Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the top quark mass using charged particles in pp collisions at root s=8 TeV

Peer reviewe

Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

Peer reviewe

Effects of audience on orthographic variation

Research has demonstrated that speakers make linguistic choices in order to narrow or widen the social distance between a speaker and his or her audience. These choices are often based on a speaker???s awareness of an audience???s demographic profile, which is composed of characteristics such as age, gender, and ethnicity. The present study investigates the role that awareness of audience plays in influencing orthographic choices in a ???demographically lean??? community, i.e. an online community where demographic information about the audience is largely absent or intentionally obscured. Results indicate that awareness of audience remains a significant explanatory factor for style-shifting, even in the absence of many of the social cues present in demographically robust communities.published or submitted for publicationis peer reviewe

Transforming the Transcript to Reflect the Whole Scholar: Legitimizing Pedagogical Training for Graduate Student Instructors

Although universities acknowledge that teacher training is critical for ensuring quality undergraduate education, research has repeatedly demonstrated that universities typically do an inadequate job of preparing graduate students for their instructor role. In this paper, we show that both graduate students and universities find the pedagogical development of graduate students to be a valid endeavor, and while graduate students strive to legitimize their own pedagogical development, universities must more fully and officially engage in the process. We conclude with a short list of recommendations for universities to consider toward the goal of legitimizing graduate student pedagogical development

MESSY TALK IN VIRTUAL TEAMS Achieving Knowledge Synthesis through Shared Visualizations

Engineering teams collaborating in virtual environments face many technical, social and cultural challenges. In this paper we focus on distributed teams making joint unanticipated discoveries in virtual environments. We operationalize Dossick and Neff’s definition of “Messy Talk” as a process in which teams mutually discover issues, critically engage in clarifying and finding solutions to the discovered issues, exchange their knowledge, and resolve the issue. Can globally distributed teams use “Messy Talk” via virtual communication technology? We analyzed the interactions of four distributed student teams collaborating on a complex design and planning project using building information models (BIM) and the CyberGRID, a virtual world specifically developed for collaborative work. Their interactions exhibited all four elements of Messy Talk, even though resolution was the least common. Virtual worlds support real time joint problem solving by 1) providing affordances for talk mediated by shared visualizations, 2) supporting team perceptions of building information models that are mutable and 3) allowing transformations of those models while people were together in real time. Our findings suggest that distributed team collaboration requires technologies that support Messy Talk--and iterative trial-and-error--for complex multidimensional problems