涵盖的内容有，foreign exchange markets; international investment decision making; sources of and approaches to dealing with foreign exchange exposure; political risk; and international funding mechanisms and decision making in multinational business organisations.
为什么要学习代写代考这门课
• Continuously liberalization of international trade and investment • Rapid advances in telecommunications and transportation technologies
The benefit of international trade is the mutual improvement of the welfare for both countries. The basis of this argument is the theory of comparative advantage. This theory says that countries should produce those goods for which they have comparative advantage, and then trade those goods. The underlying assumptions of this theory are the free trade between nations and that the factors of production are not easily movable from one country to the other. The first assumption is needed so that the trade can happen. The second assumption is needed because otherwise the input factors such as skilled workers can move from one country to another, which makes the comparative advantage disappear.
The University of Western Ontario DAN Management and Organizational Studies MOS 3311: Advanced Corporate Finance GROUP PROJECT代写，是个最近接到的为数不多的调理十分清晰，写起来十分高效，合作十分默契的小组作业
TOPIC 3 – RISK AND RETURN BIG QUESTIONS: What is the risk profile of the company? Provide a qualitative and quantitative analysis of the company’s risks and costs of capital. Risk and Return Basics • Obtain an estimate of the expected return and standard deviation for the company’s stock. How would you characterize total risk for potential investors in the company’s equity? • What is the performance profile of an investment in this company? What return would you have earned investing in this company’s stock? Would you have under or out-performed the market? • Obtain an estimate of the risk-free rate and the expected return on the market portfolio.
Estimating the Cost of Equity
The CAPM – Regression Beta Run a regression of returns on your firm’s stock against returns on a market index, or alternately, if you have access to Bloomberg, go into the beta calculation page and obtain the relevant output (suggestion: in either case, use monthly data and 5 years of observations). • What is the intercept of the regression? What does it tell you about the performance of this company’s stock during the period of the regression? • What is the slope of the regression? What does it tell you about the risk of the stock? • How precise is this estimate of risk? (Provide a range for the estimate). • Search for alternate estimates of beta for your company. How do they differ? How reliable are they? • What portion of this firm’s risk can be attributed to market factors? What portion to firm-specific factors? Why is this important? • How much of the risk for this firm is due to business factors? How much of it is due to financial leverage?
The CAPM – Fundamental Beta • Consider the firm’s business components, and obtain an estimate of business beta for each component if the firm has stated business components. • Attach weights to each component and estimate a levered and an unlevered beta for the business. Cost of Equity • Which of the beta estimates that you have obtained for the firm would you view as more reliable? Why? • Using the beta that you have chosen, estimate the expected return on an equity investment in this company. • How risky is this company’s equity? Why? What is its cost of equity? • As a manager in this firm, how would you use this expected return?
Estimating Cost of Debt • Does your company have the ability to service its existing debt load? • If your company has bonds outstanding, what is the yield to maturity on a long term bond? • If your company is rated: What is the most recent rating for the firm? What is the default spread and interest rate associated with this rating? • If your company is not rated, does it have any recent borrowings? If yes, what interest rate did the company pay on these borrowing? • Are there any alternative ways to estimate the cost of debt? • How risky is this company’s debt? What is its cost of debt? • What is the company’s marginal tax rate?
TOPIC 4 – CAPITAL BUDGETING BIG QUESTIONS: How effective is the company at making capital budgeting decisions? What process is used to choose investments? How successful have previous investments been relative to expectations? What are the implications for future growth? • What methods (NPV, IRR, Payback, Discounted payback, or other) does the firm use to make investment decisions? • Is there a typical project for this firm? If yes, what would it look like in terms of life (long-term or short-term), investment needs and cash flow patterns? • How good are the projects that the company has on its books currently? Are those projects providing a tax shield? • Have recent investment projects added value to the firm or destroyed value? If so, can you estimate how value was added or reduced? • Are the projects in the future likely to look like the projects in the past? Why or why not? How will these projects affect the firm? • Estimate the company’s operating cash flows for the latest year for which you have data. How may these, and total cash flows, change going forward? • Are there any real options in the firm? If so, what type?
Probability Central Tendency Variability Relationship Between Variables Probability Distribution Hypothesis Testing and Statistical Significance Regression
Topics covered in this course will include engineering plasticity, design of pressure vessels and pipes, thick-walled cylinders, shrink fitting, duplex pressure vessels, inelastic deformation, residual stresses, membrane theory of shells of revolution, yielding, rotating shells, local bending stresses, stress analysis of rotating discs with and without holes, shrink fitting, initial and ultimate yielding, fracture mechanics and fatigue, and introduction to the finite element method.
This course introduces the Bayesian paradigm for statistical inference. Topics covered include prior and posterior distributions: conjugate priors, informative and non-informative priors; one- and two-sample problems; models for normal data, models for binary data, Bayesian linear models, Bayesian computation: MCMC algorithms, the Gibbs sampler; hierarchical models; hypothesis testing, Bayes factors, model selection; use of statistical software.
Prerequisites: A course in the theory of statistical inference, such as STAT GU4204/GR5204 a course in statistical modeling and data analysis such as STAT GU4205/GR5205.
对Bayes有初步了解的，有一定 statistics，machine learning 基础的，且对理论有兴趣的人。整体上是基于 measure-theoretical probability， 所以读者最好有一定 measure theory基础，基本上，具有数学本科三年级基础就足够了。主要内容: Parametric Bayes and posterior consistency. Non-parametric Bayes, including Dirichlet process prior and Gaussian process prior. General consistency theory for non-parametric Bayes. Reproducing kernel Hilbert space (RKHS) theory.
5 Hierarchical models
5.1 Constructing a parameterized prior distribution 5.2 Exchangeability and setting up hierarchical models 5.3 Fully Bayesian analysis of conjugate hierarchical models 5.4 Estimating exchangeable parameters from a normal model 5.5 Example: parallel experiments in eight schools 5.6 Hierarchical modeling applied to a meta-analysis 5.7 Weakly informative priors for hierarchical variance parameters 5.8 Bibliographic note 5.9 Exercises
6 Model checking
6.1 The place of model checking in applied Bayesian statistics 6.2 Do the inferences from the model make sense? 6.3 Posterior predictive checking 6.4 Graphical posterior predictive checks 6.5 Model checking for the educational testing example 6.6 Bibliographic note
