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This study seeks to examine the market returns of five domestic real estate investment trust (REIT) indices to determine whether they exhibit a turn‐of‐the‐month (TOM) effect.

A test is carried out for the TOM effect by employing a battery of parametric and non‐parametric statistical tests that address the concerns of distributional assumption violations. An OLS regression model compares the TOM returns with the rest‐of‐the‐month (ROM) returns and an ANOVA model examines the TOM period while controlling for monthly seasonalities. A non‐parametric t‐test examines whether the TOM returns are greater than the ROM returns and a Wilcoxon signed rank test examines the matched‐pairs of TOM and ROM returns.

A TOM effect in all five domestic REIT indices is found: real estate 50 REIT, all‐REIT, equity REIT, hybrid REIT, and mortgage REIT. More specifically, the six‐day TOM period, on average, accounts for over 100 per cent of the monthly return for the three non‐mortgage REITs, while the ROM period generates a negative return. Additionally, the TOM returns are greater than the ROM returns in 75 per cent of the months.

The data are limited to five‐years of daily returns and five different indices. Thus, the results could be biased on the selected time period.

These results are important to REIT portfolio managers and investors. Domestic REIT markets experience a TOM effect from which investors and portfolio managers can benefit.

The daily returns of all five major domestic REIT indices are examined. Data are evaluated which include daily returns after the passage of the REIT Modernization Act of 1999 that resulted in numerous changes for REITs. Whether the TOM effect can be detected with both parametric and non‐parametric tests is examined.

This chapter introduces four research methods that are not covered in the previous chapters. They are (1) non-parametric statistics, (2) interpretive structural modeling, (3) analytic hierarchy process, and (4) data envelopment analysis. The methods are discussed with examples. The discussion, however, is introductory; so we urge the reader to go through the pertinent references for details.

Describes non‐parametric methods applied to comparisons of three or more sample groups.Illustrates non‐parametric ANOVA applied to a randomized block design for a consumer sensory experiment.

This paper aims to investigate the informational content of earnings surprises and accounting information in credit default swap (CDS) markets.

This paper analyzes a sample of 444 US firms and 6,907 earnings announcements. By means of parametric and non-parametric event study analysis, the paper assesses the informational value and the timeliness in the assimilation of earnings surprises by CDS rates.

This paper shows that earnings surprises contain material information and that CDS rates are affected by the disclosure of obligors’ financial statements. There is also supporting evidence that positive and negative surprises induce asymmetric reactions on CDS rates, especially after accounting for the credit risk of the obligor and the liquidity of the CDS contract. Finally, and perhaps the most interesting conclusion of the study, there is evidence that earnings disclosed during unstable periods lack informational value, in opposition to normal periods.

As compared with similar studies, this paper presents three novel contributions. The first concerns the use of non-parametric analysis in parallel with parametric tests to achieve robust conclusions. The second novel contribution resides in assessing whether the liquidity of the CDS contracts affects the information value of earnings surprises or the timeliness at which the information is assimilated into CDS rates. Finally, this paper also contributes to improve our understanding on the relationship between the business cycle and the informativeness of accounting information.

This paper aims to study the weak form of efficiency of Indian capital market during the period of global financial crisis in the form of random walk.

The study considered daily closing prices of S&P CNX Nifty, BSE, CNX100, S&P CNX 500 from April 1, 2005 to March 31, 2010. The data source is the equity market segment of NSE and BSE. Both parametric and nonparametric tests (“ex‐posts” in nature) are applied for the purpose of testing weak‐form efficiency. The parametric tests include Augmented Dickey‐Fuller (ADF) unit root tests and nonparametric tests include Phillips‐Perron (PP) unit root tests and Run test. ADF tests use a parametric autoregressive structure to capture serial correlation and PP tests use non‐parametric corrections based on estimates of the long‐run variance of ΔY_t.

The results suggested that the Indian stock market was efficient in its weak form during the period of recession. It means that investors should not be able to consistently earn abnormal gains by analysing the historical prices. Hence one should not be able to make a profit from using something that everybody else knows.

The study reports that all the stocks in these selected indices are fundamentally strong and their prices are not influenced largely by historical prices and other relevant factors which came from industry and any other information that is publically available. Thus it can be concluded that the Indian stock market was informationally efficient and no investor can usurp any privileged information to make abnormal profits.

Where past studies have examined the weak‐form of efficiency of various markets and the effect of globalisation and global financial crisis on the various sectors of developing and emerging economies, this paper attempts to study the weak form of efficiency of the Indian capital market in the period of recession in the form of random walk.

This paper aims to provide empirical evidence for using the prospect theory (PT) basic assumptions in the Argentine context. Mainly, this study analysed the financial decision-making process in students of the economic-administrative academic area of two universities, one public and one private, in Córdoba.

The analysis methodology included (1) the descriptive statistical analysis to identify the presence of the certainty, reflection and isolation effects; (2) the construction of a set of indicators on the application of the PT; (3) the chi-squared independence test, to determine if the decisions made are independent of the degree course taken; (4) the non-parametric Kruskal–Wallis test, to determine if the decisions made by individuals vary according to the semesters taken or students' levels of progress; and (5) the non-parametric Mann–Whitney test, to determine if there are differences between the decisions made by men and women.

The empirical results provided evidence on the effects of certainty, reflection and isolation in both universities, concluding that the study participants make financial decisions in situations of uncertainty based more on PT than on expected utility theory.

This study contributes to the empirical evidence in a different Latin-American context, confirming that individuals make financial decisions based on the PT independently of their degree course, semester, level of advance, gender or the kind of university where they belong (public or private).

The purpose of this paper is to evaluate the performance of 191 equity unit trusts in an emerging market, South Africa over the period from February 2006 to January 2016, which captures different market conditions (pre-global financial crisis, crisis and recovery periods). Besides testing for managerial ability, both cross-sectional regression and the non-parametric rank correlation test are used to test whether the performance generated by unit trusts does persist.

To evaluate the managerial ability of portfolio managers, two widely used methods, the Treynor-Mazuy (1966) model and Henriksson-Merton (1981) model, are employed. Both models test whether portfolio managers have stock selection and market timing ability. The cross-sectional regression and the rank correlation test are implemented which account for both parametric and non-parametric approaches of persistence testing, respectively.

Weak evidence of stock selection as well as market timing ability was found. Moreover, most of the unit trusts are reported to have insignificant coefficients. When testing for performance persistence using returns, the Sharpe ratio and the Sortino ratio as performance metrics, the overall results also revealed weak evidence of persistence that is equally spread across winning and losing funds.

While research on unit trusts’ performance has been conducted in emerging economies, little has been done in testing for managerial ability in general and in South Africa in particular. Moreover, the research tends to focus more on one class – Equity General. This paper extends the performance literature by testing whether portfolio managers in the South African equity unit trusts industry have stock selection and market timing ability.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

This study aims to examine the market returns of the Ukrainian stock and bond markets to determine whether they exhibit calendar anomalies including the January effect, weekend effect, and turn‐of‐the‐month (TOM) effect. Ukraine provides an opportunity to examine the efficiency of an emerging market, adding to the extensive body of research on calendar anomalies.

Regression analysis is used to examine the relationship between January returns vs non‐January returns, Monday returns vs non‐Monday returns, and TOM returns vs non‐TOM returns. Non‐parametric t‐tests and Wilcoxon signed rank tests are also used to examine TOM returns vs the rest of the month returns.

There is no evidence of a January effect or a weekend effect in the Ukrainian stock and bond markets. However, our results support a TOM effect in the Ukrainian stock market. The mean daily TOM return is 0.35 vs 0.24 per cent for the rest of the month. Additionally, in 63 per cent of the months, the mean daily TOM return exceeds the return for the rest of the month.

The data are limited to five‐years of daily returns and two different Ukrainian indexes. Thus, the results could be biased by the time period analyzed. The results are important for portfolio managers and investors as they can benefit from the TOM effect, but not the January effect and weekend effect.

This is the first study to our knowledge that has extensively examined the calendar anomalies in the Ukrainian stock and bond markets.

The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility.

The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis.

The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility.

This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.