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The purpose of this paper is to examine the risk neutral and non-risk neutral pricing of Singapore Real Estate Investment Trusts (S-REITs) via comparing the average of the individual ratios (of deviation between expected and observed closing price/observed closing price) with the ratio (of standard deviation/mean) for closing prices via the binomial options pricing tree model.

If the ratio (of standard deviation/mean) ratio > the ratio (of deviation between expected and observed closing price/observed closing price), then the deviation of closing prices from the expected risk neutral prices is not significant and that the S-REIT is consistent with risk neutral pricing. If the ratio (of deviation between expected and observed closing price/observed closing price) is greater, then the S-REIT is not consistent with risk neutral pricing.

Capitacommercial Trust (CCT), Capitamall Trust (CMT) and Keppel Real Estate Investment Trust (REIT) have large positive differences between the two ratios (39.86, 30.79 and 18.96 percent, respectively), implying that these S-REITs are not trading at risk neutral pricing. Suntec REIT has a small positive difference of 2.35 percent between both ratios, implying that it is trading at risk neutral pricing. Ascendas REIT has the largest negative difference between the two ratios at −4.24 percent, to be followed by Mapletree Logistics Trust at −0.44 percent. Both S-REITs are trading at risk neutral pricing. The analysis shows that CCT, CMT and Keppel REIT exhibit risk averse pricing.

Results are consistent with prudential asset allocation for viable S-REIT portfolio investing but that not all these S-REITs exhibit strong market efficiency in their pricing.

Pricing may be risk neutral over a certain period but investor sentiments, fear of risks and speculative activities could affect an S-REIT’s risk neutrality.

With enhanced risk diversification activities, the S-REITs should attain risk neutral pricing.

Virtually no research of this nature has been undertaken for S-REITS.

This article is based on responses to the 1982 general invitation from the Review Board for Government Contracts. The authors' main contention is that the pricing of government contracts has hitherto been deficient in at least two fundamental respects — the use of the historic cost accounting model as a computational framework for the costing and pricing of non‐competitive Government contracts and the use of ex post accounting rates of return for estimating target rates of return.

This paper aims to investigate a relatively new anomaly of investment growth and revisits well-known anomalies of size and value. It aims to answer two main research questions. First, can covariance risks (i.e. factor loadings) be excluded from being determining variables that drive return premiums and explain stock returns? Second, from a behavioral finance standpoint, the authors examine whether using firm characteristics is a more practical and accessible approach and also meets the necessary and sufficient conditions to analyze stock returns.

The authors create the investment-growth-based factor (LMH) which is defined as the return difference between low and high investment growth portfolios. The authors then incorporate the LMH factor along with other characteristic-based factors and their loadings into characteristic-balanced portfolio and three-factor model tests.

The authors find that covariance risks on investment growth, size and value are not necessary as determining variables. Instead, they find that behavioral-related firm characteristics of investment growth, size and value are necessary and sufficient as determinants of return premiums and stock returns.

The results have practical and useful implications for investors in their stock portfolio analysis and selection because firm characteristics are relatively more available than covariance risks that need estimation and typically contain measurement errors.

The paper has practical value to investors in their stock portfolio analysis and selection. Methodologically, in contrast to prior studies that do not directly use the investment growth to control for portfolio characteristics, the use of the newly created LMH factor and its loadings allows us to directly and properly test if the investment growth anomaly is related to the investment growth characteristic that is hypothesized to drive return premiums and determine stock returns from behavioral finance perspectives.

Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model.

The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression.

The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered.

The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians.

This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

When agents first become active investors in financial markets, they are relatively inexperienced. Much of the literature focuses on the incentives of presumably sophisticated informed agents to produce information, and not on the nave agents. However, unsophisticated agents are important aspects of financial markets and worth analyzing further. In this paper, we provide a theoretical perspective that addresses the issue of how many nave traders would one expect in a financial market where policy makers try to educate the nave agents.We show that such policy balances the effects of nave trades on corporate investment and liquidity, as well as the monetary cost of increasing financial sophistication. The optimal proportion of nave agents varies with the value of information, the noise in private signals, and the inherent sensitivity of corporate investment to prices.We also show that the policy tool of encouraging insider trading can deter nave investors and thus improve corporate governance and the efficacy of corporate investment.

The purpose of this paper is to examine the performance of the agricultural banking industry using both traditional and risk‐adjusted non‐parametric efficiency measurement techniques. In addition to computing efficiency scores, the risk preference structure of the agricultural banking industry is examined.

The paper used data envelopment analysis (DEA) to examine the efficiency of agricultural banks in the year 2001. Standard cost efficiency is computed and compared to both profit and risk‐adjusted profit efficiency scores. The risk‐adjustment is a modification of traditional DEA wherein firm preferences are represented via a mean‐variance criterion. The risk‐adjusted technique also provides estimates of firm level risk aversion.

Results from the traditional approach that does not account for risk indicate a low degree of efficiency in the banking industry, while the risk‐adjusted approach indicates banks are much more efficient. On average, 77 percent of the inefficiency identified by the standard DEA formulation is actually attributable to risk averse behavior by the firm. In addition, most banks appear to be substantially risk averse.

The risk‐adjusted DEA technique used in this study should be applied to other, diverse data sets to examine its performance in a broader context.

Results from this study support the idea that traditional DEA methods may mischaracterize the level of efficiency in the data if agents are risk averse. In addition, the paper outlines a practical method for deriving firm level risk aversion coefficients.

This paper sheds light on the agricultural banking industry and illustrates the power of a new efficiency and risk analysis technique.

The purpose of this paper is to investigate the firm-specific anomaly effect and to identify market anomalies that account for the cross-sectional regularity in the Indian stock market. The paper also examines the cross-sectional return predictability of market anomalies after making the firm-specific raw return risk adjusted with respect to the systematic risk factors in the unconditional and conditional multifactor specifications.

The paper employs first step time series regression approach to drive the risk-adjusted return of individual firms. For examining the predictability of firm characteristics on the risk-adjusted return, the panel data estimation technique has been used.

There is a weak anomaly effect in the Indian stock market. The choice of a five-factor model (FFM) in its unconditional and conditional specifications is able to capture the book-to-market equity, liquidity and medium-term momentum effect. The size, market leverage and short-run momentum effect are found to be persistent in the Indian stock market even with the alternative conditional specifications of the FFM. The results also suggest that it is naï argue for disappearing size effect in the cross-sectional regularity.

Constrained upon the data availability, certain market anomalies and conditioning variables cannot be included in the analysis.

Considering the practitioners' prospective, the results indicate that the profitable investment strategy with respect to the small size effect is still persistent and warrants close-ended mutual fund investment portfolio strategy for enhancing the long-term profitability. The short-run momentum effect can generate potential profits given a short-term investment horizon.

This paper provides the first-ever empirical evidence from an emerging stock market towards the use of alternative conditional multifactor models for the complete explanation of market anomalies. In an attempt to analyze the anomaly effect in the Indian stock market, this paper provides further evidence towards the long-short hedge portfolio return variations in terms of a wide set of market anomalies that have been documented in prior literature.

Divides investors into two types: tax‐paying investors and tax‐exempt pension funds. Tax‐paying investors will worry about the expected after‐tax variance of return on real estate, while tax‐exempt pension funds will worry about the expected pre‐tax variance of return. States this is an important observation because the after‐tax variance of return is apt to be significantly less than the pre‐tax variance of return (particularly during the early 1980s when tax‐paying investors were able to use real estate losses to offset other income). The model developed by the author suggests this reduced expected after‐tax variance of return helps explain the seemingly irrational construction that took place in US office markets during the 1980s.

This study aims to examine the performance and volatility of Turkey Real Estate Investment Trusts (Turkish REITs) as the world is adjusting to the new normal situation in every aspect of REITs' business activities.

The prices of REITs were acquired from 26 Turkish REITs in this study, but owing to autocorrelation difficulties, 14 Turkish REITs were employed in the analysis. The ten-year long-term bond of the Turkish Government was also utilized and the period of data obtained was based on availability. The performance of Turkish REITs was evaluated using Sharpe's ratio and Treynor's ratio, and the volatility was assessed using MGARCH-BEKK.

The authors found out that Turkish REITs are constantly underperforming and the REITs' returns remain highly volatile and persistent. In addition, findings showed evidence of volatility clustering and the asymmetric impact of shocks. This study further revealed the uniqueness of each of the Turkish REITs due to the lack of evidence of multicollinearity.

However, the limitation of this study is the constraint in obtaining more macro-economic variables of more than ten-years of Turkey's Government bond and the study focused mainly on Turkish REITs.

The result suggests that since Turkish REITs are not mandatory to payout 90% of taxable earnings as dividends, high performance and an appropriate risk management approach are expected. The need for timely revealing performance of T-REITs and associated uncertainty may trigger better performance as discussed in the relationship between disclosure and performance which is recently emphasized in a recent study by Koelbl (2020). With current performance and associated uncertainty in Turkish REITs, the need to protect Turkish REITs investors is highly essential. The result further educates REIT investors that diversification benefits of REITs tend to reduce in extremely risky situations.

This is the first study in the context of Turkish REITs that comprehensively integrated market capitalization of REITs and simultaneous evaluation of performance and the volatility of the Turkish REITs as the world adjusts to the new normal.