A Comprehensive Portfolio Construction Under Stochastic Environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: a) increase the efficiency of the portfolio optimization process, b) implement large-scale optimizations, and c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH).

Multivariate Appoximations to Portfolio Return Distribution

This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram-Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation coefficients. The procedure involves consistent estimates even under density misspecification and solves the so-called ‘curse of dimensionality’ of multivariate modelling. Furthermore, the use of a MGC distribution represents a flexible and general approximation to the true distribution of portfolio returns and accounts for all its empirical regularities. An application of such procedure is performed for a portfolio composed of three European indices as an illustration. The MM estimation of the MGC (MGC-MM) is compared with the traditional maximum likelihood of both the MGC and multivariate Student’s t (benchmark) densities. A simulation on Value-at-Risk (VaR) performance for an equally weighted portfolio at 1% and 5% confidence indicates that the MGC-MM method provides reasonable approximations to the true empirical VaR. Therefore, the procedure seems to be a useful tool for risk managers and practitioners.

Multicenter randomized phase II clinical trial comparing neoadjuvant oxaliplatin, capecitabine, and preoperative radiotherapy with or without cetuximab followed by total mesorectal excision in patients with high-risk rectal cancer (EXPERT-C).

PURPOSE: To evaluate the addition of cetuximab to neoadjuvant chemotherapy before chemoradiotherapy in high-risk rectal cancer. PATIENTS AND METHODS: Patients with operable magnetic resonance imaging-defined high-risk rectal cancer received four cycles of capecitabine/oxaliplatin (CAPOX) followed by capecitabine chemoradiotherapy, surgery, and adjuvant CAPOX (four cycles) or the same regimen plus weekly cetuximab (CAPOX+C). The primary end point was complete response (CR; pathologic CR or, in patients not undergoing surgery, radiologic CR) in patients with KRAS/BRAF wild-type tumors. Secondary end points were radiologic response (RR), progression-free survival (PFS), overall survival (OS), and safety in the wild-type and overall populations and a molecular biomarker analysis. RESULTS: One hundred sixty-five eligible patients were randomly assigned. Ninety (60%) of 149 assessable tumors were KRAS or BRAF wild type (CAPOX, n = 44; CAPOX+C, n = 46), and in these patients, the addition of cetuximab did not improve the primary end point of CR (9% v 11%, respectively; P = 1.0; odds ratio, 1.22) or PFS (hazard ratio [HR], 0.65; P = .363). Cetuximab significantly improved RR (CAPOX v CAPOX+C: after chemotherapy, 51% v 71%, respectively; P = .038; after chemoradiation, 75% v 93%, respectively; P = .028) and OS (HR, 0.27; P = .034). Skin toxicity and diarrhea were more frequent in the CAPOX+C arm. CONCLUSION: Cetuximab led to a significant increase in RR and OS in patients with KRAS/BRAF wild-type rectal cancer, but the primary end point of improved CR was not met.

Prevalence and risk of Down syndrome in monozygotic and dizygotic multiple pregnancies in Europe: implications for prenatal screening

OBJECTIVE: To determine risk of Down syndrome (DS) in multiple relative to singleton pregnancies, and compare prenatal diagnosis rates and pregnancy outcome.

DESIGN: Population-based prevalence study based on EUROCAT congenital anomaly registries.

SETTING: Eight European countries.

POPULATION: 14.8 million births 1990-2009; 2.89% multiple births.

METHODS: DS cases included livebirths, fetal deaths from 20 weeks, and terminations of pregnancy for fetal anomaly (TOPFA). Zygosity is inferred from like/unlike sex for birth denominators, and from concordance for DS cases.

MAIN OUTCOME MEASURES: Relative risk (RR) of DS per fetus/baby from multiple versus singleton pregnancies and per pregnancy in monozygotic/dizygotic versus singleton pregnancies. Proportion of prenatally diagnosed and pregnancy outcome.

STATISTICAL ANALYSIS: Poisson and logistic regression stratified for maternal age, country and time.

RESULTS: Overall, the adjusted (adj) RR of DS for fetus/babies from multiple versus singleton pregnancies was 0.58 (95% CI 0.53-0.62), similar for all maternal ages except for mothers over 44, for whom it was considerably lower. In 8.7% of twin pairs affected by DS, both co-twins were diagnosed with the condition. The adjRR of DS for monozygotic versus singleton pregnancies was 0.34 (95% CI 0.25-0.44) and for dizygotic versus singleton pregnancies 1.34 (95% CI 1.23-1.46). DS fetuses from multiple births were less likely to be prenatally diagnosed than singletons (adjOR 0.62 [95% CI 0.50-0.78]) and following diagnosis less likely to be TOPFA (adjOR 0.40 [95% CI 0.27-0.59]).

CONCLUSIONS: The risk of DS per fetus/baby is lower in multiple than singleton pregnancies. These estimates can be used for genetic counselling and prenatal screening.

Selective serotonin reuptake inhibitor antidepressant use in first trimester pregnancy and risk of specific congenital anomalies: a European register-based study

Evidence of an association between early pregnancy exposure to selective serotonin reuptake inhibitors (SSRI) and congenital heart defects (CHD) has contributed to recommendations to weigh benefits and risks carefully. The objective of this study was to determine the specificity of association between first trimester exposure to SSRIs and specific CHD and other congenital anomalies (CA) associated with SSRI exposure in the literature (signals). A population-based case-malformed control study was conducted in 12 EUROCAT CA registries covering 2.1 million births 1995-2009 including livebirths, fetal deaths from 20 weeks gestation and terminations of pregnancy for fetal anomaly. Babies/fetuses with specific CHD (n = 12,876) and non-CHD signal CA (n = 13,024), were compared with malformed controls whose diagnosed CA have not been associated with SSRI in the literature (n = 17,083). SSRI exposure in first trimester pregnancy was associated with CHD overall (OR adjusted for registry 1.41, 95% CI 1.07-1.86, fluoxetine adjOR 1.43 95% CI 0.85-2.40, paroxetine adjOR 1.53, 95% CI 0.91-2.58) and with severe CHD (adjOR 1.56, 95% CI 1.02-2.39), particularly Tetralogy of Fallot (adjOR 3.16, 95% CI 1.52-6.58) and Ebstein's anomaly (adjOR 8.23, 95% CI 2.92-23.16). Significant associations with SSRI exposure were also found for ano-rectal atresia/stenosis (adjOR 2.46, 95% CI 1.06-5.68), gastroschisis (adjOR 2.42, 95% CI 1.10-5.29), renal dysplasia (adjOR 3.01, 95% CI 1.61-5.61), and clubfoot (adjOR 2.41, 95% CI 1.59-3.65). These data support a teratogenic effect of SSRIs specific to certain anomalies, but cannot exclude confounding by indication or associated factors.

A DST-based Approach for Construction Project Risk Analysis

Despite its huge potential in risk analysis, the Dempster–Shafer Theory of Evidence (DST) has not received enough attention in construction management. This paper presents a DST-based approach for structuring personal experience and professional judgment when assessing construction project risk. DST was innovatively used to tackle the problem of lacking sufficient information through enabling analysts to provide incomplete assessments. Risk cost is used as a common scale for measuring risk impact on the various project objectives, and the Evidential Reasoning algorithm is suggested as a novel alternative for aggregating individual assessments. A spreadsheet-based decision support system (DSS) was devised to facilitate the proposed approach. Four case studies were conducted to examine the approach's viability. Senior managers in four British construction companies tried the DSS and gave very promising feedback. The paper concludes that the proposed methodology may contribute to bridging the gap between theory and practice of construction risk assessment.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

Exposure Assessment for Formaldehyde and Acetaldehyde in the Workplace

Personal exposure and possible cancer risk to formaldehyde and acetaldehyde were appraised in 8 work places at a university in Brazil. Levels of formaldehyde measured ranged from 22.5 to 161.5 g·m 3 and from 18.3 to 91.2 g·m 3 for acetaldehyde. The personal exposure, expressed as the potential dose in indoor air, was calculated to range from 129.8 to 930.4 g·day 1 (low exposure) and 183.9 to 1318.1 g·day 1 (medium exposure) for formaldehyde and 105.5 to 525.3 g·day 1 (low exposure) and 149.5 to 744.2 g·day 1 (medium exposure) for acetaldehyde. The indoor/outdoor ratio showed the existence of indoor sources of the compounds which were mainly in practical classes and research laboratories. The highest formaldehyde and acetaldehyde levels were found where chemical reagents were manipulated. Relating the levels found to the permissible limit given by the US OSHA showed there was no particular risk although some formaldehyde levels did exceed the lower exposure limit of the US agency NIOSH. Any cancer risk would be highest for female technicians and teaching researchers.

Avaliação do potencial cancerigénico de microcistinas (cianotoxinas)

Tese de doutoramento em Farmácia (Toxicologia), apresentada à Faculdade de Farmácia da Universidade de Lisboa, 2009.

Evaluation of ergonomic physical risk factors in a truck manufacturing plant: case study in SCANIA Production Angers

International audience

Nutritional risk among surgery patients and associations with hospital stay and postoperative complications

Introduction and Objectives: Nutritional Risk Screening (NRS 2002) is employed to identify nutritional risk in the hospital setting and determine which patients would benefit from nutritional support. The aim of the present study was to identify nutritional risk in patients admitted to the surgery ward and determine possible associations with hospital stay and postoperative complications. Methods: Three hundred fifteen surgery patients were evaluated in the first 24 hours since admission. Evaluations involved the calculation of the body mass index, the determination of weight loss ≥ 5% in the previous six months and the assessment of nutritional risk using the NRS 2002. Hospital stay (in days) and postoperative complications were also recorded. Results: A total of 31.1% of the patients were classified as being "at risk", among whom 98.3% had food intake 50% lower than habitual intake, 65.9% had weight loss ≥ 5% in the previous six months, 64.7% had a diagnosis of neoplasm, 59.9% were aged ≥ 60 years and 59.9% were candidates for non-elective surgery. Postoperative complications were recorded in 4.4% of the overall sample and were more frequent in patients at nutritional risk (p < 0.000). Hospital stay was also longer among the patients at nutritional risk (p < 0.01). Conclusion: A high percentage of surgery patients were at nutritional risk in the present study and associations were found with age ≥ 60 years, a diagnosis of neoplasm, non-elective surgery of the gastrointestinal tract, a reduction in habitual food intake and weight loss. Patients at nutritional risk had a greater frequency of postoperative complications and a longer hospital stay.

Strengthen Unilever-Jerónimo Martins’ position in the traditional supermarkets

Field lab: Entrepreneurial and innovative ventures