Lecture Notes in Financial Econometrics (MSc course) Paul Söderlind1 1 January 2013 of St. Gallen. Address: s/bf-HSG‚ Rosenbergstrasse 52‚ CH-9000 St. Gallen‚ Switzerland. E-mail: Paul.Soderlind@unisg.ch. Document name: FinEcmtAll.TeX 1 University Contents 1 Review of Statistics 1.1 Random Variables and Distributions . . . . . . . . . . . . . . 1.2 Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Distributions Commonly Used in Tests . . . . . . . . . . . . . 1
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Proposal – Generalizations of Newsvendor Problem 1. Introduction: The newsvendor model has been used in operations management and applied economics for years to determine optimal ordering quantity under uncertain demand. Perishable goods such as banana and lettuce cannot be carried from one period to another. Managers have to make decision on the inventory level of perishable goods over a very limited period. For example‚ due to the uncertainty of the demand of the newspaper‚ the newsboy
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Analysis of Financial Time Series Third Edition RUEY S. TSAY The University of Chicago Booth School of Business Chicago‚ IL A JOHN WILEY & SONS‚ INC.‚ PUBLICATION Analysis of Financial Time Series WILEY SERIES IN PROBABILITY AND STATISTICS Established by WALTER A. SHEWHART and SAMUEL S. WILKS Editors: David J. Balding‚ Noel A. C. Cressie‚ Garrett M. Fitzmaurice‚ Iain M. Johnstone‚ Geert Molenberghs‚ David W. Scott‚ Adrian F. M. Smith‚ Ruey S. Tsay‚ Sanford Weisberg Editors Emeriti:
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terms of origin moments using the binomial expansion of (X )2‚ as shown below. 2 = E[ (X )2] = E[(X2 2 X + 2 )] = E(X2) 2 E(X) + 2 = E(X2) 2 = ()2 = 2 . (13) Example 24 (continued). For the exponential density‚ f(x) = e x‚ = = 2/2 and = = 1/ so that equation (13) yields 2 = V(x) = 2 = 1/2 . (Note that the exponential pdf is the only Pearsonian statistical model with CVx = 100%.) (3) The 3rd central moment‚ 3‚ is a measure of skewness
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following probability distribution. The squad is on duty 24 hours per day‚ 7 days per week: Time Between Emergency Calls (hr.) Probability 1 0.05 2 0.10 3 0.30 4 0.30 5 0.20 6 0.05 1.00 a. Simulate the emergency calls for 3 days (note that this will require a “running”‚ or cumulative‚ hourly clock)‚ using the random number table. b. Compute the average time between calls and compare this value with the expected value of the time between calls from the probability distribution
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M09/5/MATHL/HP1/ENG/TZ2/XX 22097205 mathematics higher level PaPer 1 Thursday 7 May 2009 (afternoon) 2 hours iNsTrucTioNs To cANdidATEs Write your session number in the boxes above. do not open this examination paper until instructed to do so. You are not permitted access to any calculator for this paper. section A: answer all of section A in the spaces provided. section B: answer all of section B on the answer sheets provided. Write your session number on each answer sheet‚ and attach them
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1. Torpedo question: 2 torpedoes‚ each with 1/3 probability of hitting/ sinking a ship 2. I have 20% chance to have cavity gene. If I do have the gene‚ there is 51% chance that I will have at least one cavity over 1 year. If I don’t have the gene‚ there is 19% chance that I will have at least one cavity over 1 year. Given that I have a cavity in 6 months‚ what’s the probability that I have at least a cavity over 1 year? 3. What is the probability of 5 people with different ages siting in ascending
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[pic] Eagle Airlines Business Decisions with Data Models Assignment on Risk Analysis Team Members: Sfykti Dimitra Goumas Evangelos Manikas Athanasios Papaspirou Yiannis As assigned by Mr. Hadjistelios‚ President of Eagle Airlines‚ a simulation analysis is developed in order to evaluate company’s intention to proceed with the purchase of a new aircraft. According to the President’s estimations‚ the uncertain parameters which affect the annual cash flow are the below;
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1. The time between arrivals of cars at MRR Service Company is shown in the following probability distribution: Times between Arrivals (Min) Probability 1 0.15 2 0.30 3 0.40 4 0.15 1.00 a) Simulate the arrival of cars at the company for 20 arrivals‚ and compute the average time between arrivals. Random number: 39‚ 73‚ 72‚ 75‚ 37‚ 02‚ 87‚ 98‚ 10‚ 47‚ 93‚ 21‚ 95‚ 97‚ 69‚ 41‚ 91‚ 80‚ 67‚ 59. b) Simulate the arrival of cars at the service station for one hour‚ and compute the average time between
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UMT 11th International Annual Symposium on Sustainability Science and Management 09th – 11th July 2012‚ Terengganu‚ Malaysia Irrigation Scheduling for Onion (Allium cepa L.) at Various Plant Densities in a Semi-Arid Environment A.O.A. Dorcas 1‚ M.D. Magaji1‚ A. Singh2‚ R. Ibrahim1 and Y. Siddiqui3 Department of Crop Science‚ UsmanuDanfodiyo University‚ Sokoto‚ P.M.B. 2346‚ Sokoto‚ Sokoto State‚ Nigeria. 2 A. Singh‚ School of Biosciences‚ Faculty of Science‚ The University of Nottingham‚ Malaysia
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