Defining social investing and its boundaries is a challenging task. Since the religious beginning of ethical investments, many overlapping investment styles have been grouped into the bucket of socially responsible investments, or SRI. This includes, for instance, faith-based investments. In this paper we study the underlying principles of SRI and Islamic funds as investment classes, and try to determine whether Islamic mutual funds, as faith-based investments, can be included into the category of socially responsible mutual funds, or if they exhibit distinguishing characteristics that indicate that they would be more fittingly grouped in a separate investment family. We address the question from both a qualitative and quantitative point of view. Comparing ideas, ratios and investment styles underlying SRI and comparing them to Islamic portfolios, we identify the potential inconsistencies related to some of the investment decisions. Together with a qualitative assessment of the differences and similarities, we discuss, in the quantitative section of our study, the different sector and country composition of two generic portfolios, SRI and Islamic (proxied by relevant European indices), derived from the application of the investment screens. In addition, through a cointegration analysis on FTSE indices, we show that FTSE Islamic, exhibits peculiar and interesting portfolios' differences in terms of econometric profile, compared to conventional and SRI indices. This paper attempts to unify the studies regarding SRI, with the available studies on Islamic investments. To the best of authors' knowledge, this is the first time that SRI and Islamic indices are analysed and compared. JEL Classification : G12, G14
This paper proposes a novel approach to directional forecasts for carry trade strategies based on support vector machines (SVMs), a learning algorithm that delivers extremely promising results. Building on recent findings in the literature on carry trade, we condition the SVM on indicators of uncertainty and risk. We show that this provides a dramatic performance improvement in strategy, particularly during periods of financial distress such as the recent financial crises. Disentangling the measures of risk, we show that conditioning the SVM on measures of liquidity risk rather than on market volatility yields the best performance.
We analyse the factors influencing the target company's choice of bank advisor in mergers and acquisitions (M&As). We first examine the choice of hiring an advisor, which is nontrivial, since in one-third of transactions our sample target companies did not hire one. We also analyse the choice to hire as advisor a bank with a strong prior relationship with the company (i.e., the main bank). Using data on 473 European M&A transactions completed in the period 1994-2003, we find evidence that the decision to hire an advisor depends on three main factors: (i) the intensity of the previous banking relationship, (ii) the reputation of the bidder company's advisor, and (iii) the complexity of the deal. We also investigate the impact of the bank advisor on shareholder wealth. We find that the abnormal returns of target company shareholders increase with the intensity of the previous banking relationship, thus indicating a 'certification role' on the part of investment banks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.