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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

The effects of the COVID-19 pandemic on mental health have been profound. Mental health and diabetes self-care are inter-related. We examined whether COVID-19 anxiety, depressive symptoms and health anxiety were associated with domains of diabetes self-management and investigated whether greater COVID-19 anxiety syndrome would independently contribute to suboptimal diabetes self-care.Surveys were sent to people attending diabetes clinics of three London hospitals. Participants completed the Diabetes Self-Management Questionnaire (DSMQ), the COVID-19 Anxiety Syndrome Scale (C-19 ASS), which measures perseveration and avoidant maladaptive coping behaviour, assessed with measures of co-existent depressive symptoms and anxiety, controlling for age, gender and social deprivation. Clinical data, including pre- and post-lockdown HbADepressive symptom scores were high. Both pre-existing health anxiety and depressive symptoms were independently linked to improvable measures of diabetes care, as was lower socio-economic rank. However, avoidant COVID-19 anxiety responses were independently associated with higher diabetes self-care scores. HbADuring the height of lockdown, avoidant coping behaviours characteristic of the COVID-19 anxiety syndrome may in fact work to improve diabetes self-care, at least in the short term. We recommend screening for depressive symptoms and being aware of the significant minority of people with COVID-19 anxiety syndrome who may now find it difficult to re-engage with face-to-face clinic opportunities.

We investigate the determinants of several measures of psychological distress and work and social adjustment, using data from a large survey covering six countries and three continents over the COVID-19 pandemic. Our analysis reveals substantial cross-country heterogeneity and identifies a strong effect of COVID-19 specific measures of distress onto generic ones, but not the other way around. The results confirm the importance of controlling for individual characteristics, which help explain some of the cross-country differences. Finally, they also highlight specific categories of individuals who have recorded extremely high levels of psychological distress.

The paper proposes a new text-based indicator aimed at assessing the impact over time of political debate on economy. Textual data from the plenary verbatim reports of the Italian Parliament are pre-processed and relevant themes, whose temporal evolution allows predicting fluctuations in fundamental macro-economic variables, are estimated via a Correlated Topic Model. Specifically, a Political Debate Index is derived based on a time-varying weighting function of the estimated topic proportions. The capability, in terms of out-of-sample forecasts accuracy, of the proposed approach in improving the predictability of selected economic indicators is evaluated considering different predictors. The reached results seem to support the evidence that qualitative information conveyed by the daily political debate does have an impact on the economic dynamic over time and can be usefully used to improve the economic predictions performance.

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.

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 miR-7-mediated β-cell dedifferentiation induces EMT signalling and a chronic response to tissue injury, which alters the islet microenvironment and predisposes to fibrosis. This research suggests that regulators of EMT signalling may represent novel therapeutic targets for treating β-cell dysfunction and fibrosis in T2D., Molecular Metabolism, 53

Patients with diabetes mellitus admitted to hospital with COVID-19 caused by infection with the novel coronavirus (SARS-CoV-2) have poorer outcomes. However, the drivers for this are not fully elucidated. We performed a retrospective cohort study, including detailed pre-hospital and presenting clinical and biochemical factors of 889 patients diagnosed with COVID-19 in three constituent hospitals of a large London NHS Trust. 62% of patients with severe COVID-19 were of non-White ethnic backgrounds and the prevalence of diabetes was 38%. 323 (36%) patients met the primary outcome of death or admission to the intensive care unit (ICU) within 30 days of diagnosis. Male gender, advancing age and the Clinical Frailty Scale, an established measure of multimorbidity, independently predicted poor outcomes on multivariate analysis. Diabetes did not confer an independent risk for adverse outcomes in COVID-19, although patients with diabetes and ischaemic heart disease were at particular risk. Additional risk factors which significantly and independently associated with poorer outcomes in patients with diabetes were age, male gender and lower platelet count. Antiplatelet medication was associated with a lower risk of death/ICU admission and should be evaluated in randomised clinical trials amongst high risk patient groups.

Aims: GLP-1 (GLP-1R) and glucagon (GCGR) receptor co-agonists are in development to treat type 2 diabetes. The effect of chronic GCGR agonism on weight loss is well-documented, but its direct influence on islet function remains poorly understood. We investigated the effects of a long-acting glucagon analogue G778 on pancreatic islet calcium dynamics. Methods: C57Bl/6 (n=9 per group) mice with diet-induced obesity (DIO) received daily subcutaneous injections of G778 100nmol/kg or saline (and calorie restricted to achieve weight matching) for 40 days. All mice had syngeneic islets with beta-cell specific expression of the calcium fluorophore GCaMP6f implanted in the anterior chamber of the eye, providing a direct, longitudinal readout of beta-cell function in vivo using confocal microscopy. Such islets were tested in vitro to measure the effects of G778 on whole islet calcium dynamics. Another experiment measured the effects of G778 administration on oxygen consumption in a CLAMS system. Results: G778 produced a small but significant rise in energy expenditure (EE) in mice. At 40 days, there was non-significant difference in body weight loss between the saline and G778-treated groups (0.9g ±1.1 vs. 3.4g ±0.7 p=0.07), but a marked improvement in glucose tolerance in mice treated long term with the glucagon analogue (15 min glucose on a 2mg/kg IPGTT 15.9 mmol/L vs. 9.2 mmol/L p Summary: Our data suggest that the glucagon element of a glucagon/GLP-1 analogue contributes to weight-loss partly through an elevation in EE but also has independent effects on insulin secretory function, promoting more robust and sustained beta-cell calcium responses. Disclosure K. Suba: None. Y.S. Patel: None. A. Martin Alonso: None. R. Scott: None. J.S. Minnion: None. I. Leclerc: Consultant; Spouse/Partner; Sun Pharmaceutical Industries Ltd. Research Support; Spouse/Partner; Servier. B. Owen: None. W. Distaso: None. T.M. Tan: None. K. Murphy: None. S. Bloom: None. G.A. Rutter: Consultant; Self; Sun Pharmaceutical Industries Ltd. Research Support; Self; Servier, Sun Pharmaceutical Industries Ltd. V. Salem: None. Funding Diabetes UK (15/0005317)

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 βStard10KO 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 transport, phosphatidylinositides, influencing membrane lipid composition, insulin granule biosynthesis, and insulin processing., Highlights • βStard10KO β-cells show altered granule morphology. • Deletion of Stard10 increased basal secretion of newly synthesised proinsulin. • βStard10KO islets had an altered lipidomics profile, including phosphatidylinositols. • STARD10 bound to phosphoinositides in a lipid overlay assay. • STARD10 structure reveals that its cavity readily accommodates phosphatidylinositols.

Background: Drugs that safely promote weight loss are required to treat the obesity crisis. The gut hormone peptide YY 3-36 (PYY3-36) is secreted post-prandially to suppress appetite via the Y2 receptor (Y2R). However, it is unclear whether PYY3-36 acts directly on the Y2R in the hypothalamic arcuate nucleus (ARC) or the afferent vagus nerve to inhibit food intake. Understanding the pathways by which PYY3-36 mediates its anorectic effects may facilitate the therapeutic targeting of this system. Methods: Y2R knockdown in the ARC (ARC-Y2R-KD) was achieved by stereotactic injection of Cre-expressing adeno-associated virus (AAV-Cre) in Y2R-flox C57Bl/6 mice. Y2R KD in the vagus was achieved by bilateral microinjection of AAV-Cre into the nodose ganglia (NG), where the cell bodies of vagal afferents reside. An alternative germline model of sensory nerve Y2R knockdown was generated using Nav1.8-Cre mice crossed with the Y2R-flox strain (Nav1.8-Y2R-KD). Feeding behaviour over 10 days in metabolic cages and the effects of endogenously released (after oral gavage of a nutrient bolus) or exogenously-administered PYY3-36 were investigated. Results: NG-Y2R-KD animals had 60% reduction in NG Y2R mRNA but remained responsive to cholecystokinin, a positive control of vagal functionality. This is the first example of receptor specific adult vagal deafferentation in mice. The Nav1.8-Y2R-KD model achieved 30% receptor KD. Feeding patterns in the ARC-Y2R-KD and NG-Y2R-KD groups were highly different from their controls, with smaller, faster meals in the KD groups. The anorectic effects (at the next meal) of endogenous PYY3-36 were attenuated in NG-Y2R-KD. Low dose exogenous PYY3-36 at 5 µg/kg significantly reduced 2h post injection food intake (FI) in the control groups (n=8; P=0.045) but this was abrogated in the NG-Y2R-KD group. This pattern was mirrored in the Nav1.8-Y2R-KD model: low dose PYY3-36 significantly reduced FI 1h post-IP compared to vehicle in controls (-0.19±0.05 g; P =0.036; n=8) but not in the Nav1.8-Y2R-KD (-0.004±0.111 g; n=3). Peripherally-administered PYY3-36 at a high dose (30 µg/kg) decreased FI in all groups, including ARC-Y2R-KD. Summary: These results suggest that endogenous PYY3-36 modulates meal patterning. The vagus nerve mediates physiological PYY3-36 signalling but alternative pathways, not exclusively via the ARC, may be more important in mediating its pharmacological effects. This is relevant for the design of more effective weight loss agents.

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.

Many asset pricing theories treat the cross-section of expected returns, volatility and correlations as quantities driven by common factors. We formulate and estimate a model without such factors, but with a continuum of securities that have returns driven by a string. Our arbitrage restrictions require that any asset premium links to the granular exposure of the asset returns to shocks in all other asset returns: an average correlation premium. The model predictions uncover fresh properties of big stocks. Big stocks display a high degree of market connectivity in bad times, but also work as correlation hedges: they contribute to a negative fraction of the average correlation premium, and portfolios that are more exposed to them command a lower premium. The string model performs at least as well as many existing linear factor models.

Aim: Risk alleles for type 2 diabetes (T2D) in the STARD10 locus, impair insulin secretion and are associated with decreased proinsulin:insulin ratios. We have shown that the T2D risk associated with variation at this locus is likely to be mediated through lowered STARD10 expression in the β cell. Here, we investigate the mechanisms by which STARD10 may regulate insulin secretion. Materials and Methods: A 3-dimensional model of STARD10 was constructed from the structure of STARD2, using the modelling tools Chimera and Modeller. Islets were isolated from StarD10fl/fl-Ins1Cre male mice (βStarD10KO). Electron Microscopy (EM) images were obtained from isolated islets after chemical fixation. Total zinc content was measured by inductively coupled plasma mass spectrometry. Pulse-chase analysis of proinsulin processing was performed using 35S-labelled amino acids. RNA-Seq was done on polyadenylated transcripts selected during the preparation of paired-end, directional RNAseq libraries, sequenced on an Illumina HiSeq 4000 machine. Results: Molecular modelling indicated that STARD10 binds either phosphatidylcholine or phosphatidylethanolamine. EM analysis of islets from βStarD10KO mice revealed a markedly altered dense core granule appearance, with a dramatic increase (Fold change = 4.3; p Conclusion: We identify STARD10 as a critical regulator of insulin granule biogenesis and β cell zinc homeostasis. Our data also suggest that increased β cell Zn2+ secretion in risk allele carriers may decrease the clearance of mature insulin to lower plasma proinsulin:insulin ratio. Disclosure G. Carrat: None. E. Haythorne: None. L. Haataja: None. P. Arvan: None. A. Tomas: None. A. Piunti: None. T.J. Pullen: None. E. Georgiadou: None. T. Stylianides: None. V. Salem: None. W. Distaso: None. A. Cakebread: None. D. Hodson: None. A.C. Fung: None. R.B. Sessions: None. F. Alpy: None. A.P. Kong: Advisory Panel; Self; Lilly Diabetes. Research Support; Self; AstraZeneca, Lilly Diabetes. Speaker's Bureau; Self; Abbott. Other Relationship; Self; AstraZeneca, Novartis Pharmaceuticals Corporation, Sanofi. I. Leclerc: None. G.A. Rutter: Consultant; Self; Sun Pharma. Funding Medical Research Council UK; UK Wellcome Trust; Royal Society; Societe Francophone du Diabete

Aim: In-vitro studies reveal a subpopulation of β cells which co-ordinate insulin release from pancreatic islets. This connectivity has not been established in 3 dimensions across the islet or in the living animal. We investigated this in the living zebrafish D. rario or in mouse islets engrafted in the anterior eye chamber (ACE), using the recombinant Ca2+ sensor GCaMP6 under the insulin promoter/C57Bl6, Ins1Cre:GCaM6ff/f. Methods: Whole islet live imaging of D. rario primary islets in situ at an acquisition rate of 0.8Hz, covering 700μm, was achieved using resonant scanner technology with a Leica inverted laser scanning confocal system, using a 25X/N.A. 0.95 water lens. Fully vascularized islets in the murine ACE were imaged under isofluorane anaesthesia on a modified Nikon Ti-E spinning disc confocal microscope (20x 0.75 NA water immersion objective, 3 Hz frame rate). Results: 3-dimensional β cell connectivity (Pearson R statistic) significantly rose to 88% across the zebrafish islet in response to glucose stimulation. Focused ablation of the co-ordinating “hub” (but not follower) β cells significantly attenuated the subsequent response to a glucose challenge. In mouse islets, high circulating glucose levels were also associated with a significant rise in 3D beta cell connectivity from 65 to 86% (n=3; p=0.02). Granger causality analysis on these islets revealed that even on prolonged (>10 minute) glucose stimulation, pan-islet connectivity was sustained and the most highly connected cells were those in the region of the islet from which Ca2+ waves emanated. Binarized signal analysis (n=6) separately confirmed the presence of a highly-connected β cell subpopulation (8.7 ± 3.6% of cells). Conclusions: These studies evidence beta cell “hubs” which are responsible for the initiation and sustained coordination of the Ca2+ response to glucose across fish and mouse islets in vivo. Disclosure V. Salem: None. L.F. Delgadillo Silva: None. K. Suba: None. A. Martin Alonso: None. W. Kim: None. V. Kalogianni: None. N. Akhtar: None. N. Mousavy Gharavy: None. E. Georgiadou: None. I. Leclerc: None. L. Briant: None. D. Hodson: None. W. Distaso: None. N.N. Ninov: None. G.A. Rutter: Consultant; Self; Sun Pharma. Funding Diabetes UK; UK Wellcome Trust

International audience; Bitcoin is foremost amongst the emerging asset class known as cryptoassets. Two noteworthy characteristics of the returns of non-stablecoin cryptoassets are their high volatility, which brings with it a high level of risk, and their high intraclass correlation, which limits the benefits that can be had by diversifying across multiple cryptoassets. Yet cryptoassets exhibit no correlation with gold, a highly-liquid yet scarce asset which has proved to function as a safe haven during crises affecting traditional financial systems. As exemplified by Shannon's Demon, a lack of correlation between assets opens the door to principled risk control through 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 the risk profile of the resulting portfolio while preserving its independence from mainstream financial asset classes such as stocks, bonds and fiat currencies. We generalise the theory of Equal Risk Contribution to allow for weighting according to a desired level of contribution to volatility. We find a crypto-gold weighting based on Weighted Risk Contribution to be historically more effective in terms of Sharpe Ratio than several alternative asset allocation strategies including Shannon's Demon. Within the crypto-basket, whose constituents are selected and rebalanced monthly, we find an Equal Weighting scheme to be more effective in terms of the same metric than a market capitalisation weighting.

In this paper, we investigate the association between international banks' operational losses and macro-financial variables, Governance Indicators and banks' specific covariates. We do so in a panel data setting, which includes both censoring (since losses below a given threshold are not reported) and attrition (since banks may not operate in a given Country over some fraction of the data temporal dimension), and allows for Country and bank specific fixed effects. We develop an asymptotic theory to estimate parameters of interest and their standard errors consistently, allowing us to conduct valid inference. The results of our analysis uncover interesting links between macroeconomic and financial variables, Governance Indicators and banks' losses, whereas banks' specific variables seem to play a less prominent role.

This article develops statistical tools for testing conditional independence among the jump components of the daily quadratic variation, which we estimate using intraday data. To avoid sequential bias distortion, we do not pretest for the presence of jumps. If the null is true, our test statistic based on daily integrated jumps weakly converges to a Gaussian random variable if both assets have jumps. If instead at least one asset has no jumps, then the statistic approaches zero in probability. We show how to compute asymptotically valid bootstrap-based critical values that result in a consistent test with asymptotic size equal to or smaller than 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 and E-mini futures on the S&P 500 index, but also that integrated jumps in the E-mini futures during the overnight period carry relevant information. Supplementary materials for this article are available as an online supplement.

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., info:eu-repo/semantics/published

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 Ca

We investigate how individual equity prices react to stock specific expected jump components. We find that a portfolio buying stocks with negative expected jump component and selling stocks with positive expected jump component earns significant returns, equal to 51 basis points per month. The returns of the spread portfolio cannot be explained by traditional risk factors and are robust to different model specifications. Furthermore, the associated risk premium is very close to the average monthly return, and remains significant after controlling for portfolio characteristics.

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.

This paper deals with the estimation of the long-run variance of a stationary sequence. We extend the usual Bartlett-kernel heteroskedasticity and autocorrelation consistent (HAC) estimator to deal with long memory and antipersistence. We then derive asymptotic expansions for this estimator and the memory and autocorrelation consistent (MAC) estimator introduced by Robinson [Robinson, P. M., 2005. Robust covariance matrix estimation: HAC estimates with long memory/antipersistence correction. Econometric Theory 21, 171–180]. We offer a theoretical explanation for the sensitivity of HAC to the bandwidth choice, a feature which has been observed in the special case of short memory. Using these analytical results, we determine the MSE-optimal bandwidth rates for each estimator. We analyze by simulations the finite-sample performance of HAC and MAC estimators, and the coverage probabilities for the studentized sample mean, giving practical recommendations for the choice of bandwidths.

Transaction prices of financial assets are contaminated by market microstructure effects. This is particularly relevant when estimating volatility using high frequency data. In this article, we assess statistically the effect of microstructure noise on volatility estimators, and test the hypothesis that its variance is independent of the sampling frequency. We provide evidence based on the Dow Jones Industrial Average stocks. We find that noise has a statistically significant effect on volatility estimators at frequencies of 2–3 min or higher. The independently and identically distributed specification with constant variance seems to be a plausible model for microstructure noise, except for ultra high frequencies.

This paper proposes a procedure to test for the correct specification of the functional form of the volatility process within the class of eigenfunction stochastic volatility models. The procedure is based on the comparison of the moments of realized volatility measures with the corresponding ones of integrated volatility implied by the model under the null hypothesis. We first provide primitive conditions on the measu rement error associated with the realized measure, which allow to construct asymptotically valid specification tests. Then we establish regularity conditions under which the considered realized measures, namely, realized volatility, bipower variation, and modified subsampled realized volatility, satisfy the given primitive assumptions. Finally, we provide an empirical illustration based on thr ee stocks from the Dow Jones Industrial Average. © 2006 The Review of Economic Studies Limited.

The paper introduces and develops the concept of Visual Econometrics - an innovative way of doing econometrics by manipulating visual information on a computer screen without the need to write code or issuing commands. This new approach has been made possible by the development, in recent years, of ViSta, a powerful and easy to use graphically oriented interactive computing environment for regression analysis. The paper argues that the visual approach perfectly complements the algebraic and numerical perspectives of doing econometrics. We illustrate with a few examples relevant to economics and econometrics how ViSta can be useful not only for general data analysis but also for the teaching and practicing of econometrics.

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.

How does stock market volatility relate to the business cycle? We develop, and estimate, a no-arbitrage model, and find that (i) the level and fluctuations of stock volatility are largely explained by business cycle factors and (ii) some unobserved factor contributes to nearly 20% to the overall variation in volatility, although not to its ups and downs. Instead, this “volatility of volatility” relates to the business cycle. Finally, volatility risk-premiums are strongly countercyclical, even more than stock volatility, and partially explain the large swings of the VIX index during the 2007–2009 subprime crisis, which our model captures in out-of-sample experiments.

We test the hypothesis that the impartiality of referees in football matches suffers from two types of biases. First, the unconscious bias, a result of the pressure exerted by suppoters benefiting the teams playing at home. Second, the conscious bias, the outcome of a voluntary action taken by the referee to determine of influence match results. Using data from the Italian 2004/05 Serie A season, we show that our hypothesis is empirically supported; our result sh elp also to shed light on different aspects of the Calciopoli corruption scandal that exploded in Italy in the summer of 2006.

This paper proposes a framework to gauge the degree of volatility transmission among international stock markets by deriving tests for conditional independence among daily volatility measures. We suppose that asset prices follow a multivariate jump-diffusion process, and make no parametric assumption on the functional form of the drift, diffusive, and jump components. To check for conditional independence of asset A's daily volatility given asset B's daily volatility, we consider the integrated (relative) squared difference between two nonparametric conditional density estimates. The first estimate considers only information concerning asset A's daily volatility, whereas the second estimate also includes information about asset B's daily volatility. To proxy for the unobservable daily volatility, we employ model-free realized measures, allowing for both microstructure noise and jumps. We establish the asymptotic normality of the test statistic based on realized measures as well as the first-order validity of its bootstrap analog.In addition, we investigate volatility spillovers between the stock markets in China, Japan, UK and US from January 2000 to December 2005. We find significant volatility spillovers across all markets, especially if we control for jumps and/or market microstructure effects. Apart from the expected bidirectional link between the UK and the US, we uncover significant Japan and China effects on the US stock market volatility. Their impact is particularly apparent if we further conditioning on the realized measure of the FTSE 100 index to control for the presence of global shocks.

This paper aims to assess dynamic tail risk exposure in the hedge fund sector using daily data. We use a copula function to model both lower and upper tail dependence between hedge-fund and broad-market returns as a function of market uncertainty. We proxy the latter by means of a single index that combines the options-implied market volatility, the volatility risk premium, and the swap and term spreads. We find substantial time-variation in both lower- and upper-tail dependence, even for hedge fund styles that exhibit little unconditional tail dependence. In particular, dependence between hedge fund and equity market returns decreases in both tails significantly with market uncertainty. There are only a few styles that feature neither unconditional nor conditional tail dependence, e.g., convertible arbitrage and equity market neutral. We also fail to observe any tail dependence with bond and currency markets, though we find strong evidence that the lower-tail risk exposure of macro hedge funds to commodity markets increases with liquidity risk. Finally, further analysis shows mixed evidence on how much hedge funds contribute to systemic risk.

This paper introduces a no-arbitrage framework to assess how macroeconomic factors help explain the risk-premium agents require to bear the risk of fluctuations in stock market volatility. We develop a model in which return volatility is 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 payoffs indexed to nonparametric measures of realized volatility. We find that volatility risk-premia are strongly countercyclical and that in turn, they are of substantial help in predicting future economic activity.

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned quantities. The kernel functions used in our analysis are based on different realized volatility measures, which are constructed using the ex post variation of asset prices. A set of sufficient conditions under which the estimators are asymptotically equivalent to their unfeasible counterparts, based on the unobservable volatility process, is provided. Asymptotic normality is also established. The efficacy of the estimators is examined via Monte Carlo experimentation, and an empirical illustration based upon data from the New York Stock Exchange is provided.

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, especially when the data are generated from fat-tailed densities.

This paper proposes methods for testing the multivariate mixture of normals hypothesis. It uses multivariate measures of integrated variance to standardize (in a matrix sense) daily returns. Because replacing the unobserved integrated covariance by its estimator introduces a finite-sample distortion, a correction is implemented to alleviate this problem. In the empirical application to foreign exchange rates, the mixture-of-normals hypothesis is soundly rejected. The rejection appears to be due to the deviations of the marginals from standard normality rather than the dependence structure being inconsistent with a normal copula. To shed more light on the joint distribution of the Euro, Dollar and Yen exchange rates, a five-equation parametric model is estimated for the bivariate standardized returns, realized volatilities and realized correlation, allowing for time-varying volatility of the realized measures as well as non-normal innovations. The model fits data well and uncovers nonlinear dependencies between return and volatility innovations.

This article focuses on recent developments in the forecasting literature on how to simultaneously control both the overall error rate and the contribution of irrelevant models. As a novel contribution, it derives a general class of superior predictive ability tests, which controls for family-wise error rate (FWER) and the contribution of irrelevant models. The article is organized as follows. Section 2 defines the setup. Section 3 reviews the approaches that control for the conservative FWER. Section 4 considers a general class of tests characterized by multiple joint inequalities. Section 5 presents results allowing for control of the less conservative false discovery rate. Section 6 considers the model confidence set approach and offers a simple alternative that reduces the influence of irrelevant models in the initial set. Section 7 briefly reviews the empirical evidence, while Section 8 concludes.

In this chapter the authors provide evidence of the effectiveness of European National Regulatory Authorities in applying the basic principles of the ladder of investment. The analysis discusses and compares the regulatory approach adopted in 12 European Countries from January 2005 to July 2007. Results are not easy to interpret, given the peculiarities of the different national markets. Nevertheless, they can conclude that the policies adopted by National Regulatory Authorities are broadly consistent with the ladder of investment theory.

This paper introduces a no-arbitrage framework to assess how macroeconomic factors help explain the risk-premium agents require to bear the risk of fluctuations in stock market volatil- ity. 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.

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.