquidity (measured by serial correlation, following Getmanskyet al.(2004)).Design/methodology/approachThe authors extend the seminal work of Bondet al.(2003), and shed a new light on the relative performance of listed real estate before and after the GFC. First, the authors suggest the use of various asset pricing models (APM) including the Fama and French (2015) five-factor APM with global and country-level factors. Second, the authors implement unbiased estimators to correct for the econometric bias induced by EIV in APM. Third, the authors deal with the impact of illiquidity (measured by serial correlation) on the risk properties of international securitized real estate returns.FindingsThe findings show that post-GFC, a radical change in international listed real estate risk factors has resulted in more homogeneous markets internationally and less diversification opportunities for international investors.Practical implicationsThe authors suggest the use of robust linear APM (including the Fama and French (2015) five-factor APM) to analyze the risk and performance of publicly traded real estate companies from 14 countries over the period 2000–2015.Originality/valueThe authors analyze and revisit the risk and performance of publicly traded real estate companies from 14 countries over the period 2000–2015, marked by the unprecedented Global Financial Crisis.

Does asset liquidity matter? Evidence from real estate stock markets

2015 ◽  
Vol 8 (3) ◽  
pp. 220-242 ◽  
Author(s):  
Alexander Scholz ◽  
Karim Rochdi ◽  
Wolfgang Schaefers
Keyword(s):  
Asset Pricing ◽  
Real Estate ◽  
Risk Premium ◽  
Investment Strategy ◽  
Time Series Regression ◽  
Underlying Asset ◽  
Content Type ◽  
Low Degree ◽  
Asset Liquidity ◽  
The Impact

Purpose – The purpose of this paper in this context is to examine the impact of asset liquidity on real estate equity returns, after taking well-documented systematic risk factors into account. Due to their unique characteristics, real estate equities constitute an inherently low degree of underlying asset liquidity. Design/methodology/approach – Following the Fama-French time-series regression approach, the authors extend the conventional asset pricing model by a real estate-specific asset liquidity factor (ALF), using a sample of 244 real estate equities. Findings – The results, based on monthly data for the period 1999-2012, reveal that asset liquidity is a relevant pricing factor which contributes to explaining return variations in real estate equity markets. Accordingly, investors expect a risk premium from listed real estate companies with a low degree of asset liquidity, which is especially the case for companies facing financial constraints and during economic downturns. Furthermore, an investment strategy exploiting differences in the underlying asset liquidity yields considerable average excess returns of upto 8.04 per cent p.a. Practical implications – Considering the findings presented in this paper, asset liquidity should receive special attention from investors, as well as from the management boards of listed real estate companies. While investors who ignore the magnitude of asset liquidity may systematically misprice real estate equities, management can influence the firm’s cost of capital by adjusting the underlying asset liquidity. Originality/value – This is the first study to examine the role of an ALF in a real estate asset pricing framework.

Time-varying beta during the 2008 financial crisis – evidence from North America and Western Europe

2017 ◽  
Vol 18 (4) ◽  
pp. 398-431
Author(s):  
Ikrame Ben Slimane ◽  
Makram Bellalah ◽  
Hatem Rjiba
Keyword(s):  
Financial Crisis ◽  
North America ◽  
Risk Premium ◽  
Western Europe ◽  
Global Financial Crisis ◽  
Subprime Crisis ◽  
Content Type ◽  
Crisis Period ◽  
Beta Risk ◽  
The Impact

Purpose This paper aims to analyze the impact of the global financial crisis on the conditional beta in the region of North America and Western Europe and the effect on the behavior and decisions of the investor. Design/methodology/approach The authors model the variations of volatility in financial markets during crisis using the bivariate GARCH model of Engle and Kroner (1995). Findings The empirical investigation identifies an additional effect of the crisis over the period of the test. Results indicate a rise in the beta in some cases and a fall in others. This rise had a direct impact on the systematic beta risk, which increased for the majority of the companies during the crisis period. The increase in beta during the crisis period has an effect on the behavior of the investor and his decisions. Research limitations/implications The increase in the beta during the period of crisis due to a high volatility returns has an effect on the behavior and decisions of the investor. Originality/value This paper examines the effects of the “subprime crisis” on the risk premium of companies in several sectors of activity.

scholarly journals Kurtosis and Skewness on Lagged Market Risk Premium in Indonesian Market During Covid 19 Pandemic

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Iman Lubis
Keyword(s):  
Panel Data ◽  
Capital Market ◽  
Risk Premium ◽  
Market Risk ◽  
Previous Model ◽  
Return Distribution ◽  
Market Risk Premium ◽  
Predictive Regression ◽  
The Impact ◽  
Skewness And Kurtosis

This study investigates the impact of return distribution such as skewness and kurtosis on lagged market risk premium to risk premium in Indonesia capital market during COVID-19 pandemic. Data are monthly, from january to December 2020, and 674 firms. Panel data predictive regression is used The method  For this study, I first looked for market risk premium and risk premium desripitives. Second, I used monthly panel data predictive regression from lagged market risk premium and risk premium in 2020. Third, I incorporate skewness and kurtosis simultaneously. Fourth, I exclude kurtosis or skewness in previous model. The results are market risk premium and risk premium having negative return. Risk premium has lower returns than market risk premium. The beta lagged market risk premium is significant to risk premium. The skewness and kurtosis market risk premium do not signify to risk premium together but significant separately. I can clonclude that the movement market risk premim and risk premium during COVID-19 pandemic are average negative. Beta lagged market risk premium can explain the future monthly risk premium. Contrary skewness and kurtosis, those can not be run together. When the model used to beta lagged market risk premium and skewness, partially the skewness was significant and the direction was positive. However, only beta lagged market risk premium and kurtosis were staying negative to the previous model. Incorporating lagged assumptive distribution only explain the risk premium under 1 % about 0.24%.

An assessment of the risk and return of residential real estate

2015 ◽  
Vol 41 (6) ◽  
pp. 591-599 ◽  
Author(s):  
Dale Domian ◽  
Rob Wolf ◽  
Hsiao-Fen Yang
Keyword(s):  
Asset Pricing ◽  
Real Estate ◽  
Risk Premium ◽  
Real Estate Market ◽  
Individual Investors ◽  
Residential Real Estate ◽  
Risk And Return ◽  
Content Type ◽  
Market Risk Premium ◽  
Substantial Investment

Purpose – The home is a substantial investment for most individual investors but the assessment of risk and return of residential real estate has not been well explored yet. The existing real estate pricing literature using a CAPM-based model generally suggests very low risk and unexplained excess returns. However, many academics suggest the residential real estate market is unique and standard asset pricing models may not fully capture the risk associated with the housing market. The purpose of this paper is to extend the asset pricing literature on residential real estate by providing improved CAPM estimates of risk and required return. Design/methodology/approach – The improvements include the use of a levered β which captures the leverage risk and Lin and Vandell (2007) Time on Market risk premium which captures the additional liquidity risk of residential real estate. Findings – In addition to presenting palatable risk and return estimates for a national real estate index, the results of this paper suggest the risk and return characteristics of multiple cities tracked by the Case Shiller Home Price Index are distinct. Originality/value – The results show higher estimates of risk and required return levels than previous research, which is more consistent with the academic expectation that housing performs between stocks and bonds. In contrast to most previous studies, the authors find residential real estate underperforms based on risk, using standard financial models.

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