Alternative Class Research Articles

Delegated Investment Management in Alternative Assets

Abstract Institutional investors can be segmented into investors that hold simple portfolios of traditional equities and bonds, and investors that manage complex strategies in public and private markets. Investors implementing active portfolio management and holding diversified portfolios of equities and bonds are more likely to invest in alternative asset classes. The performance of institutional investors in alternative assets is significantly lower than in equities, suggesting that investors accept lower returns in exchange for diversification benefits. Institutions delegate 90% of their alternative investments to external managers and funds-of-funds. These intermediaries capture large part of the potential diversification benefits through higher fees and lower returns. (JEL G11, G23) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Overview of Investing in Private Corporate Debt

Private debt is the second fastest growing alternative asset class behind private equity. Private debt refers to loans that are typically originated without the use of a bank or other financial intermediary. The private debt alternative asset class includes corporate debt, real estate debt, structured debt, and infrastructure debt. In this article, the author focuses on private corporate debt, the reasons for its rapid growth, the different credit strategies, the risks faced by investors in private debt programs, the estimated potential compensation for accepting those risks, and the challenges in managing a private debt program.

Pyramidal neuron subtype diversity governs microglia states in the neocortex.

Microglia are specialized macrophages in the brain parenchyma that exist in multiple transcriptional states and reside within a wide range of neuronal environments1-4. However, how and where these states are generated remains poorly understood. Here, using the mouse somatosensory cortex, we demonstrate that microglia density and molecular state acquisition are determined by the local composition of pyramidal neuron classes. Using single-cell and spatial transcriptomic profiling, we unveil the molecular signatures and spatial distributions of diverse microglia populations and show that certain states are enriched in specific cortical layers, whereas others are broadly distributed throughout the cortex. Notably, conversion of deep-layer pyramidal neurons to an alternate class identity reconfigures the distribution of local, layer-enriched homeostatic microglia to match the new neuronal niche. Leveraging the transcriptional diversity of pyramidal neurons in the neocortex, we construct a ligand-receptor atlas describing interactions between individual pyramidal neuron subtypes and microglia states, revealing rules of neuron-microglia communication. Our findings uncover a fundamental role for neuronal diversity in instructing the acquisition of microglia states as a potential mechanism for fine-tuning neuroimmune interactions within the cortical local circuitry.

Testing for structural changes in large dimensional factor models via discrete Fourier transform

We propose a new test for structural changes in large dimensional factor models using a discrete Fourier transform (DFT) approach. When structural changes occur, the conventional principal component analysis may fail to estimate the common factors and factor loadings consistently, and the estimated residuals contain information about the structural changes. This allows us to compare the DFT of the estimated residuals weighted by the estimated common factors with the null (zero) spectrum implied by no structural change. The proposed test is powerful against both smooth structural changes and abrupt structural breaks with an unknown number of breaks and unknown break dates in factor loadings. It can detect a class of local alternatives at the rate N−1/2T−1/2, where N and T are the numbers of cross-sectional units and time periods, respectively. Monte Carlo studies demonstrate that the proposed test has reasonable size and excellent power in detecting various structural changes in factor loadings. When applied to the U.S. macroeconomic data, the test reveals significant and robust evidence of time-varying factor loadings for the post-Great Moderation sample and the pre-Great Recession subsample, which the existing literature may fail to address.

On universally consistent and fully distribution-free rank tests of vector independence

Rank correlations have found many innovative applications in the last decade. In particular, suitable rank correlations have been used for consistent tests of independence between pairs of random variables. Using ranks is especially appealing for continuous data as tests become distribution-free. However, the traditional concept of ranks relies on ordering data and is, thus, tied to univariate observations. As a result, it has long remained unclear how one may construct distribution-free yet consistent tests of independence between random vectors. This is the problem addressed in this paper, in which we lay out a general framework for designing dependence measures that give tests of multivariate independence that are not only consistent and distribution-free but which we also prove to be statistically efficient. Our framework leverages the recently introduced concept of center-outward ranks and signs, a multivariate generalization of traditional ranks, and adopts a common standard form for dependence measures that encompasses many popular examples. In a unified study, we derive a general asymptotic representation of center-outward rank-based test statistics under independence, extending to the multivariate setting the classical Hájek asymptotic representation results. This representation permits direct calculation of limiting null distributions and facilitates a local power analysis that provides strong support for the center-outward approach by establishing, for the first time, the nontrivial power of center-outward rank-based tests over root-n neighborhoods within the class of quadratic mean differentiable alternatives.

Portfolio risk and stress across the business cycle

In this study, we investigate the interactions of daily tail risk estimates of thirty market indices representing a broad spectrum of asset classes and geographies from 2003 till 2021 and document important findings. Using a step-by-step conditional copula with orthogonalized GARCH margins augmented further with Markov-switching transitions, we study the dependence structure across the asset classes. Our results predominantly indicate the presence of contagion in tail risk across assets and geographies, especially during economy-wide stress. Our results suggest that alternative asset classes are crucial in mitigating overall portfolio risk. Our results also show the magnitude of tail risk contagion amongst countries studied.

Sample entropy applied to test of fit for Lindley distribution and power comparison

This work is devoted to construction of goodness-of-fit test statistics for the Lindley model. The proposed test statistics are based on the sample entropy. The properties of the tests and critical points of them for various sample sizes are obtained. An empirical power comparison study is then conducted using Monte Carlo simulations, under various alternatives and for different sample sizes. The new tests exhibit good performance in terms of power in comparison to the EDF-based test statistics. A discussion of the results follows, where the best tests are selected for different classes of alternatives. Finally, a real dataset is analyzed for illustrative purposes.

Susceptibility status of the wild-caught Phlebotomus argentipes (Diptera: Psychodidae: Phlebotominae), the sand fly vector of visceral leishmaniasis, to different insecticides in Nepal.

BackgroundVisceral leishmaniasis (VL) is targeted for elimination as a public health problem in Nepal by 2023. For nearly three decades, the core vector control intervention in Nepal has been indoor residual spraying (IRS) with pyrethroids. Considering the long-term use of pyrethroids and the possible development of resistance in the vector Phlebotomus argentipes sand flies, we monitored the susceptibility status of their field populations to the insecticides of different classes, in villages with and without IRS activities in recent years.Methodology/Principal findingsSand flies were collected from villages with and without IRS in five VL endemic districts from August 2019 to November 2020. The WHO susceptibility test procedure was adopted using filter papers impregnated at the discriminating concentrations of insecticides of the following classes: pyrethroids (alpha-cypermethrin 0.05%, deltamethrin 0.05%, and lambda-cyhalothrin 0.05%), carbamates (bendiocarb 0.1%) and organophosphates (malathion 5%). Pyrethroid resistance intensity bioassays with papers impregnated with 5× of the discriminating concentrations, piperonyl butoxide (PBO) synergist-pyrethroid bioassays, and DDT cross-resistance bioassays were also performed. In the IRS villages, the vector sand flies were resistant (mortality rate <90%) to alpha-cypermethrin and possibly resistant (mortality rate 90–97%) to deltamethrin and lambda-cyhalothrin, while susceptibility to these insecticides was variable in the non-IRS villages. The vector was fully susceptible to bendiocarb and malathion in all villages. A delayed knockdown time (KDT50) with pyrethroids was observed in all villages. The pyrethroid resistance intensity was low, and the susceptibility improved at 5× of the discriminating concentrations. Enhanced pyrethroid susceptibility after pre-exposure to PBO and the DDT-pyrethroid cross-resistance were evident.Conclusions/SignificanceOur investigation showed that P. argentipes sand flies have emerged with pyrethroid resistance, suggesting the need to switch to alternative classes of insecticides such as organophosphates for IRS. We strongly recommend the regular and systematic monitoring of insecticide resistance in sand flies to optimize the efficiency of vector control interventions to sustain VL elimination efforts in Nepal.

Class I Polyhydroxyalkanoate (PHA) Synthase Increased Polylactic Acid Production in Engineered Escherichia Coli.

Polylactic acid (PLA), a homopolymer of lactic acid (LA), is a bio-derived, biocompatible, and biodegradable polyester. The evolved class II PHA synthase (PhaC1 Ps6-19) was commonly utilized in the de novo biosynthesis of PLA from biomass. This study tested alternative class I PHA synthase (PhaC Cs ) from Chromobacterium sp. USM2 in engineered Escherichia coli for the de novo biosynthesis of PLA from glucose. The results indicated that PhaC Cs had better performance in PLA production than that of class II synthase PhaC1 Ps6-19. In addition, the sulA gene was engineered in PLA-producing strains for morphological engineering. The morphologically engineered strains present increased PLA production. This study also tested fused propionyl-CoA transferase and lactate dehydrogenase A (fused Pct Cp /LdhA) in engineered E. coli and found that fused Pct Cp /LdhA did not apparently improve the PLA production. After systematic engineering, the highest PLA production was achieved by E. coli MS6 (with PhaC Cs and sulA), which could produce up to 955.0 mg/L of PLA in fed-batch fermentation with the cell dry weights of 2.23%, and the average molecular weight of produced PLA could reach 21,000 Da.

Evolving objective function for improved variational quantum optimization

A promising approach to useful computational quantum advantage is to use variational quantum algorithms for optimization problems. Crucial for the performance of these algorithms is to ensure that the algorithm converges with high probability to a near-optimal solution in a small time. In Barkoutsos et al. [Quantum 4, 256 (2020)], an alternative class of objective functions, called conditional value at risk (CVaR), was introduced and it was shown that they perform better than standard objective functions. Here we extend that work by introducing an evolving objective function, which we call ascending-CVaR and that can be used for any optimization problem. We test our proposed objective function in an emulation environment, using as case studies three different optimization problems: MaxCut, number partitioning, and portfolio optimization. We examine multiple instances of different sizes and analyze the performance using the variational quantum eigensolver with hardware-efficient ansatz and the quantum approximate optimization algorithm. We show that ascending-CVaR in all cases performs better than standard objective functions or the constant CVaR of Barkoutsos et al. [Quantum 4, 256 (2020)] and that it can be used as a heuristic for avoiding suboptimal minima. Our proposal achieves higher overlap with the ideal state in all problems, whether we consider easy or hard instances---on average, it gives up to ten times greater overlap at portfolio optimization and number partitioning, while it gives an 80% improvement at MaxCut. In the hard instances we consider, for the number partitioning problem, standard objective functions fail to find the correct solution in almost all cases, CVaR finds the correct solution at 60% of the cases, while ascending-CVaR finds the correct solution in 95% of the cases.

PiRNA-like small RNAs target transposable elements in a Clade IV parasitic nematode

The small RNA (sRNA) pathways identified in the model organism Caenorhabditis elegans are not widely conserved across nematodes. For example, the PIWI pathway and PIWI-interacting RNAs (piRNAs) are involved in regulating and silencing transposable elements (TE) in most animals but have been lost in nematodes outside of the C. elegans group (Clade V), and little is known about how nematodes regulate TEs in the absence of the PIWI pathway. Here, we investigated the role of sRNAs in the Clade IV parasitic nematode Strongyloides ratti by comparing two genetically identical adult stages (the parasitic female and free-living female). We identified putative small-interfering RNAs, microRNAs and tRNA-derived sRNA fragments that are differentially expressed between the two adult stages. Two classes of sRNAs were predicted to regulate TE activity including (i) a parasite-associated class of 21–22 nt long sRNAs with a 5′ uridine (21-22Us) and a 5′ monophosphate, and (ii) 27 nt long sRNAs with a 5′ guanine/adenine (27GAs) and a 5′ modification. The 21-22Us show striking resemblance to the 21U PIWI-interacting RNAs found in C. elegans, including an AT rich upstream sequence, overlapping loci and physical clustering in the genome. Overall, we have shown that an alternative class of sRNAs compensate for the loss of piRNAs and regulate TE activity in nematodes outside of Clade V.

An alternative class of models to position social network groups in latent spaces

Identifying key nodes, estimating the probability of connection between them, and distinguishing latent groups are some of the main objectives of social network analysis. In this paper, we propose a class of blockmodels to model stochastic equivalence and visualize groups in an unobservable space. In this setting, the proposed method is based on two approaches: latent distances and latent dissimilarities at the group level. The projection proposed in the paper is performed without needing to project individuals, unlike the main approaches in the literature. Our approach can be used in undirected or directed graphs and is flexible enough to cluster and quantify between and within-group tie probabilities in social networks. The effectiveness of the methodology in representing groups in latent spaces was analyzed under artificial datasets and in two case studies.

Resilient Adaptive Neural Control for Uncertain Nonlinear Systems With Infinite Number of Time-Varying Actuator Failures.

Existing studies on adaptive fault-tolerant control for uncertain nonlinear systems with actuator failures are restricted to a common result that only system stability is established. Such a result of not being asymptotically stable is a tradeoff paid for reducing the number of online learning parameters. In this article, we aim to obviate such restrictions and improve the bounded error control to asymptotic control. Toward this end, a resilient adaptive neural control scheme is newly proposed based on a new design of the Lyapunov function candidates, a projection-associated tuning functions method, and an alternative class of smooth functions. It is proved that the system stability is guaranteed for the case of an infinite number of failures and when the number of failures is finite, asymptotic tracking performance can be automatically recovered, and besides, an explicit bound for the tracking error in terms of L2 norm is established. Illustrative examples demonstrate the methods developed.

Evaluation of Antipsychotic Reduction Efforts in Patients With Dementia in Veterans Health Administration Nursing Homes.

The Veterans Health Administration (VHA) and the Centers for Medicare and Medicaid Services (CMS) each created initiatives to reduce off-label use of antipsychotics in patients with dementia in nursing homes. Although CMS has reported antipsychotic reductions, the impact on prescribing of antipsychotic and other CNS-active medications in the VHA remains unclear. The authors evaluated national trends in antipsychotic and other CNS-active medication prescribing for nursing home patients with dementia in the VHA. The study sample was all veterans with dementia residing in VHA nursing homes for more than 30 days (N=35,742). Using an interrupted time-series design, the quarterly prevalences of antipsychotic, antidepressant, antiepileptic, anxiolytic, opioid, and memory medication prescribing were evaluated from FY2009 through FY2018. Antipsychotic prescribing in VHA nursing homes declined from FY2009 to FY2018 (from 33.7% to 27.5%), with similar declines in anxiolytic prescribing (from 33.5% to 27.1%). During this period, prescribing of antiepileptics, antidepressants, and opioids increased significantly (antiepileptics: from 26.8% to 43.3%; antidepressants: from 56.8% to 63.4%; opioids: from 32.6% to 41.2%). Gabapentin served as the main driver of antiepileptic increases (from 11.1% to 23.5%). Increases in antidepressant prescribing included sertraline, mirtazapine, and trazodone. From FY2009 to FY2018, the overall prescribing of non-antipsychotic psychotropic medications grew from 75.0% to 81.1%. Antipsychotic and anxiolytic prescribing for VHA nursing home residents with dementia declined, although overall prescribing of other psychotropic and opioid medications increased. Policies focused primarily on reducing antipsychotic use without considering use in the context of other medications may contribute to growth in alternative medication classes with even less evidence of benefit and similar risks.

Kidney Effects by Alternative Classes of Medicines in Patients and Relationship to Effects in Nonclinical Toxicity Studies

Drug-induced kidney injury has historically been associated with renal tubule injury related to small molecule pharmaceuticals such as nonsteroidal anti-inflammatory drugs, antineoplastic agents, or antibiotics, but as a greater number of alternative classes of medicines such as biotherapeutics, molecular-targeted antineoplastic drugs, chimeric antigen receptor T-cell therapies, antibody-drug conjugates, oligonucleotide therapies, or other immunomodulatory drugs come to market, the presentation of drug-induced nephrotoxicity is changing. This review article describes the potential rare clinical events in drug-induced kidney injury that might be noted with these new therapies and their potential impact on patients. Potential pathogenic mechanisms related to immunogenicity, immune complex formation, and stimulation of downstream proinflammatory pathways with some of these alternative medicine classes have resulted in the potential for glomerulonephritis, acute interstitial nephritis, renal vasculitis, and other immune-mediated renal disorders in humans. This contrasts with nonclinical toxicity studies, where biologic therapies more often result in vasculitis and glomerulonephritis associated with antidrug antibodies and immunomodulatory pharmacology, and which are not always predictive of clinical effects. While nonclinical antidrug antibody-related renal disease is generally not clinically relevant, other immune-mediated nephrotoxicities associated with immunomodulatory drugs may be predictive of clinical adverse events. Fortunately, these conditions are still rare and account for a small percentage of serious adverse events in kidneys of patients.

“Water‐in‐Eutectogel” Electrolytes for Quasi‐Solid‐State Aqueous Lithium‐Ion Batteries

AbstractThe development of high safety lithium‐ion batteries (LIBs) is greatly impeded by the flammability and leakage concerns of typical organic solvent‐based electrolytes. As one of the alternative classes of electrolytes, hydrogel electrolytes exhibit high safety, high flexibility, low cost, and are benign to the environment. However, the narrow electrochemical stability window (ESW) of typical hydrogel electrolytes restricts the operating voltage of battery cells. Here, a new class of “water‐in‐eutectogel (WiETG)” electrolyte is reported, fabricated by combining a hydrogel with a “deep eutectic solvent” (LiTFSI in acetamide). The obtained WiETG electrolyte exhibits non‐flammability, high ionic conductivity, and a wide ESW. LiMn2O4||Li4Ti5O12 cells with the WiETG electrolyte exhibit good cycling stability, high flexibility, and high safety. This newly developed WiETG electrolyte not only broadens the ESW of typical hydrogel electrolytes, but also opens a new perspective on future directions and guidance for the design of high safety electrolytes for flexible LIBs and beyond.

On Alternative Approximating Distributions in the Multivariate Version of Kolmogorov's Second Uniform Limit Theorem

The aim of the present work is to show that recent results of the authors on the approximation of distributions of sums of independent summands by the infinitely divisible laws on convex polyhedra can be shown via an alternative class of approximating infinitely divisible distributions. We will also generalize the results to the infinite-dimensional case.

Do volatility spillover and hedging among GCC stock markets and global factors vary from normal to turbulent periods? Evidence from the global financial crisis and Covid-19 pandemic crisis

In this paper, we use a bivariate VAR-asymmetric-BEKK-GARCH model to examine returns, asymmetric volatility spillovers, and time-varying correlations among GCC stock markets (Saudi Arabia, UAE, Qatar, Kuwait, Oman, and Bahrain) and five global factors (Islamic stocks, oil, gold, bonds, and real estate) from July 5, 2004, to March 31, 2021. To take into account the effects of the global financial crisis (GFC) and recent COVID-19 pandemic, we divide the sample period into four sub-periods: the full sample without COVID-19, pre-GFC, post-GFC, and the COVID-19 crisis. The empirical results indicate significant return and volatility spillovers between the GCC stock markets and global factors. Moreover, these spillovers between GCC stock markets and global factors increase in both the return and variance during turbulent periods (post-GFC and COVID-19 crisis periods). The time-varying correlations reveal that gold serves as a hedge and safe haven against most of the GCC stock markets in all sample periods, whereas the results vary across markets and sample periods for bonds, oil, Islamic stocks, and real estate assets against the GCC stocks. Our findings provide useful insights for investors and portfolio managers formulating trading strategies, determining asset allocation, and assembling optimal portfolios, since they persistently pursue challenging investment ideas and alternative asset classes, especially at times of financial crisis and global recession.

Silhouettes and Quasi Residual Plots for Neural Nets and Tree-based Classifiers

Classification by neural nets and by tree-based methods are powerful tools of machine learning. There exist interesting visualizations of the inner workings of these and other classifiers. Here we pursue a different goal, which is to visualize the cases being classified, either in training data or in test data. An important aspect is whether a case has been classified to its given class (label) or whether the classifier wants to assign it to a different class. This is reflected in the (conditional and posterior) probability of the alternative class (PAC). A high PAC indicates label bias, that is, the possibility that the case was mislabeled. The PAC is used to construct a silhouette plot which is similar in spirit to the silhouette plot for cluster analysis. The average silhouette width can be used to compare different classifications of the same dataset. We will also draw quasi residual plots of the PAC versus a data feature, which may lead to more insight in the data. One of these data features is how far each case lies from its given class. The graphical displays are illustrated and interpreted on datasets containing images, mixed features, and tweets. Supplementary materials for this article are available online.

Real-World Treatment Strategies to Improve Outcomes in Patients With Chronic Idiopathic Constipation and Irritable Bowel Syndrome With Constipation.

Chronic idiopathic constipation and irritable bowel syndrome with constipation are complex, overlapping conditions. Although multiple guidelines have informed healthcare providers on appropriate treatment options for patients with chronic idiopathic constipation and irritable bowel syndrome with constipation, little direction is offered on treatment selection. First-line treatment options usually include fiber and over-the-counter osmotic laxatives; however, these are insufficient for many individuals. When these options fail, prescription secretagogues (plecanatide, linaclotide, lubiprostone, and tenapanor [pending commercial availability]), or serotonergic agents (prucalopride and tegaserod) are generally preferred. Individuals experiencing concurrent abdominal pain and/or bloating may experience greater overall improvements from prescription therapies because these agents have been proven to reduce concurrent abdominal and bowel symptoms. Should initial prescription treatments fail, retrying past treatment options (if not adequately trialed initially), combining agents from alternative classes, or use of adjunctive therapies may be considered. Given the broad spectrum of available agents, therapy should be tailored by mutual decision-making between the patient and practitioner. Overall, patients need to be actively monitored and managed to maximize clinical outcomes.