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This paper examines the zero‐cost risk reversal as a tool for increasing returns to excess yen while limiting risk. With domestic interest rates near zero, firms holding Japanese yen face little opportunity to deposit cash for meaningful gain unless excess funds are invested in an other currency. The conversion strategy is profitable as long as the value of the yen appreciates less than the interest rate differential between the currencies, taking advantage of an apparent empirical regularity frequently referred to as ‘forward exchange bias.’ A problem arises, however, because dollar‐yen exchange rate fluctuation adds variability to returns stated in yen. This increased risk counters prudent cash management principles such as stability of returns and liquidity. We consider the possi bility that effective use of a zero‐cost currency options collar can substantially limit exchange‐rate risk and improve returns to yen holders. Data from July 1997 through June 2002 show that a one‐year strategy of reinvesting collared monthly Eurodollar returns produced a median annual yen return of 1.76 per cent, more than 8 times the median 0.21 per cent Euroyen return; risk also increases but approximately 98 per cent of returns resulting from this strategy fell between ‐6.05 per cent and +12.58 per cent.

This paper aims to offer a commentary on recent failures in financial markets.

The approach is that of critical commentary on the present situation.

Current market dynamics reinforce the fact that there are few greater issues for financial institutions than governance and control systems.

The paper shows that financial institutions are still seeking to find the correct balance between risk and reward among the forces of financial innovation.

The purpose of this paper is to ascertain whether weather variables can explain the stock return reaction on the Dow Jones Sustainability Europe Index by employing a number of macroeconomic indicators as control variables.

The authors incorporate the generalized autogressive conditional heteroskeasticity model in methodology for the period August 26, 2009 to May 30, 2014 using daily data.

The empirical results indicate that not only do changes in humidity and wind levels seem to affect positively the European stock market but changes in returns oil and gold prices as well. However, the results show that the volatility of the US dollar/Yen exchange rate and ten-year bond value exerts significant negative impact on companies’ stock returns.

This study adds to the international literature by documenting the impact of weather variables on socially responsible companies.

Prior studies in citation-based journal rankings tend to be static to compare across journals. One journal may be judged better in citations than other journals at some points in time but not at the others. The assumption that the citation distribution is normally distributed and that the citation observations are independent and identically distributed (i.i.d.) may not be appropriate. The paper aims to discuss these issues.

This study uses a stochastic dominance (SD) analysis, which overcomes the dynamic nature of changes in citation over time. The SD method proposed by Linton, Maasoumi, and Whang (hereafter LMW, 2005) does not require the data to be i.i.d. We use the LMW method to compare the relative ranking of 23 finance journals using citations for all articles from them during 1990-2010.

The study indicates that the citation distribution changes over time. Thus a SD analysis is a better approach for a comparison of journal ranking. The findings unambiguously place JF, JFE, RFS, JFQA, and JFI in the top five spots of the finance journal ranking. The “near-top” journals, such as JBF, JCF, and FM, are not clear cut in the SD analysis.

The results confirm that ranking for the lower ranked journals may change over time especially, but the top three journals appear to be robust across methods and over time.

The results of SD analysis provides more convincing evidence on finance journal ranking and could be useful to rank academic institutions, faculty research quality, and help the authors to decide what to read and which journals are influential.

The purpose of this paper is to use a stochastic dominance test to examine the relative performance of value vs growth stocks based on multiple value-growth proxies in the Taiwan stock market.

This work examines whether the return distribution of a value portfolio stochastically dominates that of a growth portfolio using a test proposed by Linton et al. (2005).

By applying stochastic dominance analysis on the full-sample period, the sub-sample period and the state of the world’s economic conditions, the authors find that the earnings-to-price or dividend-to-price ratio is better than the book-to-market ratio as a value-growth proxy in Taiwan. There are robust results even after adjusting for data frequency, a sampling method and sample excluding financial services.

This study makes the first attempt to examine value vs growth strategies based on multiple value-growth proxies in the emerging market of Taiwan by administering the stochastic dominance test.

With suitable optimization criteria, hybrid models have proven to be efficient for preparing portfolios in capital markets of developed countries. This study adapts and investigates these methods for a developing country, thus providing a novel approach to the application of banking and finance. Our specific objectives are to employ a stochastic dominance criterion to evaluate the performances of over-the-counter (OTC) companies in a developing country and to analyze them with a hybrid model involving particle swarm optimization and artificial neural networks.

In order to achieve these aims, the authors conduct a case study of OTC companies in Iran. Weekly and daily returns of 36 companies listed in this market are calculated for one year during 2014–2015. The hybrid model is particularly interesting, and the results of the study identify first-, second- and third-order stochastic dominances among these companies. The study’s chosen model uses the best performing combination of activation functions in our analysis, corresponding to TPT, where T represents hyperbolic tangent transfers and P represents linear transfers.

Our portfolios are based on the shares of companies ranked with respect to the stochastic dominance criterion. Considering the minimum and maximum numbers of shares to be 2 and 10 for each portfolio, an eight-share portfolio is determined to be optimal. Compared with the index of Iran OTC during the research period of this study, our selected portfolio achieves a significantly better performance. Moreover, the methods used in this analysis are shown to be as efficient as they were in the capital markets of developed countries.

The problem of optimizing investment portfolios has to allow for correlations among returns from the financial maintenance period under consideration if an asymmetric distribution of returns exists (Babaei et al., 2015). Therefore, it is desirable to select an appropriate criterion in order to prepare an optimal portfolio and prioritize investment options. Although a back propagation technique is very popular in artificial neural (ANN) training, it is time-consuming to train a network in this way, and other methods such as particle swarm optimization (PSO) should be considered instead. In the hybrid combination of PSO and ANN, it is not the structure of a neural network that changes. Rather, the weighting method and the training technique chosen for the network are the important aspects, and these relate to PSO, so the only role ANN plays in this process is to reduce the errors.

The hybrid model combining ANN and PSO is seen to be considerably successful for generating optimal results and appropriate activation functions. These results are consistent with the theoretical findings of Das et al. (2013) and an application of the simple PSO in a study conducted by Pederson and Chipperfield (2010). Our research results also confirm the efficiency of stochastic dominance criteria as noted in the studies conducted by Roman et al. (2013), ANN as in a study carried out by Kristijanpoller et al. (2014) and PSO as in studies conducted by Liu et al. (2015) and Deng et al. (2012). These studies were carried out in the capital markets of developed countries, whereas the authors’ analysis relates to a developing country.

The authors deduce that the tools and methods whose efficiency was proven in the capital markets of developed countries also apply to, and demonstrate efficiency in, two novel applications of portfolio optimization within developing countries. The first of these is gaining familiarity with the theory and practice of these research tools and the methods that enrich financial knowledge of investors in developing countries. The second of these is the application of tools and methods identified by investors in the capital markets of developing countries, which enables optimal allocation of financial resources and growth of the markets. The authors expect that these findings will contribute to improving the economies of developing countries and thus help with economic development and facilitation of improving trends.

This study uses stochastic dominance (SD) theory to examine whether the traditional festival, such as the Spring Festival (often in February), affects the patterns of monthly anomaly for the Taiwan Stock Exchange (TWSE). The paper aims to discuss these issues.

The authors employ a new bootstrap-based test due to Linton, Maasoumi and Whang (hereafter LMW). The LMW test is well suited for financial time series data, such as monthly returns of various portfolios in this study, because it allows for general dependence among the prospects (distributions) and does not require the observations to be identically and independently distributed.

The particular findings of this study are that the February effect and the February-size effect indeed exist in the TWSE. Furthermore, allowing part of investors' assets is invested in the risky asset and the remaining part in a risk-free asset, first finding for monthly anomaly in the extant literature, is useful in distinguishing the performance among various size-month portfolios.

Instead of tax-loss and window dressing hypothesis, the Spring Festival money movement hypothesis can be used to well explain the findings.