On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques.By combining two variants of the Free Disposal Hull (FDH) methods (order-m and order-?) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI.These results show the benefits of performing the analysis using quantile regression.

On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques. By combining two variants of the Free Disposal Hull (FDH) methods (order- m and order- α) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI. These results show the benefits of performing the analysis using quantile regression. © 2013 Elsevier B.V.

Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

Do ethics imply persistence? The case of Islamic and socially responsible funds

We analyse the performance persistence of Islamic and Socially Responsible Investment (SRI) mutual funds. We adopt a multi-stage strategy in which, in the first stage, partial frontiers’ approaches are considered to measure the performance of the different funds in the sample. In the second stage, the results yielded by the partial frontiers are plugged into different investment strategies based on a recursive estimation methodology whose persistence performance is evaluated in the third stage of the analysis. Results indicate that, for both types of funds, performance persistence actually exists, but only for the worst and, most notably, best funds. This result is robust not only across methods (and different choices of tuning parameters within each method) but also across both SRI and Islamic funds—although in the case of the latter persistence was stronger for the best funds. The persistence of SRI and Islamic funds represents an important result for investors and the market, since it provides information on both which funds to invest in and which funds to avoid. Last but not least, the use of the aforementioned techniques in the context of mutual funds could also be of interest for the non-conclusive literature.

Statistical mechanics of mutual information maximization

An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed (Becker S. and Hinton G., Nature, 355 (1992) 161). By exploiting a formal analogy to supervised learning in parity machines, the theory of zero-temperature Gibbs learning for the unsupervised procedure is presented for the case that the networks are perceptrons and for the case of fully connected committees.

Do external funds yield lower returns? Recent evidence from East Asian economies

One of the central explanations of the recent Asian Crisis has been the problem of moral hazard as the source of over-investment and excessive external borrowing. There is however rather limited firm-level empirical evidence to characterise inefficient use of internal and external finances. Using a large firm-level panel data-set from four badly affected Asian countries, this paper compares the rates of return to various internal and external funds among firms with low and high debt financing (relative to equity) among financially constrained and other firms. Selectivity-corrected estimates obtained from random effects panel data model do suggest evidence of significantly lower rates of return to long-term debt, even among firms relying more on debt relative to equity in our sample. There is also evidence that average effective interest rates often significantly exceeded the average returns to long-term debt in the sample countries in the pre-crisis period. © 2006 Elsevier Inc. All rights reserved.

The adverse selection component of exchange traded funds

The aim of our paper is to examine whether Exchange Traded Funds (ETFs) diversify away the private information of informed traders. We apply the spread decomposition models of Glosten and Harris (1998) and Madhavan, Richardson and Roomans (1997) to a sample of ETFs and their control securities. Our results indicate that ETFs have significantly lower adverse selection costs than their control securities. This suggests that private information is diversified away for these securities. Our results therefore offer one explanation for the rapid growth in the ETF market.

Exchange-traded funds and information asymmetry

This thesis focuses on three main questions. The first uses ExchangeTraded Funds (ETFs) to evaluate estimated adverse selection costs obtained spread decomposition models. The second compares the Probability of Informed Trading (PIN) in Exchange-Traded Funds to control securities. The third examines the intra-day ETF trading patterns. These spread decomposition models evaluated are Glosten and Harris (1988); George, Kaul, and Nimalendran (1991); Lin, Sanger, and Booth (1995); Madhavan, Richardson, and Roomans (1997); Huang and Stoll (1997). Using the characteristics of ETFs it is shown that only the Glosten and Harris (1988) and Madhavan, et al (1997) models provide theoretically consistent results. When the PIN measure is employed ETFs are shown to have greater PINs than control securities. The investigation of the intra-day trading patterns shows that return volatility and trading volume have a U-shaped intra-day pattern. A study of trading systems shows that ETFs on the American Stock Exchange (AMEX) have a U-shaped intra-day pattern of bid-ask spreads, while ETFs on NASDAQ do not. Specifically, ETFs on NASDAQ have higher bid-ask spreads at the market opening, then the lowest bid-ask spread in the middle of the day. At the close of the market, the bid-ask spread of ETFs on NASDAQ slightly elevated when compared to mid-day.

Doctoral work in translation studies as an interdisciplinary mutual learning process:how a translator, teacher educator and linguistic typologist worked together

The focus of this paper is on the doctoral research training experienced by one of the authors and the ways in which the diverse linguistic and disciplinary perspectives of her two supervisors (co-authors of this paper) mediated the completion of her study. The doctoral candidate is a professional translator/interpreter and translation teacher. The paper describes why and how she identified her research area and then focused on the major research questions in collaboration with her two supervisors, who brought their differing perspectives from the field of linguistics to this translation research, even though they are not translators by profession or disciplinary background and do not speak Korean. In addition, the discussion considers the focus, purpose and theoretical orientation of the research itself (which addressed questions of readability in translated English-Korean texts through detailed analysis of a corpus and implications for professional translator training) as well as the supervisory and conceptual processes and practices involved. The authors contend that doctoral research of this kind can be seen as a mutual learning process and that inter-disciplinary research can make a contribution not only to the development of rigorous research in the field of translation studies but also to the other disciplinary fields involved.

Intraday trading patterns in London listed exchange traded funds

In this paper we examine the intraday trading patterns of Exchange Traded Funds (ETFs) listed on the London Stock Exchange. ETFs have been shown to be characterised by much lower bid–ask spread costs and by lower levels of information asymmetry than individual securities. One possible explanation for intraday trading patterns is that concentration of trading arises at the start of the trading day because informed traders have private information that quickly diminishes in value as trading progresses. Since ETFs have lower trading costs and lower levels of information asymmetry we would expect these securities to display less pronounced intraday patterns than individual securities. We fail to find that ETFs are characterised by concentrated trading bouts during the day and therefore find support for the argument that information asymmetry is the cause of intraday volume patterns in stock markets. We find that ETF bid–ask spreads and volatility are elevated at the open but not at the close. This lends support to the “accumulation of information” explanation that sees high spreads and volatility at the open as a consequence of information accumulating during a market closure and impacting on the market when it next opens.

Reconnection dynamics and mutual friction in quantum turbulence

We investigate the behaviour of the mutual friction force in finite temperature quantum turbulence in 4He, paying particular attention to the role of quantized vortex reconnections. Through the use of the vortex filament model, we produce three experimentally relevant types of vortex tangles in steady-state conditions, and examine through statistical analysis, how local properties of the tangle influence the mutual friction force. Finally, by monitoring reconnection events, we present evidence to indicate that vortex reconnections are the dominant mechanism for producing areas of high curvature and velocity leading to regions of high mutual friction, particularly for homogeneous and isotropic vortex tangles.

Structural funds and the knowledge-based economy:a regional case-study (1999-2009)

The research presented in this thesis investigates the nature of the relationship between the development of the Knowledge-Based Economy (KBE) and Structural Funds (SF) in European regions. A particular focus is placed on the West Midlands (UK) and Silesia (Poland). The time-frame taken into account in this research is the years 1999 to 2009. This is methodologically addressed by firstly establishing a new way of calculating the General Index of the KBE for all of the EU regions; secondly, applying a number of statistical methods to measure the influence of the Funds on the changes in the regional KBE over time; and finally, by conducting a series of semi-structured stakeholder interviews in the two key case study regions: the West Midlands and Silesia. The three main findings of the thesis are: first, over the examined time-frame, the values of the KBE General Index increased in over 66% of the EU regions; furthermore, the number of the “new” EU regions in which the KBE increased over time is far higher than in the “old” EU. Second, any impact of Structural Funds on the regional KBE occurs only in the minority of the European regions and any form of functional dependency between the two can be observed only in 30% of the regions. Third, although the pattern of development of the regional KBE and the correlation coefficients differ in the cases of Silesia and the West Midlands, the analysis of variance carried out yields identical results for both regions. Furthermore, the qualitative analysis’ results show similarities in the approach towards the Structural Funds in the two key case-study regions.