Estimating Relative Risk Aversion, Risk-Neutral and Real-World Densities using Brazilian Real Currency Options

Building Risk-Neutral Densities (RND) from options data can provide market-implied expectations about the future behavior of a financial variable. And market expectations on financial variables may influence macroeconomic policy decisions. It can be useful also for corporate and financial institutions decision making. This paper uses the Liu et all (2007) approach to estimate the option-implied Risk-neutral densities from the Brazilian Real/US Dollar exchange rate distribution. We then compare the RND with actual exchange rates, on a monthly basis, in order to estimate the relative risk-aversion of investors and also obtain a Real-world density for the exchange rate. We are the first to calculate relative risk-aversion and the option-implied Real World Density for an emerging market currency. Our empirical application uses a sample of Brazilian Real/US Dollar options traded at BM&F-Bovespa from 1999 to 2011. The RND is estimated using a Mixture of Two Log-Normals distribution and then the real-world density is obtained by means of the Liu et al. (2007) parametric risktransformations. The relative risk aversion is calculated for the full sample. Our estimated value of the relative risk aversion parameter is around 2.7, which is in line with other articles that have estimated this parameter for the Brazilian Economy, such as Araújo (2005) and Issler and Piqueira (2000). Our out-of-sample evaluation results showed that the RND has some ability to forecast the Brazilian Real exchange rate. Abe et all (2007) found also mixed results in the out-of-sample analysis of the RND forecast ability for exchange rate options. However, when we incorporate the risk aversion into RND in order to obtain a Real-world density, the out-of-sample performance improves substantially, with satisfactory results in both Kolmogorov and Berkowitz tests. Therefore, we would suggest not using the “pure” RND, but rather taking into account risk aversion in order to forecast the Brazilian Real exchange rate.

Are real options a real option for real-world finance professionals? case study : the application of real options to evaluate investment projects in the latin american oil and gas field services industry

Brasil e outros mercados emergentes continuarão a apresentar muitas oportunidades de investimento nos próximos anos. Profissionais financeiros que gerenciam os processos de orçamento de capital nas empresas terão grandes desafios a enfrentar. Características específicas destes projetos como preços ligados a commodities (por exemplo: petróleo e gás e projetos agrícolas) e as incertezas habituais relacionadas com os mercados emergentes são desafios adicionais. Neste cenário, ferramentas mais sofisticadas de orçamento de capital como Opções Reais, oferece uma teoria mais robusta para lidar com incerteza, flexibilidade gerencial, e os resultados voláteis embutidas nestas oportunidades. A teoria de Opções Reais assume que o envolvimento dos gestores nos projetos gera valor à medida que potencializam os bons resultados ou reduzem as perdas por abandonar projetos com maus resultados. O objetivo principal desta pesquisa foi aplicar a análise de Opções Reais para um projeto de investimento e discutir o processo e os resultados da metodologia. O estudo de caso analisa retroativamente um projeto de investimento na Colômbia e compara os resultados sob o tradicional VPL e Opções Reais. As técnicas de avaliação foram realizadas como se estivessem sendo aplicadas no momento em que o projeto foi aprovado, e depois comparadas com o desempenho real do projeto. O estudo de caso avaliado possui dois tipos de Opções Reais: primeiro, o efeito de uma opção para cancelar um contrato que é analisado a partir da perspectiva do cliente que pode exercer essa opção, e o segundo, a opção de abandonar e adiar a partir da perspectiva da empresa que irá executar a investimento.

Reinventing development: utopias devised by committees and seeds of change in the real world

Includes bibliography

Optimized Duration of Clopidogrel Therapy Following Treatment with the Endeavor Zotarolimus-Eluting Stent in Real-World Clinical Practice (OPTIMIZE) Trial: Rationale and design of a large-scale, randomized, multicenter study

Background Current recommendations for antithrombotic therapy after drug-eluting stent (DES) implantation include prolonged dual antiplatelet therapy (DAPT) with aspirin and clopidogrel >= 12 months. However, the impact of such a regimen for all patients receiving any DES system remains unclear based on scientific evidence available to date. Also, several other shortcomings have been identified with prolonged DAPT, including bleeding complications, compliance, and cost. The second-generation Endeavor zotarolimus-eluting stent (E-ZES) has demonstrated efficacy and safety, despite short duration DAPT (3 months) in the majority of studies. Still, the safety and clinical impact of short-term DAPT with E-ZES in the real world is yet to be determined. Methods The OPTIMIZE trial is a large, prospective, multicenter, randomized (1: 1) non-inferiority clinical evaluation of short-term (3 months) vs long-term (12-months) DAPT in patients undergoing E-ZES implantation in daily clinical practice. Overall, 3,120 patients were enrolled at 33 clinical sites in Brazil. The primary composite endpoint is death (any cause), myocardial infarction, cerebral vascular accident, and major bleeding at 12-month clinical follow-up post-index procedure. Conclusions The OPTIMIZE clinical trial will determine the clinical implications of DAPT duration with the second generation E-ZES in real-world patients undergoing percutaneous coronary intervention. (Am Heart J 2012;164:810-816.e3.)

Models and Algorihtm for the Optimization of Real-World Routing and Logistics Problems

Logistics involves planning, managing, and organizing the flows of goods from the point of origin to the point of destination in order to meet some requirements. Logistics and transportation aspects are very important and represent a relevant costs for producing and shipping companies, but also for public administration and private citizens. The optimization of resources and the improvement in the organization of operations is crucial for all branches of logistics, from the operation management to the transportation. As we will have the chance to see in this work, optimization techniques, models, and algorithms represent important methods to solve the always new and more complex problems arising in different segments of logistics. Many operation management and transportation problems are related to the optimization class of problems called Vehicle Routing Problems (VRPs). In this work, we consider several real-world deterministic and stochastic problems that are included in the wide class of the VRPs, and we solve them by means of exact and heuristic methods. We treat three classes of real-world routing and logistics problems. We deal with one of the most important tactical problems that arises in the managing of the bike sharing systems, that is the Bike sharing Rebalancing Problem (BRP). We propose models and algorithms for real-world earthwork optimization problems. We describe the 3DP process and we highlight several optimization issues in 3DP. Among those, we define the problem related to the tool path definition in the 3DP process, the 3D Routing Problem (3DRP), which is a generalization of the arc routing problem. We present an ILP model and several heuristic algorithms to solve the 3DRP.

Secondary collisions revisited: real-world crash data and relationship to crash test criteria

Objectives: Previous research conducted in the late 1980s suggested that vehicle impacts following an initial barrier collision increase severe occupant injury risk. Now over 25years old, the data are no longer representative of the currently installed barriers or the present US vehicle fleet. The purpose of this study is to provide a present-day assessment of secondary collisions and to determine if current full-scale barrier crash testing criteria provide an indication of secondary collision risk for real-world barrier crashes. Methods: To characterize secondary collisions, 1,363 (596,331 weighted) real-world barrier midsection impacts selected from 13years (1997-2009) of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS) were analyzed. Scene diagram and available scene photographs were used to determine roadside and barrier specific variables unavailable in NASS/CDS. Binary logistic regression models were developed for second event occurrence and resulting driver injury. To investigate current secondary collision crash test criteria, 24 full-scale crash test reports were obtained for common non-proprietary US barriers, and the risk of secondary collisions was determined using recommended evaluation criteria from National Cooperative Highway Research Program (NCHRP) Report 350. Results: Secondary collisions were found to occur in approximately two thirds of crashes where a barrier is the first object struck. Barrier lateral stiffness, post-impact vehicle trajectory, vehicle type, and pre-impact tracking conditions were found to be statistically significant contributors to secondary event occurrence. The presence of a second event was found to increase the likelihood of a serious driver injury by a factor of 7 compared to cases with no second event present. The NCHRP Report 350 exit angle criterion was found to underestimate the risk of secondary collisions in real-world barrier crashes. Conclusions: Consistent with previous research, collisions following a barrier impact are not an infrequent event and substantially increase driver injury risk. The results suggest that using exit-angle based crash test criteria alone to assess secondary collision risk is not sufficient to predict second collision occurrence for real-world barrier crashes.

Real-World Performance of Longitudinal Barriers Struck by Large Trucks

Outside of relatively limited crash testing with large trucks, very little is known regarding the performance of traffic barriers subjected to real-world large truck impacts. The purpose of this study was to investigate real-world large truck impacts into traffic barriers to determine barrier crash involvement rates, the impact performance of barriers not specifically designed to redirect large trucks, and the real-world performance of large-truck-specific barriers. Data sources included the Fatality Analysis Reporting System (2000-2009), the General Estimates System (2000-2009) and 155 in-depth large truck-to-barrier crashes from the Large Truck Crash Causation Study. Large truck impacts with a longitudinal barrier were found to comprise 3 percent of all police-reported longitudinal barrier impacts and roughly the same proportion of barrier fatalities. Based on a logistic regression model predicting barrier penetration, large truck barrier penetration risk was found to increase by a factor of 6 for impacts with barriers designed primarily for passenger vehicles. Although large-truck-specific barriers were found to perform better than non-heavy vehicle specific barriers, the penetration rate of these barriers were found to be 17 percent. This penetration rate is especially a concern because the higher test level barriers are designed to protect other road users, not the occupants of the large truck. Surprisingly, barriers not specifically designed for large truck impacts were found to prevent large truck penetration approximately half of the time. This suggests that adding costlier higher test level barriers may not always be warranted, especially on roadways with lower truck volumes.

Wild immunology: converging on the real world

Recently, the Centre for Immunity, Infection and Evolution sponsored a one-day symposium entitled "Wild Immunology." The CIIE is a new Wellcome Trust-funded initiative with the remit to connect evolutionary biology and ecology with research in immunology and infectious diseases in order to gain an interdisciplinary perspective on challenges to global health. The central question of the symposium was, "Why should we try to understand infection and immunity in wild systems?" Specifically, how does the immune response operate in the wild and how do multiple coinfections and commensalism affect immune responses and host health in these wild systems? The symposium brought together a broad program of speakers, ranging from laboratory immunologists to infectious disease ecologists, working on wild birds, unmanaged animals, wild and laboratory rodents, and on questions ranging from the dynamics of coinfection to how commensal bacteria affect the development of the immune system. The meeting on wild immunology, organized by Amy Pedersen, Simon Babayan, and Rick Maizels, was held at the University of Edinburgh on 30 June 2011.

Secondary Collisions Revisited: Real-World Crash Characteristics and Relationship to Crash Test Criteria

Previous research conducted in the late 1980’s suggested that vehicle impacts following an initial barrier collision increase severe occupant injury risk. Now over twenty-five years old, the data used in the previous research is no longer representative of the currently installed barriers or US vehicle fleet. The purpose of this study is to provide a present-day assessment of secondary collisions and to determine if full-scale barrier crash testing criteria provide an indication of secondary collision risk for real-world barrier crashes. The analysis included 1,383 (596,331 weighted) real-world barrier midsection impacts selected from thirteen years (1997-2009) of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS). For each suitable case, the scene diagram and available scene photographs were used to determine roadside and barrier specific variables not available in NASS/CDS. Binary logistic regression models were developed for second event occurrence and resulting driver injury. Barrier lateral stiffness, post-impact vehicle trajectory, vehicle type, and pre-impact tracking conditions were found to be statistically significant contributors toward secondary event occurrence. The presence of a second event was found to increase the likelihood of a serious driver injury by a factor of seven compared to cases with no second event present. Twenty-four full-scale crash test reports were obtained for common non-proprietary US barriers, and the risk of secondary collisions was determined using recommended evaluation criteria from NCHRP Report 350. It was found that the NCHRP Report 350 exit angle criterion alone was not sufficient to predict second collision occurrence for real-world barrier crashes.

Real-world context, interest, understanding, and retention

This study investigated the use of real-world contexts during instruction in a high school physics class - through building file folder bridges- and the resulting effect upon student interest in the subject matter, level of understanding, and degree of retention. In particular, the study focused upon whether increases in student interest were attained through the use of real-world contexts, and if the elevated interest level led to a higher degree of subject matter understanding than would be achieved using more traditional teaching methods. The study also determined whether using real-world contexts ultimately resulted in achievement of greater levels of knowledge retention by students. Class observations during traditionally taught units and during units that incorporated real-world contexts, along with a post-graduation questionnaire, were used to assess differences in student interest levels. Student pre- and post-unit test scores were evaluated and compared to determine if statistical differences existed in levels of understanding resulting from the different teaching methods. The post-graduation questionnaire results provided evidence of retention that could be related back to teaching methods. The results of this study revealed the importance of incorporating real-world contexts into science and mathematics courses. Students better understood the relevance of the lessons, which led to higher levels of interest and greater understanding than was achieved through more traditional teaching methods. The use of real-world contexts improved knowledge retention.

Improving sixth grade student knowledge of ecology using fish rearing and release as a real-world context

This research project measured the effects of real-world content in a science classroom by determining change (deep knowledge of life science content, including ecosystems from MDE – Grade Level Content Expectations) in a subset of students (6th Grade Science) that may result from the addition of curriculum (real-world content of rearing trout in the classroom). Data showed large gains from the pre-test to post-test in students from both the experimental and control groups. The ecology unit with the implementation of real-world content [trout] was even more successful, and improved students’ deep knowledge of ecosystem content from Michigan’s Department of Education Grade Level Content Expectations. The gains by the experimental group on the constructed response section of the test, which included higher cognitive level items, were significant. Clinical interviews after the post-test confirmed increases in deep knowledge of ecosystem concepts in the experimental group, by revealing that a sample of experimental group students had a better grasp of important ecology concepts as compared to a sample of control group students.

Unprotected left main stenting in the real world: two-year outcomes of the French left main taxus registry

BACKGROUND: Cardiac surgery is the reference treatment for patients with left main (LM) disease, although percutaneous coronary intervention with drug-eluting stents is emerging as a possible alternative. The objective of this registry was to evaluate the 2-year outcome of elective percutaneous coronary intervention for unprotected LM disease with paclitaxel-eluting stents. METHODS AND RESULTS: A total of 291 patients were prospectively included from 4 centers. Acute myocardial infarction and cardiogenic shock were the only exclusion criteria. Patients were 69+/-11 years old, 29% were diabetic, and 25% had 3-vessel disease. For distal LM lesions (78%), the provisional side-branch T-stenting approach was used in 92% of cases and final kissing balloon inflation in 97%. Angiographic success was obtained in 99.7% of cases. At 2-year follow-up, the total cardiac death rate was 5.4% (1 EuroSCORE point was associated with a 15% [95% confidence interval 2.9% to 28.2%, P=0.013] higher risk of cardiac death), target-lesion revascularization was 8.7%, and incidence of Q-wave or non-Q-wave myocardial infarction was 0.9% and 3.1%, respectively. The combined end point occurred in 15.8% of cases and stroke in 0.7%. The incidence of definite and probable LM stent thrombosis was 0.7%, whereas the incidence of any stent thrombosis was 3.8%, with a higher risk in patients with side-branch stenting in the presence of LM bifurcation lesions (hazard ratio 9.6, 95% confidence interval 1.2 to 77.7, P=0.035). CONCLUSIONS: Unprotected LM stenting with paclitaxel-eluting stents, with a strategy of provisional side-branch T-stenting for distal lesions, provides excellent acute angiographic results and good mid-term clinical outcomes, with a 15.8% rate of major adverse cardiac events at 2-year follow-up.

Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models.