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Real estate investment has been generally accepted as a value-adding proposition for a portfolio investor. Such an impression is not only shared by investment professionals and financial advisors but also appears to be supported by an overwhelming amount of research in the academic literature. The benefits of adding real estate as an asset class to a well-diversified portfolio are usually attributed to the respectable risk-return profile of real estate investment together with the relatively low correlation between its returns and the returns of other financial assets. By using the regime-switching technique on an extensive historical dataset, we attempt to look for the statistical evidence for such a claim. Unfortunately, the empirical support for the claim is neither strong nor universal. We find that any statistically significant improvement in risk-adjusted return is very much limited to the bullish environment of the real estate market. In general, the diversification benefit is not found to be statistically significant unless investors are relatively risk averse. We also document a regime-switching behavior of real estate returns similar to those found in other financial assets. There are two distinct states of the real estate market. The low-return (high-return) state is characterized by its high (low) volatility and its high (low) correlations with the stock market returns. We find this kind of dynamic risk characteristics to play a crucial role in dictating the diversification benefit from real estate investment.

The paper uses 101 years of Chilean and international financial assets returns to investigate mean-variance optimal portfolio allocations. The key conclusion is that the share of international unhedged investments is substantial even in minimum risk portfolios (20%), unless the period 1980–2002 is assumed to be drawn from a different distribution and previous history is disregarded. In addition to that, the paper finds that mean-variance optimal investors would have generated substantial demand for an asset replicating the return profile of an efficient pay-as-you-go pension scheme. Labour income and departures from log-normality of returns might, however, affect the latter conclusion.

This paper aims to determine the specific financial ratio's effects on market value and return of assets for Turkish real estate investment trusts (REITs) traded at Istanbul Stock Exchange (ISE). The paper intends to define liquidity ratios, financial structure ratios, return ratios and stock performance ratios related to market value and return of asset.

The study includes 17 REITs traded in ISE. The period of study is specified as the year from 2009 to 2018. Panel data analysis is applied in this study. Dependent variables are current market value and return of assets, independent variables are 12 financial ratios, which are considered to explain the model significantly. These ratios will be calculated from audited year-end balance sheets for specific periods throughout at least ten years as time series. Two different models and hypotheses have been established to identify the financial ratios that affect the market value and return of assets for REITs.

According to the results, long-term financial loans/total assets, return of equity and working capital ratio are negatively correlated with market value, while market value/book value and total assets are correlated positively. On the other hand, market value/book value ratio, price/earning ratio, long-term financial loans/total assets and earnings per share are correlated with return of assets. REITs have high levels of financial leverage, especially in foreign currency. The striking point is that REITs hardly ever do not use financial derivatives to hedge their position again currency and interest rate risk. This approach makes the financial structures of REITs vulnerable and fragile against market volatility.

In Turkey, as an example of an emerging market, financial borrowing does not increase the return rates and market value for REITs due to market's idiosyncratic properties. This finding provides substantial insight into how the debt and equity allocation of Turkish REITs should be structured. Also, it has been observed that forward-looking expectations are considered more than the current situation in the market.

The purpose of this paper is to address two questions: did adoption of Statements of Financial Accounting Standards No. 132(R) and No. 158 affect neutrality of the financial reporting with regard to the disclosed expected rate of return (ERR) on pension assets assumptions, and did pension asset allocations change in response to the new recognition and disclosure requirements?

The author uses several measures of association between reported expected return and pension assets allocations to assess neutrality of the reported ERR. The series of tests explores changes in correlations between asset allocations and expected rates of return and changes in the implied risk premiums following adoption of Statements No. 132(R) and No. 158. Granger causality analysis is used to explore the second research question: did pension asset allocations change in response to the new recognition and disclosure requirements?

The empirical results are consistent with improved neutrality of financial reporting following adoption of Standard No. 132(R). There were no detectable changes in neutrality following adoption of Standard No. 158. While the data are consistent with portfolio allocations changing to a greater degree than did expected rates of return following Statement No. 132(R) adoption, the effect appears short-lived.

The overall results are consistent with Standard 132(R) having a positive effect on the neutrality of the reported ERR. Also, there is no evidence of persistent and systematic structuring of transactions around preferred financial reporting outcomes.

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.

The purpose of this paper is to determine the required return of intangible assets for eight different business sectors by means of an empirical study of companies from the US Standard & Poor's 500 index. The resulting required return is subsequently compared with proxies for the required return on intangible assets used in practice, such as the weighted average cost of capital (WACC).

To determine the discount rate of the intangible assets the paper applies the weighted average return on assets method (weighted average return on assets (WARA) method). The paper finds the return on intangible assets (R_IA) by setting the WARA equal to the WACC and solves the equation for R_IA.

For all the identified sectors, the R_IA is higher than the WACC. It is also shown that this return is higher than the levered or unlevered cost of equity of the company as a whole. In six of the eight sectors, the levered cost of equity appears to be the best proxy for the required return on intangible assets.

The paper shows how the required return on intangible assets can be estimated. The required return is needed for discounted cash flow valuations of intangible assets.

This paper adjusts the WARA method applied by Smith and Parr. In contrast to Smith and Parr, the tax shield is included as a separate asset in the model. Consequently, the WACC before tax is used instead of the WACC after tax.

The purpose of this paper is to examine whether firm-level asset investment effects in returns found for US firms occur within the Greek stock market.

The paper utilizes portfolio-level tests and cross-sectional regressions.

The authors find that growth in total assets is strongly negatively related to future stock returns of Greek firms. In fact, the relation remains statistically significant, even when the authors control for other strong predictors of future returns (i.e. market capitalization and book-to-market ratio). Furthermore, the authors find that a hedge trading strategy on asset growth rate consisting of a long (short) position in firms with low (high) balance sheet growth generates positive returns, confirming that investment growth has significant predictive power for future returns of Greek listed firms.

The paper adds to the literature on the generalization of asset pricing regularities attributable to accounting figures in an emerging market.

With the bankruptcy of Enron and the accompanying loss of pension benefits of its employees, pensions have recently received significant press. Accounting for pension plan obligations, for defined benefit plans in particular, requires companies to make assumptions regarding discount rates, projected salary increases, and expected long‐term return on plan assets. Such assumptions, in turn, determine the funding status of the pension plan and the annual pension expense. Higher assumed discount rates reduce the pension obligation, enhance the funding status of the plan, and reduce any lump‐sum payments. Higher expected return on assets reduces the current pension expense. This study investigates the relationship between pension plan assumptions and the funding status of a pension plan. The results reveal that companies with pension plans that are more fully funded assume higher discount rates and expected long‐term return on assets than do companies with less funded plans. The effect of these assumptions is that higher discount rate assumptions lead to better funding status, and higher expected long‐term rates of return on assets partially offset the pension expense impacts of these higher discount rate assumptions. We are doubtful that more funded plans collectively should be assuming higher discount rates and expected long‐term return on plan assets, especially since the actual return on plan assets investigated did not correlate with these assumptions.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

This study aims to introduce a tree-structured linear and quantile regression framework to the analysis and modeling of equity returns, within the context of asset pricing.

The approach is based on the idea of a binary tree, where every terminal node parameterizes a local regression model for a specific partition of the data. A Bayesian stochastic method is developed including model selection and estimation of the tree structure parameters. The framework is applied on numerous U.S. asset pricing models, using alternative mimicking factor portfolios, frequency of data, market indices, and equity portfolios.

The findings reveal strong evidence that asset returns exhibit asymmetric effects and non- linear patterns to different common factors, but, more importantly, that there are multiple thresholds that create several partitions in the common factor space.

To the best of the authors' knowledge, this paper is the first to explore and apply a tree-structured and quantile regression framework in an asset pricing context.