What is the value of value-at-risk after all?: A conditional approach using quantile regressions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations

This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

Learning about Risk and Return: A Simple Model of Bubbles and Crashes

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Construction and analysis of a new conditional ferritin H knockout mouse strain/

Résumé Le fer joue un rôle important dans la plupart des fonctions biologiques mais sa présence excessive provoque la production de molécules réactives d'oxygène (ROS) qui peuvent contribuer à diverses maladies. La protéine de stockage du fer, la ferritine H, capte l'excès en fer et le stocke sous forme non-toxique, ce qui empêche des dommages potentiels. La délétion de la ferritine H dans des souris knock-out a été essayée antérieurement, mais ces souris mouraient au stade précoce du développement embryonnaire. Pour étudier l'importance du fer, et en particulier son stockage dans la ferritine, et pour pouvoir mieux comprendre les fonctions de la ferritine H, nous avons créé un modèle de souris knock-out conditionnelles de la ferritine H, selon le système classique de Cre-LoxP. Le premier exon et la région du promoteur du gène de la ferritine H ont été entourés de sites loxP. La mortalité embryonnaire provoquée par la délétion constitutive du gène de la ferritine H a été confirmée en croisant nos souris avec des souris exprimant nestin-Cre1. En croisant nos souris avec des souris transgéniques Mx-Cre, nous avons observé que l'induction de Cre par injection de polyI-polyC provoque la délétion presque complète de la ferritine H dans le foie (> 99%) et la rate (> 88%). Ces tissus ont également perdu une grande partie de leur réserve de fer. Cette observation apporte pour la première fois la preuve in vivo que la ferritine H est indispensable pour le stockage du fer, que les fonctions de la ferritine H et de la ferritine L ne sont pas équivalentes, et que la ferritine L ne peut pas assumer seule la fonction de stockage du fer. Dans le foie des souris knock-out, l'expression de l'ARN messager de l'hepcidine a été induite après 10 jours. En même temps, l'expression de l'ARN messager des gènes codant pour des protéines de l'absorption de fer (DMT1, ferroportin, Dcytb1 et hephaestin) a été réprimée mais dans le duodénum seulement. L'expression d'hepcidine est inversément corrélée avec celle des gènes liés à l'absorption de fer. Cette observation corrobore des études antérieures. Mais, en plus, elle montre également que cette répression se produit seulement dans l'intestin. Nous pouvons ainsi tirer la conclusion suivante : ou bien l'hepcidine a un récepteur spécifique dans le duodénum ou bien les gènes liés à l'absorption de fer dans le duodénum ont un facteur spécifique de transcription sensible à l'hepcidine. Aucune répression de DMT1 et de ferroportin n'a été observée dans les macrophages de la rate après l'induction d'hepcidine. La délétion de ferritine H a entraîné une augmentation du taux de mortalité des cellules hépatiques, ainsi que des altérations dans l'architecture normale du tissu de la rate. Vu par l'immunohistologie, le nombre de lymphocytes B et T était réduit dans la rate, tendant à démontrer que la ferritine H et l'homéostase du fer jouent un rôle dans l'immunité. En conclusion, le modèle de souris knock-out conditionnelles de la ferritine H nous fournit un outil précieux pour l'étude in vivo du rôle joué par la ferritine dans l'homéostase du fer, dans les dommages créés par les ROS, ainsi que dans l'apoptose et l'immunité. Summary Iron plays an important role in most biological functions. However, excess of iron results in production of reactive oxygen species (ROS) which could substantially contribute to pathology of various diseases. Ferritin H scavenges excess of iron and stores it in non-toxic form and potentially prevents the damage. Fenitin H targeting in mice has been attempted before, however, straight knockout was lethal in early embryonic stage. To study the role of iron and its storage protein ferritin and to further elucidate ferritin H functions, we aimed at creating a conditional ferritin H knockout mouse model by classical Cre-LoxP system. First exon along with promoter region of the ferritin H gene was foxed. Embryonic lethality of the constitutive ferritin H deletion was confirmed by crossing the foxed mice with mice expressing nestin Cre-1 as transgene. Almost complete deletion was observed in liver (> 99%) and spleen (>88%) upon induction of Cre by injecting polyI-polyC in Fth Lox/Lox; MxCre mice. These tissues also lost substantial fraction of their iron stores. This provides first in vivo evidence that ferritin H is required for iron storage, ferritin H and L functions are not redundant and that ferritin L cannot perform iron storage function alone. Hepcidin mRNA expression was induced after 10 days in the livers of deleted mice and, simultaneously, mRNA expression of iron absorption related genes (DMT 1, ferroportin, Dcytb1 and hephaestin) was repressed in duodenum only. Hepcidin expression is inversely correlated with that of duodenal iron absorption related genes. This is in agreement with previous studies. However, we also show that this repression happens only in intestine. This leads to the conclusion that either hepcidin has a specific receptor in duodenum or the iron absorption related genes have duodenum specific transcription factor that is responsive to hepcidin. No repression of DMT1 and ferroportin was observed in spleen macrophages upon hepcidin induction. Ferritin H deletion showed increased cell death in liver and disruption of normal architecture of spleen. B lymphocytes were reduced in spleen on immunohistology which point towards a role of ferritin H and iron homeostasis in immunity. In conclusion, ferritin H conditional knockout mouse model provides us with an invaluable tool to study the in vivo role of ferritin H in iron homeostasis, ROS mediated damage, apoptosis and immunity.

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

Keeping up with the Joneses: An international asset pricing model

We derive an international asset pricing model that assumes local investorshave preferences of the type "keeping up with the Joneses." In aninternational setting investors compare their current wealth with that oftheir peers who live in the same country. In the process of inferring thecountry's average wealth, investors incorporate information from the domesticmarket portfolio. In equilibrium, this gives rise to a multifactor CAPMwhere, together with the world market price of risk, there existscountry-speciffic prices of risk associated with deviations from thecountry's average wealth level. The model performs signifficantly better, interms of explaining cross-section of returns, than the international CAPM.Moreover, the results are robust, both for conditional and unconditionaltests, to the inclusion of currency risk, macroeconomic sources of risk andthe Fama and French HML factor.

Frailty and risk for heart failure in older adults: The health, aging, and body composition study.

OBJECTIVE: The aim of this study was to assess the association between frailty and risk for heart failure (HF) in older adults. BACKGROUND: Frailty is common in the elderly and is associated with adverse health outcomes. Impact of frailty on HF risk is not known. METHODS: We assessed the association between frailty, using the Health ABC Short Physical Performance Battery (HABC Battery) and the Gill index, and incident HF in 2825 participants aged 70 to 79 years. RESULTS: Mean age of participants was 74 ± 3 years; 48% were men and 59% were white. During a median follow up of 11.4 (7.1-11.7) years, 466 participants developed HF. Compared to non-frail participants, moderate (HR 1.36, 95% CI 1.08-1.71) and severe frailty (HR 1.88, 95% CI 1.02-3.47) by Gill index was associated with a higher risk for HF. HABC Battery score was linearly associated with HF risk after adjusting for the Health ABC HF Model (HR 1.24, 95% CI 1.13-1.36 per SD decrease in score) and remained significant when controlled for death as a competing risk (HR 1.30; 95% CI 1.00-1.55). Results were comparable across age, sex, and race, and in sub-groups based on diabetes mellitus or cardiovascular disease at baseline. Addition of HABC Battery scores to the Health ABC HF Risk Model improved discrimination (change in C-index, 0.014; 95% CI 0.018-0.010) and appropriately reclassified 13.4% (net-reclassification-improvement 0.073, 95% CI 0.021-0.125; P = .006) of participants (8.3% who developed HF and 5.1% who did not). CONCLUSIONS: Frailty is independently associated with risk of HF in older adults.

Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation

Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.

Official Positions for FRAX® clinical regarding falls and frailty: can falls and frailty be used in FRAX®? From Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

Risk factors for fracture can be purely skeletal, e.g., bone mass, microarchitecture or geometry, or a combination of bone and falls risk related factors such as age and functional status. The remit of this Task Force was to review the evidence and consider if falls should be incorporated into the FRAX® model or, alternatively, to provide guidance to assist clinicians in clinical decision-making for patients with a falls history. It is clear that falls are a risk factor for fracture. Fracture probability may be underestimated by FRAX® in individuals with a history of frequent falls. The substantial evidence that various interventions are effective in reducing falls risk was reviewed. Targeting falls risk reduction strategies towards frail older people at high risk for indoor falls is appropriate. This Task Force believes that further fracture reduction requires measures to reduce falls risk in addition to bone directed therapy. Clinicians should recognize that patients with frequent falls are at higher fracture risk than currently estimated by FRAX® and include this in decision-making. However, quantitative adjustment of the FRAX® estimated risk based on falls history is not currently possible. In the long term, incorporation of falls as a risk factor in the FRAX® model would be ideal.

Simulated-annealing-based conditional simulation for the local-scale characterization of heterogeneous aquifers

Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.

Chaotic systems with a null conditional Lyapunov exponent under nonlinear driving.

Control of a chaotic system by homogeneous nonlinear driving, when a conditional Lyapunov exponent is zero, may give rise to special and interesting synchronizationlike behaviors in which the response evolves in perfect correlation with the drive. Among them, there are the amplification of the drive attractor and the shift of it to a different region of phase space. In this paper, these synchronizationlike behaviors are discussed, and demonstrated by computer simulation of the Lorentz model [E. N. Lorenz, J. Atmos. Sci. 20 130 (1963)] and the double scroll [T. Matsumoto, L. O. Chua, and M. Komuro, IEEE Trans. CAS CAS-32, 798 (1985)].

Conditional maximum likelihood timing recovery: estimators and bounds

This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulationthat is systematically applied in the literature for the derivationof non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB)[which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statisticalaccuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained boundis not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRBis obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.

Association between frailty and delirium in older adult patients discharged from hospital.

BACKGROUND: Delirium and frailty - both potentially reversible geriatric syndromes - are seldom studied together, although they often occur jointly in older patients discharged from hospitals. This study aimed to explore the relationship between delirium and frailty in older adults discharged from hospitals. METHODS: Of the 221 patients aged >65 years, who were invited to participate, only 114 gave their consent to participate in this study. Delirium was assessed using the confusion assessment method, in which patients were classified dichotomously as delirious or nondelirious according to its algorithm. Frailty was assessed using the Edmonton Frailty Scale, which classifies patients dichotomously as frail or nonfrail. In addition to the sociodemographic characteristics, covariates such as scores from the Mini-Mental State Examination, Instrumental Activities of Daily Living scale, and Cumulative Illness Rating Scale for Geriatrics and details regarding polymedication were collected. A multidimensional linear regression model was used for analysis. RESULTS: Almost 20% of participants had delirium (n=22), and 76.3% were classified as frail (n=87); 31.5% of the variance in the delirium score was explained by frailty (R (2)=0.315). Age; polymedication; scores of the Confusion Assessment Method (CAM), instrumental activities of daily living, and Cumulative Illness Rating Scale for Geriatrics; and frailty increased the predictability of the variance of delirium by 32% to 64% (R (2)=0.64). CONCLUSION: Frailty is strongly related to delirium in older patients after discharge from the hospital.