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Existing approaches have considered characteristics of Environmental, Social and Governance (ESG) focused investments from a return-oriented perspective, not paying due consideration to investors’ utility and how ESG features impact utility. We contribute

We propose a multivariate model of returns that accounts for four of the stylised facts of financial data: heavy tails, skew, volatility clustering, and asymmetric dependence with the aim of improving the accuracy of risk estimates and increasing out-of-sample utility of investors’ portfolios. We accommodate volatility clustering, the generalized Pareto distribution to capture heavy tails and skew, and the skewed-t copula to provide for asymmetric dependence. The proposed approach produces more accurate VaR estimates than seven competing approaches across eight data sets encompassing five asset classes. We show that this produces portfolios with higher utility, and lower downside risk than alternative approaches including mean-variance. We confirm that investors can substantially increase utility by accounting for departures from normality.

Emerging Market equity returns have proved challenging to model using conventional statistical tools. In this paper we use the conditional capital asset pricing model (CCAPM) together with an explicit expectations structure to arrive at a framework which can be easily estimated. We take the perspective that US equity corresponds to the market and that our investors are US dollar investors and use this approach to explain emerging market country index equity returns. Different choices of US equity index provide, unsurprisingly, different results. A noteworthy finding is that the Russell 2000 seems a better explanatory variable than the Russell 1000 suggesting that it is the small to medium capitalised US companies that help us understand emerging market returns.

INTRODUCTION Only 2.4% of the 16.5-kb mitochondrial DNA (mtDNA) genome shows homoplasmic variation at >1% frequency in humans. Migration patterns have contributed to geographic differences in the frequency of common genetic variants, but population genetic evidence indicates that selection shapes the evolving mtDNA phylogeny. The mechanism and timing of this process are not clear. Unlike the nuclear genome, mtDNA is maternally transmitted and there are many copies in each cell. Initially, a new genetic variant affects only a proportion of the mtDNA (heteroplasmy). During female germ cell development, a reduction in the amount of mtDNA per cell causes a “genetic bottleneck,” which leads to rapid segregation of mtDNA molecules and different levels of heteroplasmy between siblings. Although heteroplasmy is primarily governed by random genetic drift, there is evidence of selection occurring during this process in animals. Yet it has been difficult to demonstrate this convincingly in humans. RATIONALE To determine whether there is selection for or against heteroplasmic mtDNA variants during transmission, we studied 12,975 whole-genome sequences, including 1526 mother–offspring pairs of which 45.1% had heteroplasmy affecting >1% of mtDNA molecules. Harnessing both the mtDNA and nuclear genome sequences, we then determined whether the nuclear genetic background influenced mtDNA heteroplasmy, validating our findings in another 40,325 individuals. RESULTS Previously unknown mtDNA variants were less likely to be inherited than known variants, in which the level of heteroplasmy tended to increase on transmission. Variants in the ribosomal RNA genes were less likely to be transmitted, whereas variants in the noncoding displacement (D)–loop were more likely to be transmitted. MtDNA variants predicted to affect the protein sequence tended to have lower heteroplasmy levels than synonymous variants. In 12,975 individuals, we identified a correlation between the location of heteroplasmic sites and known D-loop polymorphisms, including the absence of variants in critical sites required for mtDNA transcription and replication. We defined 206 unrelated individuals for which the nuclear and mitochondrial genomes were from different human populations. In these individuals, new population-specific heteroplasmies were more likely to match the nuclear genetic ancestry than the mitochondrial genome on which the mutations occurred. These findings were independently replicated in 654 additional unrelated individuals. CONCLUSION The characteristics of mtDNA in the human population are shaped by selective forces acting on heteroplasmy within the female germ line and are influenced by the nuclear genetic background. The signature of selection can be seen over one generation, ensuring consistency between these two independent genetic systems.

The purpose of this paper is to investigate the dynamics and steady-state properties of threshold autoregressive models with exogenous states that follow Markovian processes; these processes are widely used in applied economics although their statistical properties have not been explored in detail. We use characteristic functions to carry out the analysis and this allows us to describe limiting distributions for processes not considered in the literature previously. We also calculate analytical expressions for some moments. Furthermore, we see that we can have locally explosive processes that are explosive in one regime whilst being strongly stationary overall. This is explored through simulation analysis where we also show how the distribution changes when the explosive state become more frequent although the overall process remains stationary. In doing so, we are able to relate our analysis to asset prices which exhibit similar distributional properties.

The selective entry of nanoparticles into target tissues is the key factor which determines their tissue distribution. Entry is primarily controlled by microvascular endothelial cells,\ud which have tissue-specific properties. This study investigated the cellular properties involved in selective transport of gold nanoparticles (

Mean-variance optimisation has been roundly criticised by financial economists and practitioners alike, leading many to advocate a simple 1/N weighting heuristic. We investigate the performance of the Markowitz technique conditional on investor forecasting ability. Using a novel analytical approach, we demonstrate that investors with a modicum of forecasting ability can employ mean-variance to significantly increase their ex ante utility, outperforming the 1/N rule.

In the matter of financial literacy it is often supposed that more is automatically preferable to less. This paper considers to what extent this may be true generally, and specifically focuses on the case of investment forecasting skill (a significant component of an individual's financial literacy). We show that the while improved forecasting skill can increase an individual's own utility, the resulting increase in trading volume leads to higher asset price volatility. Under the plausible assumption that this volatility imposes disutility on non-investors, an interesting trade-off is exposed between the benefits of skill improvement which accrue to investors, and the costs suffered more broadly by society. The paper constructs a formal analytic framework in which to discuss these issues, examines under what conditions the marginal utility of skill is in fact monotonic for the individual and considers implications for policy-makers.

The use of correlation between forecasts and actual returns is commonplace in the literature, often used as a measurement of investors’ skill. A prominent application of this is the concept of the Information Coefficient (IC). Not only can IC be used as a tool to rate analysts and fund managers but it also represents an important parameter in the asset allocation and portfolio construction process. Nevertheless, theoretical understanding of it has typically been limited to the partial equilibrium context where the investing activities of each agent have no effect on other market participants. In this paper we show that this can be an undesirable oversimplification and we demonstrate plausible circumstances in which conventional empirical measurements of IC can be highly misleading. We suggest that improved understanding of IC in a general equilibrium setting can lead to refined portfolio decision making ex ante and more informative analysis of performance ex post., Information Ratio

In light of recent regulatory initiatives focusing on fair treatment of customers in financial markets, this paper examines the agency problem created by an asset manager with market impact, segregated accounts and preference-based contracts. It illustrates how aggregate client welfare and assets under management are affected by the order in which clients' accounts are sequentially traded and demonstrates that the manager is unlikely to have incentives for equal treatment of clients. Effectively, she may conduct limited invisible transfers of wealth among largely uninformed clients by granting preferential market access to some of them and this may be purely the result of her dollar-alpha maximization efforts rather than size/importance-based client discrimination. Increased transparency and/or effective regulation in this area seem socially desirable since the manager's incentives and client welfare generally appear to be misaligned.

We assume that log equity prices follow multi-state threshold autoregressions and generalize existing results for threshold autoregressive models, presented in Knight and Satchell (2012) for the existence of a stationary process and the conditions necessary for the existence of a mean and a variance; we also present formulae for these moments. Using a simulation study we explore what these results entail with respect to the impact they can have on tests for detecting bubbles or market efficiency. We find that bubbles are easier to detect in processes where a stationary distribution does not exist. Furthermore, we explore how threshold autoregressive models with i.i.d trigger variables may enable us to identify how often asset markets are inefficient. We find, unsurprisingly, that the fraction of time spent in an efficient state depends upon the full specification of the model; the notion of how efficient a market is, in this context at least, a model-dependent concept. However, our methodology allows us to compare efficiency across different asset markets.

© 2015 The Authors. Efficient investment of personal savings depends on clear risk disclosures. We study the propensity of individuals to violate some implications of expected utility under alternative "mass-market" descriptions of investment risk, using a discrete choice experiment. We found violations in around 25% of choices, and substantial variation in rates of violation, depending on the mode of risk disclosure and participants' characteristics. When risk is described as the frequency of returns below or above a threshold we observe more violations than for range and probability-based descriptions. Innumerate individuals are more likely to violate expected utility than those with high numeracy. Apart from the very elderly, older individuals are less likely to violate the restrictions. The results highlight the challenges of disclosure regulation.

This paper applies LINEX loss functions to forecasting nonlinear functions of variance. We derive the optimal one-step-ahead LINEX forecast for various volatility models using data transformations such as ln(y2t) where yt is the return of the asset. Our results suggest that the LINEX loss function is particularly well-suited to many of these forecasting problems and can give better forecasts than conventional loss functions such as mean square error (MSE).