'Monte carlo' diaporamas de présentation

MN50324: MAF Corporate Finance: Semester 2, 2008/9

MN50324: MAF Corporate Finance: Semester 2, 2008/9 Investment Appraisal, decision trees, real options. Cost of capital (Bridging section). 3. Capital Structure and Value of the Firm. Optimal Capital Structure - Agency Costs, Signalling. Mergers and Acquisitions. Convertible Debt.

1.73k views • 111 slides

Statistical Methods in Particle Physics Day 1: Introduction

969 views • 63 slides

Tarek A. Elgohary University of Central Florida Internet of Things (IoT) Summit at RWW2019

A New Method for Computing Orbital Probability of Collision and Autonomous Space-based Orbit Estimation with Multiple Agent Nodes. Tarek A. Elgohary University of Central Florida Internet of Things (IoT) Summit at RWW2019 January 21 st , 2019. Motivation.

742 views • 56 slides

Retirement

680 views • 41 slides

Retirement

573 views • 41 slides

Recent Spin Physics Results from the Experiment

791 views • 38 slides

Estimating the Workers Compensation Tail

Estimating the Workers Compensation Tail. Richard Sherman & Gordon Diss . SAIF Corp. (Oregon State Fund). Extensive data for 160,000 permanent disability claims. Accident years 1926-2002. 77 years of development experience. Medical & indemnity payments separated.

695 views • 36 slides

Probability and Risk

640 views • 27 slides

Performance Yield-Driven Task Allocation and Scheduling for MPSoCs under Process Variation

Performance Yield-Driven Task Allocation and Scheduling for MPSoCs under Process Variation. Presenter: Lin Huang Lin Huang and Qiang Xu CU hk RE liable computing laboratory (CURE) The Chinese University of Hong Kong. Process Variation Becomes A Serious Concern.

431 views • 25 slides

Romanian Antheneum, Bucharest, Romania

451 views • 22 slides

Modeling and Simulation

Modeling and Simulation. CS 4211. Course outlines. Introduction. (Definition, Brief History, Applications and advantage and disadvantages of simulation) Simulation Software Discrete event simulation Introducing the discrete event simulation Single server queuing systems simulation

1.41k views • 22 slides

XENON10: Searching For Dark Matter with a Noble Liquid TPC

345 views • 21 slides

Enterprise Risk Management

Enterprise Risk Management. Framework for establishing industry requirements and priorities. Andreas Vogel September 13 th , 2006. Framework for Discussion. This is a strawman proposal which summarizes some thinking and brainstorming Next steps Team discussion and refinement

683 views • 20 slides

b-tagging commissioning strategy at ATLAS

b-tagging commissioning strategy at ATLAS. Introduction: b-tagging for top at LHC What is required of b-tagging algorithms? Tagging b-jets Lifetime-based b-tagging algorithms Soft lepton-based b-tagging algorithms Commissioning b-tagging Track selection and alignment

320 views • 20 slides

W/Z Plan For Winter Conferences

316 views • 14 slides

Introduction to sampling

Introduction to sampling . Discussion on An Introduction to MCMC for Machine Learning, Andrieu et al., 2001. Sampling. What is sampling? Useful for? Bayesian inference and learning Normalization Marginalization Expectation Optimization Model selection. Sampling.

301 views • 12 slides

Monte Carlo Simulation

Monte Carlo Simulation. Presented by Megan Aldrich and Tiffany Timm. What is Monte Carlo?. Uses random numbers to generate a simulation to mimic real data Helps find statistics for data that is really messy Use of a computer is required. Discovery and First Use.

690 views • 11 slides

SPICE

402 views • 11 slides

ISOPT V

ISOPT V. March 11-14, 2004 Monte Carlo. ISOPP new name: ISOPT. International Symposium of Ocular Pharmacology and Pharmaceutics (ISOPP) has been changed to: International Symposium of Ocular Pharmacology and Therapeutics (ISOPT)

439 views • 9 slides

Quantitative Stock Selection: Dynamic Factor Weights

Quantitative Stock Selection: Dynamic Factor Weights. Campbell R. Harvey Duke University National Bureau of Economic Research. Dynamic Factor Weights. 1. We have identified five factors based on univariate quintile sorts: PB(1), PB(5), Mom(1), RR(1), ROE(5)

259 views • 7 slides