48 results found
The paper focuses on econometrically justified robust analysis of the effects of the COVID-19 pandemic on financial markets in different countries across the World. It provides the results of robust estimation and inference on predictive regressions for returns on major stock indexes in 23 countries in North and South America, Europe, and Asia incorporating the time series of reported infections and deaths from COVID-19. We also present a detailed study of persistence, heavy-tailedness and tail risk properties of the time series of the COVID-19 infections and death rates that motivate the necessity in applications of robust inference methods in the analysis. Econometrically justified analysis is based on heteroskedasticity and autocorrelation consistent (HAC) inference methods, recently developed robust t-statistic inference approaches and robust tail index estimation.
Suba K, Hansen B, Patel Y, et al., 2022, Beta cell functional heterogeneity underpinning coordinated oscillatory activity is not fixed, Publisher: SPRINGER, Pages: S121-S121, ISSN: 0012-186X
Distaso W, Malik MMAH, Semere S, et al., 2022, Diabetes self-management during the COVID-19 pandemic and its associations with COVID-19 anxiety syndrome, depression and health anxiety, Publisher: WILEY, ISSN: 0742-3071
Eng PC, Distaso W, Durreshahwar H, et al., 2022, The benefit of dexamethasone in patients with COVID-19 infection is preserved in patients with diabetes., Diabetes, Obesity and Metabolism: a journal of pharmacology and therapeutics, Vol: 24, Pages: 1385-1389, ISSN: 1462-8902
Dexamethasone significantly reduces mortality1 and is now standard treatment for patients with COVID-19 who require supplemental oxygen and/or mechanical ventilation. However, supraphysiological doses of glucocorticoids may exacerbate dysglycaemia and precipitate hyperglycaemic complications, particularly in those with or at risk of Type 2 diabetes2. The RECOVERY trial1 reported a low incidence of hyperglycaemic complications (2/1996, 0.1%), although the real-world incidence is likely to be much higher3. Type 2 diabetes itself increases the risk of severe COVID-194, and hyperglycaemia independently predicts poor outcomes5. We investigated the possibility that patients with diabetes may derive less survival benefit from steroid therapy in the setting of severe COVID-19 infection
Abadir KM, Distaso W, Giraitis L, 2021, Partially one-sided semiparametric inference for trending persistent and antipersistent processes, Econometrics and Statistics, ISSN: 2452-3062
Hypothesis testing in models allowing for trending processes that are possibly nonstationary and non-Gaussian is considered. Using semiparametric estimators, joint hypothesis testing for these processes is developed, taking into account the one-sided nature of typical hypotheses on the persistence parameter in order to gain power. The results are applicable for a wide class of processes and are easy to implement. They are illustrated with an application to the dynamics of GDP.
de Jesus DS, Mak TCS, Wang Y-F, et al., 2021, Dysregulation of the Pdx1/Ovol2/Zeb2 axis in dedifferentiated β-cells triggers the induction of genes associated with epithelial-mesenchymal transition in diabetes, Molecular Metabolism, Vol: 53, ISSN: 2212-8778
OBJECTIVE: β-cell dedifferentiation has been revealed as a pathological mechanism underlying pancreatic dysfunction in diabetes. We previously showed that increased miR-7 levels trigger β-cell dedifferentiation and diabetes. We used β-cell-specific miR-7 overexpressing mice (Tg7) to test the hypothesis that loss of β-cell identity triggered by miR-7 overexpression alters islet gene expression and islet microenvironment in diabetes. METHODS: We performed bulk and single-cell RNA sequencing (RNA-seq) in islets obtained from β-cell-specific miR-7 overexpressing mice (Tg7). We carried out loss- and gain-of-function experiments in MIN6 and EndoC-bH1 cell lines. We analysed previously published mouse and human T2D data sets. RESULTS: Bulk RNA-seq revealed that β-cell dedifferentiation is associated with the induction of genes associated with epithelial-to-mesenchymal transition (EMT) in prediabetic (2-week-old) and diabetic (12-week-old) Tg7 mice. Single-cell RNA-seq (scRNA-seq) indicated that this EMT signature is enriched specifically in β-cells. These molecular changes are associated with a weakening of β-cell: β-cell contacts, increased extracellular matrix (ECM) deposition, and TGFβ-dependent islet fibrosis. We found that the mesenchymal reprogramming of β-cells is explained in part by the downregulation of Pdx1 and its inability to regulate a myriad of epithelial-specific genes expressed in β-cells. Notable among genes transactivated by Pdx1 is Ovol2, which encodes a transcriptional repressor of the EMT transcription factor Zeb2. Following compromised β-cell identity, the reduction in Pdx1 gene expression causes a decrease in Ovol2 protein, triggering mesenchymal reprogramming of β-cells through the induction of Zeb2. We provided evidence that EMT signalling associated with the upregulation of Zeb2 expression is a molecular feature of islets in T2D subjects. CONCLUSIONS: Our study indicates that m
Izzi-Engbeaya C, Distaso W, Amin A, et al., 2021, Adverse outcomes in COVID-19 and diabetes – a retrospective cohort study from three London Teaching hospitals, BMJ Open Diabetes Research and Care, Vol: 9, Pages: 1-10, ISSN: 2052-4897
INTRODUCTION: Patients with diabetes mellitus admitted to hospital with COVID-19 have poorer outcomes. However, the drivers for this are not fully elucidated. We performed detailed characterisation of COVID-19 patients to determine clinical and biochemical factors that may be the drivers of poorer outcomes. RESEARCH DESIGN AND METHODS: Retrospective cohort study of 889 consecutive inpatients diagnosed with COVID-19 between 9th March 2020 and 22nd April 2020 in a large London NHS Trust. Unbiased multivariate logistic regression analysis was performed to determine variables that were independently and significantly associated with increased risk of death and/or ICU admission within 30 days of COVID-19 diagnosis. RESULTS: 62% of patients in our cohort were of non-White ethnic backgrounds and the diabetes prevalence was 38%. 323 (36%) patients met the primary outcome of death/admission to the intensive care unit (ICU) within 30 days of COVID-19 diagnosis. Male gender, lower platelet count, advancing age and higher Clinical Frailty Scale (CFS) score (but not diabetes) independently predicted poor outcomes on multivariate analysis. Antiplatelet medication was associated with a lower risk of death/ICU admission. Factors that were significantly and independently associated with poorer outcomes in patients with diabetes were co-existing ischaemic heart disease, increasing age and lower platelet count. CONCLUSIONS: In this large study of a diverse patient population, comorbidity (i.e. diabetes with ischaemic heart disease; increasing CFS score in older patients) were major determinants of poor outcomes with COVID-19. Antiplatelet medication should be evaluated in randomised clinical trials amongst high-risk patient groups.
Carrat GR, Haythorne E, Tomas A, et al., 2020, The type 2 diabetes gene product STARD10 is a phosphoinositide-binding protein that controls insulin secretory granule biogenesis, Molecular Metabolism, Vol: 40, ISSN: 2212-8778
OBJECTIVE: Risk alleles for type 2 diabetes at the STARD10 locus are associated with lowered STARD10 expression in the β-cell, impaired glucose-induced insulin secretion, and decreased circulating proinsulin:insulin ratios. Although likely to serve as a mediator of intracellular lipid transfer, the identity of the transported lipids and thus the pathways through which STARD10 regulates β-cell function are not understood. The aim of this study was to identify the lipids transported and affected by STARD10 in the β-cell and the role of the protein in controlling proinsulin processing and insulin granule biogenesis and maturation. METHODS: We used isolated islets from mice deleted selectively in the β-cell for Stard10 (βStard10KO) and performed electron microscopy, pulse-chase, RNA sequencing, and lipidomic analyses. Proteomic analysis of STARD10 binding partners was executed in the INS1 (832/13) cell line. X-ray crystallography followed by molecular docking and lipid overlay assay was performed on purified STARD10 protein. RESULTS: βStard10KO islets had a sharply altered dense core granule appearance, with a dramatic increase in the number of "rod-like" dense cores. Correspondingly, basal secretion of proinsulin was increased versus wild-type islets. The solution of the crystal structure of STARD10 to 2.3 Å resolution revealed a binding pocket capable of accommodating polyphosphoinositides, and STARD10 was shown to bind to inositides phosphorylated at the 3' position. Lipidomic analysis of âStard10KO islets demonstrated changes in phosphatidylinositol levels, and the inositol lipid kinase PIP4K2C was identified as a STARD10 binding partner. Also consistent with roles for STARD10 in phosphoinositide signalling, the phosphoinositide-binding proteins Pirt and Synaptotagmin 1 were amongst the differentially expressed genes in βStard10KO islets. CONCLUSION: Our data indicate that STARD10 binds to, and may transp
Suba K, Patel YS, Alonso AM, et al., 2020, Chronic Administration of a Long-Acting Glucagon Analogue Results in Enhanced Insulin Secretory Activity in a Directly-Observed Murine Model, 80th Scientific Sessions of the American-Diabetes-Association (ADA), Publisher: AMER DIABETES ASSOC, ISSN: 0012-1797
Koutsouri A, Poli F, Alfieri E, et al., 2020, Balancing Cryptoassets and Gold: A Weighted-Risk-Contribution Index for the Alternative Asset Space, 1st International Conference on Mathematical Research for Blockchain Economy, Publisher: Springer Verlag, Pages: 217-232, ISSN: 0302-9743
Bitcoin is foremost amongst the emerging asset class knownas cryptoassets. Two noteworthy characteristics of the returns of non-stablecoin cryptoassets are their high volatility, which brings with it ahigh level of risk, and their high intraclass correlation, which limits thebenefits that can be had by diversifying across multiple cryptoassets. Yetcryptoassets exhibit no correlation with gold, a highly-liquid yet scarceasset which has proved to function as a safe haven during crises affectingtraditional financial systems. As exemplified by Shannon’s Demon, a lackof correlation between assets opens the door to principled risk controlthrough so-called volatility harvesting involving periodic rebalancing.In this paper we propose an index which combines a basket of five cryp-toassets with an investment in gold in a way that aims to improve therisk profile of the resulting portfolio while preserving its independencefrom mainstream financial asset classes such as stocks, bonds and fiatcurrencies. We generalise the theory of Equal Risk Contribution to allowfor weighting according to a desired level of contribution to volatility. Wefind a crypto–gold weighting based on Weighted Risk Contribution to behistorically more effective in terms of Sharpe Ratio than several alterna-tive asset allocation strategies including Shannon’s Demon. Within thecrypto-basket, whose constituents are selected and rebalanced monthly,we find an Equal Weighting scheme to be more effective in terms of thesame metric than a market capitalisation weighting.
Corradi V, Distaso W, Fernandes M, 2019, Testing for jump spillovers without testing for jumps, Journal of the American Statistical Association, Vol: 115, Pages: 1214-1226, ISSN: 0162-1459
This paper develops statistical tools for testing conditional independence among the jump components ofthe daily quadratic variation, which we estimate using intraday data. To avoid sequential bias distortion, wedo not pretest for the presence of jumps. If the null is true, our test statistic based on daily integrated jumpsweakly converges to a Gaussian random variable if both assets have jumps. If instead at least one assethas no jumps, then the statistic approaches zero in probability. We show how to compute asymptoticallyvalid bootstrap-based critical values that result in a consistent test with asymptotic size equal to or smallerthan the nominal size. Empirically, we study jump linkages between US futures and equity index markets.We find not only strong evidence of jump cross-excitation between the SPDR exchange-traded fund andE-mini futures on the S&P 500 index, but also that integrated jumps in the E-mini futures during theovernight period carry relevant information.
Salem V, Delgadillo Silva L, Suba K, et al., 2019, Leader β-cells coordinate Ca2+ dynamics across pancreatic islets in vivo, Nature Metabolism, Vol: 1, Pages: 615-629, ISSN: 2522-5812
Pancreatic β-cells form highly connected networks within isolated islets. Whether this behaviour pertains to the situation in vivo, after innervation and during continuous perfusion with blood, is unclear. In the present study, we used the recombinant Ca2+ sensor GCaMP6 to assess glucose-regulated connectivity in living zebrafish Danio rerio, and in murine or human islets transplanted into the anterior eye chamber. In each setting, Ca2+ waves emanated from temporally defined leader β-cells, and three-dimensional connectivity across the islet increased with glucose stimulation. Photoablation of zebrafish leader cells disrupted pan-islet signalling, identifying these as likely pacemakers. Correspondingly, in engrafted mouse islets, connectivity was sustained during prolonged glucose exposure, and super-connected ‘hub’ cells were identified. Granger causality analysis revealed a controlling role for temporally defined leaders, and transcriptomic analyses revealed a discrete hub cell fingerprint. We thus define a population of regulatory β-cells within coordinated islet networks in vivo. This population may drive Ca2+ dynamics and pulsatile insulin secretion.
Salem V, Delgadillo L, Suba K, et al., 2019, 3-dimensional pancreatic beta cell Ca2+ dynamics in vivo: Hub cells dictate connectivity and glucose responsivity, Publisher: WILEY, Pages: 22-22, ISSN: 0742-3071
Abadir KM, Distaso W, Žikeš F, 2014, Design-free estimation of variance matrices, Journal of Econometrics, Vol: 181, Pages: 165-180, ISSN: 1872-6895
This paper introduces a new method for estimating variance matrices. Starting from the orthogonal decomposition of the sample variance matrix, we exploit the fact that orthogonal matrices are never ill-conditioned and therefore focus on improving the estimation of the eigenvalues. We estimate the eigenvectors from just a fraction of the data, then use them to transform the data into approximately orthogonal series that deliver a well-conditioned estimator (by construction), even when there are fewer observations than dimensions. We also show that our estimator has lower error norms than the traditional one. Our estimator is design-free: we make no assumptions on the distribution of the random sample or on any parametric structure the variance matrix may have. Simulations confirm our theoretical results and they also show that our simple estimator does very well in comparison with other existing methods.
Abadir KM, Distaso W, Giraitis L, et al., 2014, Asymptotic normality for weighted sums of linear processes, Econometric Theory, Vol: 30, Pages: 252-284, ISSN: 0266-4666
We establish asymptotic normality of weighted sums of linear processes with general triangular array weights and when the innovations in the linear process are martingale differences. The results are obtained under minimal conditions on the weights and innovations. We also obtain weak convergence of weighted partial sum processes. The results are applicable to linear processes that have short or long memory or exhibit seasonal long memory behavior. In particular, they are applicable to GARCH and ARCH(∞) models and to their squares. They are also useful in deriving asymptotic normality of kernel-type estimators of a nonparametric regression function with short or long memory moving average errors.
Corradi V, Distaso W, Mele A, 2013, Macroeconomic determinants of stock volatility and volatility premiums, JOURNAL OF MONETARY ECONOMICS, Vol: 60, Pages: 203-220, ISSN: 0304-3932
Corradi V, Distaso W, Fernandes M, 2012, International market links and volatility transmission, JOURNAL OF ECONOMETRICS, Vol: 170, Pages: 117-141, ISSN: 0304-4076
Corradi V, Distaso W, 2011, Multiple Forecast Model Evaluation, The Oxford handbook of economic forecasting, Editors: Clements, Hendry, Publisher: Oxford Univ Pr, Pages: 391-413, ISBN: 9780195398649
Abadir KM, Distaso W, Giraitis L, 2011, An I(<i>d</i>) Model with Trend and Cycles
Abadir KM, Distaso W, Giraitis L, 2011, An I(d) model with trend and cycles, Journal of Econometrics, Vol: 163, Pages: 186-199
Corradi V, Distaso W, Swanson NR, 2011, Predictive Inference for Integrated Volatility, Journal of the American Statistical Association, Vol: 106, Pages: 1496-1512
Abadir KM, Distaso W, Giraitis L, 2010, An I(d) Model with Trend and Cycles
This paper deals with models allowing for trending processes and cyclical component with error processes that are possibly nonstationary, nonlinear, and non-Gaussian. Asymptotic confidence intervals for the trend, cyclical component, and memory parameters are obtained. The confidence intervals are applicable for a wide class of processes, exhibit good coverage accuracy, and are easy to implement.
Distaso W, Lupi P, Manenti FM, 2009, Static and Dynamic Efficiency in the European Telecommunications Market: The Role of Regulation on the Incentives to Invest and the Ladder of Investment, Handbook of Research on Telecommunications Planning and Management for Business, Editors: Lee, Publisher: Information Science Reference, Pages: 1-14, ISBN: 9781605661940
Awartani B, Corradi V, Distaso W, 2009, Assessing Market Microstructure Effects via Realized Volatility Measures with an Application to the Dow Jones Industrial Average Stocks, JOURNAL OF BUSINESS & ECONOMIC STATISTICS, Vol: 27, Pages: 251-265, ISSN: 0735-0015
Abadir KM, Distaso W, Giraitis L, 2009, Two estimators of the long-run variance: beyond short memory, Journal of Econometrics, Vol: 150, Pages: 56-70
Corradi V, Mele A, Distaso W, 2008, Macroeconomic Determinants of Stock Market Returns, Volatility and Volatility Risk-Premia
This paper introduces a no-arbitrage framework to assess how macroeconomic factors help explain the risk-premium agents require to bear the risk of .uctuations in stock market volatility. We develop a model in which return volatility and volatility risk-premia are stochastic and derive no-arbitrage conditions linking volatility to macroeconomic factors. We estimate the model using data related to variance swaps, which are contracts with payo¤s indexed to nonparametric measures of realized volatility. We .nd that volatility risk-premia are strongly countercyclical, even more so than standard measures of return volatility.
Distaso W, 2008, Testing for unit root processes in random coefficient autoregressive models, Journal of Econometrics, Vol: 142, Pages: 581-609
This paper proposes new tests for simple unit root and unit root with a possibly nonzero drift processes, in the context of a random coefficient autoregressive model. The asymptotic distributions of the tests are derived, and their properties are investigated through a Monte Carlo experiment. The tests have good power properties, and in many cases they perform better than the competing univariate tests available in the literature, despite testing for a multiple joint hypothesis. In particular, for moderate to large sample sizes, very small values of the variance of the random coefficient variable are needed in order for the tests to reach some power against roots very close to unity. Finally, the proposed tests are applied to the US GDP series.
Walter Distaso, 2007, Testing for a random walk in RandomCoefficient AutoRegressive models., Journal of Econometrics
Abadir KM, Distaso W, Giraitis L, 2007, Nonstationarity-extended local Whittle estimation, Journal of Econometrics, Vol: 141, Pages: 1353-1384
Abadir K M, W Distaso, 2007, Testing joint hypotheses when one of the alternatives is one-sided, Journal of Econometrics, Vol: 140, Pages: 695-718
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