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FINANCIAL ECO217 MARKETS: THEORIES & EVIDENCE Spring 2002 Time: Place: Instructor: Mondays and Wednesdays, 2pm to 3.15pm Dewey 2110D Thomas Renstr m Wallis Institute of Political Economy 110 Harkness Hall tel: 275-6834 e-mail: rnsm@troi.cc.rochester.edu Mondays 12.00-1.00 p.m. Wednesdays 12.00-1.00 p.m. Other times by appointment Office Hours: Class Web Site: http://www.econ.rochester.edu/Wallis/Renstrom/Eco217.html TAs: Juan Carlos Hatchondo, e-mail: hatch@troi.cc.rochester.edu Nathan Ringelstetter, e-mail: nr001h@mail.rochester.edu Once a week, Group 1: Wednesdays 5.00-5.5pm, in Meliora 219, Group 2:Fridays 2.00-2.50pm, in Meliora 208 Recitations: Aims The course introduces topics in financial economics at an intermediate level, focusing on methodology. Students will develop skills and learn tools for analysing and understanding financial markets. The main focus of the course is on finance from a microeconomic perspective. Objectives The students should be able to obtain a critical understanding of choice under uncertainty, portfolio formation, and equilibrium asset pricing (such as the CAPM and APT). Students should be able to derive asset-pricing relations from first principles, and understand the consequences if some of the underlying assumptions are relaxed. Students will gain understanding of how to formulate equations for empirical testing, and become aware of results from the empirical finance literature. Financial Markets: Theories & Evidence 2 General information The core material will be covered through classes. Exercises will be discussed in the weekly recitations, under the direction of the TA. Homework: During the course three sets of problems will be marked. You need to hand these selected sets (and only these) before the assigned recitation. The mark on those problem sets will count for 10% toward you final grade (see below under "Grades"). Exams: There will be two midterms and a final exam. The two midterms will be administered during regular class time, on February 27, 2002 and April 3, 2002. Midterm papers will be marked and returned to you in about a week. The final exam will take place on Tuesday May 7, 2002, starting at 8.30 am, place to be announced. There will be no make-up exams, and any conflicts or emergencies should be approved by Thomas Renstr m in advance of the exams. Grades: In determining your course grade, the following weights will be used: Homework: 10% Midterm 1: 20% Midterm 2: 20% Final Exam: 50% If a midterm exam is missed for a legitimate reason which has been pre-approved by me, the other midterm will count toward 40% of the final grade and the final exam will count toward 50% of the final grade. Lecture notes Lecture notes, problem sets, and further communication will be posted on the web (see link above) Topics to be covered Decision-making under uncertainty: expected utility, risk aversion, risk premia, insurance premia, portfolio choice. Asset pricing: standard Capital Asset Pricing Model (CAPM), Zero-Beta CAPM, APT. Empirical testing of asset pricing relations Course literature Copeland, T.E., and J.F. Weston, Financial Theory and Corporate Policy, Addison-Wesley. Main course reference. Other useful references Chiang, Alpha C. (1984), Fundamental Methods of Mathematical Economics, McGraw-Hill. Useful for mathematical requirements. Easy to read. Elton, J., Edwin and Martin J. Gruber (1995), Modern Portfolio Theory and Investment Analysis, Wiley. Useful for empirical applications of asset pricing models. Huang, C.F., and R.H. Litzenberger (1988), Foundations for Financial Economics, PrenticeHall. Useful for topics not covered in Copeland and Weston, but slightly more difficult to read. Hull, John, (1997), Options, Futures, and Other Derivatives, Prentice-Hall. Useful for option pricing and explanation of continuous-time stochastic processes. Jonathan E. Ingersoll, Jr. (1987), Theory of Financial Decision Making, Rowman & Littlefield. Useful for complementing Copeland and Weston, but is a rather difficult text. Financial Markets: Theories & Evidence 3 Course outline Lecture 1: Return and Risk. Copeland and Weston: chapter 6 (part A, and B1-B3), appendix B. Return, Risk and Choice under Uncertainty. Copeland and Weston: chapter 4 (introduction + part A + part B), appendix B. Choice under Uncertainty: Risk and Insurance Premia. Copeland and Weston chapter 4 (parts C-D, F - H), appendix D (part D). Introduction to Mean-Variance Efficient Portfolios. Copeland and Weston: chapter 6 (parts B4-B6, E1, and E3). Huang and Litzenberger: chapter 3, parts 3.6-3.7, and first paragraph of part 3.8. Ingersoll: first two pages of chapter 4. The Efficient Frontier and Mean-Variance Efficient Portfolios. Copeland and Weston: chapter 6 (parts B4-B6, E1, and E3). Huang and Litzenberger: chapter 3, parts 3.8-3.10. Ingersoll: pp. 82-87. The Investment-Opportunity Set. Copeland and Weston: chapter 6, part C (part B and E can be substituted with lecture notes and/or Huang and Litzenberger). Huang and Litzenberger: chapter 3, parts 3.11-3.13; chapter 4, part 4.1. Ingersoll: pp. 87-88. The Capital Asset Pricing Model (CAPM). Copeland and Weston: chapter 6, parts E4-E5; chapter 7, parts A-F. (Results regarding fund separation in Huang and Litzenberger, pp. 83-92, and in Ingersoll, pp. 143-145, [146-162 more difficult material], and p.164.) Relaxing the assumptions: Zero-Beta CAPM, Taxation and Borrowing-Lending constraints. Copeland and Weston: chapter 7, parts G1, G3-G5. (Huang and Litzenberger, pp. 70-72.) The Arbitrage Pricing Theory (APT). Copeland and Weston: chapter 7, part J. (Huang and Litzenberger: chapter 4, parts 4.19-4.22. Ingersoll: chapter 7, pp.166-170.) Lecture 2: Lecture 3: Lecture 4: Lecture 5: Lecture 6: Lecture 7: Lecture 8: Lecture 9: Lecture 10: Empirical Applications of the Capital Asset Pricing Model. Copeland and Weston: pp. 212-219. (Optional reference: Elton, Edwin J., and Martin J. Gruber (1995), Modern Portfolio Theory and Investment Analysis, Wiley, pp. 341-355, 359-362.) Lecture 11: Empirical Applications of the Arbitrage Pricing Theory. Copeland and Weston: chapter 7, part K. (Optional reference: Elton, Edwin J., and Martin J. Gruber (1995), Modern Portfolio Theory and Investment Analysis, Wiley, pp. 374-388.) Financial Markets: Theories & Evidence 4 Lecture 12: Introduction to Options. Copeland and Weston: chapter 8, parts A-C. (Optional reference: Hull, John, (1997), Prentice-Hall, chapters (6)-7.) Lecture 13: Introduction to Continuous-Time Finance and Option Pricing. Copeland and Weston: chapter 8, parts E-F, H. (Optional reference: Hull, John, (1997), Options, Futures, and Other Derivatives, Prentice-Hall, chapters (10)-11.)
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Rochester >> ECO >> 217 (Fall, 2009)
Lecture 7 The Capital Asset Pricing Model AIM OF LECTURE 7 Derive the Capital Asset Pricing Model (CAPM) Become familiar with Fund-Separation results 7.1 OVERVIEW We will derive the (standard) Capital Asset Pricing Model (CAPM) through Mean-Variance...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 8 Relaxing the assumptions: Zero-Beta CAPM, Taxation, and Borrowing-Lending constraints AIM OF LECTURE 8 Relax some of the assumptions underlying the Capital Asset Pricing Model (CAPM) 8.1 ZERO-BETA CAPM Why no risk-free asset? - inflation u...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 6 The Investment Opportunity Set AIM OF LECTURE 6 Derive the Investment Opportunity Set Illustrate investment decisions of individuals 6.1 DERIVING THE INVESTMENT OPPORTUNITY SET In the last lecture we found the portfolios that give the mini...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 13 Introduction to Continuous-Time Finance and Option Pricing AIM OF LECTURE 13 Become familiar with some continuous-time finance Learn how to form hedge portfolios with options Gain understanding of how a no-arbitrage argument underlies the ...
Rochester >> ECO >> 217 (Fall, 2009)
Financial Markets: Theories and Evidence 1 ECO217 Revision Lecture 2 R2.1 RELAXING ASSUMPTIONS UNDERLYING THE CAPM No risk-free borrowing/lending The zero-beta CAPM [Black (1972)]. E[Rj] - E[Rz] = j.(E[Rm] - E[Rz]) where j COV(Rj,Rm)/VAR(Rm)...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 3 Choice Under Uncertainty: Risk and Insurance Premia AIM OF LECTURE 3 Introduce the concept of risk aversion Provide measures of risk aversion Introducing the risk premium Solve for the Markowitz risk premium and analyze its components Intro...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 2 Return, Risk and Choice Under Uncertainty AIM OF LECTURE 2 Calculate return and risk of portfolios using matrix algebra Revise portfolio formation in the context of short sales Revise expected utility and provide a numerical example Show th...
Rochester >> ECO >> 217 (Fall, 2009)
ECO217 Example of Final Examination for Financial Markets: Theories and Evidence INSTRUCTIONS Answer four questions of your choice (of the five below). Write your name clearly on all answer booklets. Pocket calculator is allowed. Formulae attached at...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 5 The Efficient Frontier and MeanVariance Efficient Portfolios AIM OF LECTURE 5 Derive the Frontier Portfolios Analyse the properties of Frontier Portfolios 5.1 DERIVING THE FRONTIER PORTFOLIOS In the last lecture we formulated the optimisat...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 4 Introduction to Mean-Variance Efficient Portfolios AIM OF LECTURE 4 Introduce the intuitive idea behind efficient portfolios Formulate the optimisation problem in order to find efficient portfolios Learn how to differentiate with respect to...
Rochester >> ECO >> 217 (Fall, 2009)
ECO217 Answer to Sample Question 3 Question 3 (20%) Answer True or False (T or F ) T F (a) Two-fund separation is obtained only if there is a risk-free asset. (b) One-fund separation is obtained if returns are identically independently distributed. ...
Rochester >> ECO >> 217 (Fall, 2009)
Recitation 1 Return, Risk and Choice Under Uncertainty INSTRUCTIONS Make an attempt to solve the problems below (you need not to hand in your answers). The TA will go through the problems in the recitation. You are expected to actively participate an...
Rochester >> ECO >> 217 (Fall, 2009)
Financial Markets: Theories and Evidence 1 ECO217 Revision Lecture R.1 INTRODUCTION Course is about financial economics (pricing of risky assets) Three components: 1. 2. 3. Preferences (utility) Portfolios (the set of efficient portfolios is like a ...
Rochester >> ECO >> 217 (Fall, 2009)
Homework 2 Mean-Variance Efficient Portfolios INSTRUCTIONS 1. Solve the Problem 2.1 below (a-d), carefully showing your steps. 2. Hand in your work in the Class on Wednesday, March 20. 3. Your work will be marked and returned to you in respective rec...
Rochester >> ECO >> 217 (Fall, 2009)
ECO217 Sample Questions for Financial Markets: Theories and Evidence AIM OF QUESTIONS These questions give you an idea of the level, structure and type of questions you may expect on the midterm examination (you will have to answer all three question...
Rochester >> ECO >> 217 (Fall, 2009)
ECO217 Suggestion of Topics for Writing Credit INSTRUCTIONS Choose a topic and search for relevant literature. Produce an outline of your essay. Type your essay (5-10 pages), and hand it in on April 22. Prepare a presentation of your essay (10-15min)...
Rochester >> ECO >> 217 (Fall, 2009)
Homework 1 Return, Risk and Choice Under Uncertainty INSTRUCTIONS 1. Solve the two problems below (taken from Lecture 2), carefully showing your steps. 2. Hand in your work in the Class on Wednesday, February 6. 3. Your work will be marked and return...
Rochester >> ECO >> 217 (Fall, 2009)
ECO217 Answer to Question 5A in Example of Final Examination Question 5 A Calculate the theoretical price of the a call option to buy one share. The current share price is 70, the exercise price is 65 and the annual risk free rate is 6%. The option m...
Rochester >> ECO >> 217 (Fall, 2009)
Lecture 1 Return, Risk and Choice Under Uncertainty AIM OF LECTURE 1 Introduction of return and risk Calculate return and risk of portfolios Introduce matrix notation 1.1 NOTATION AND DEFINITIONS USED IN THIS COURSE Notation U( )= utility function (...
Rochester >> SOSP >> 2003 (Fall, 2009)
SIGOPS General chair Michael L. Scott U. of Rochester scott@cs.rochester.edu Program chair Larry Peterson Princeton University llp@cs.princeton.edu Program Committee Brian Bershad Washington Ken Birman Cornell Peter Druschel Rice Dawson Engler Stanfo...
Rochester >> CSC >> 248 (Fall, 2009)
Context Free Grammars So far we have looked at models of language that capture only local phenomena, namely what we can analyze when looking at only a small window of words in a sentence. To move towards more sophisticated applications that require s...
Rochester >> CSC >> 248 (Fall, 2009)
Lecture 16: Applications Using Ordered Alignment Models Many of the problems we have seen so far can be seen as the translation of some source stream of data into a target stream. For instance, in part of speech tagging we have a source stream of wor...
Rochester >> CS >> 247 (Fall, 2009)
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Rochester >> CS >> 242 (Fall, 2009)
Comprehensive Final Exam Answers with FFQ(TM) Feature. CSC 242 May 2004 Write your NAME legibly on the bluebook. Work all problems. Best strategy is not to spend more than the indicated time on any question (minutes = points). There are 120 points. O...
Rochester >> CS >> 242 (Fall, 2009)
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Rochester >> CS >> 242 (Fall, 2009)
Second Midterm CSC 242 10 May 2002 Write your NAME legibly on the bluebook. Work all problems. Best strategy is not to spend more than the indicated time on any question (minutes = points). Open book, open notes. 1. Grammar: 30 mins. We all remember:...
Rochester >> CS >> 242 (Fall, 2009)
Midterm CSC 242 3 March 2005 Write your NAME legibly on the bluebook. Work all problems. You may use three double-sided pages of notes. Please hand your notes in with your bluebook. The best strategy is not to spend more than the indicated time on an...
Rochester >> CS >> 242 (Fall, 2009)
Midterm CSC 242 March 2006 Write your NAME legibly on the bluebook. Work all problems. You may use two double-sided pages of notes. Please hand your notes in with your bluebook. The best strategy is not to spend more than the indicated time on any qu...
Rochester >> CS >> 242 (Fall, 2009)
Success Facilitation Survey: Unit 1. CSC 242 May 2004 Write your NAME legibly on this paper. Open book, open notes. Youre in a startup company working on a shortest-time algorithm for driving in Rochester to bundle with a global positioning system. W...
Rochester >> CS >> 242 (Fall, 2009)
Midterm Answers New, Improved, and Including the Postmortem FFQ Feature [look for square brackets] CSC 242 18 March 2002 Write your NAME legibly on the bluebook. Work all problems. Best strategy is not to spend more than the indicated time on any que...
Rochester >> CS >> 242 (Fall, 2009)
Final with Answers and FFQ (tm) CSC 242 9 May 2003 Write your NAME legibly on the bluebook. Work all problems. Best strategy is not to spend more than the indicated time on any question (minutes = points). Open book, open notes. 1. Bayes Nets: 15 Min...
Rochester >> CS >> 242 (Fall, 2009)
Clustering and Classication Chris Brown April 7, 2005 1 Explanation This is actually an assignment from the computer vision class. It sort of shows what a possible classication project would be like, and it has a tutorial about clustering techniqu...
Rochester >> CS >> 242 (Fall, 2009)
Midterm Answers, with FFQ(TM) feature CSC 242 March 2007 Write your NAME legibly on the bluebook. Work all problems. You may use two double-sided pages of notes. Please hand your notes in with your bluebook. The best strategy is not to spend more tha...
Rochester >> CS >> 242 (Fall, 2009)
CSC 242 Written Assignment #1 Knowledge Representation Using Logic Spring 1999 Answer all four questions below. Due date is MARCH 4th. 1. (25 points) Consider the following sentences: a. b. c. d. 2. John likes all kinds of food Apples are fo...
Rochester >> CS >> 242 (Fall, 2009)
Final CSC 242 5 May 2000 Write your NAME legibly on the bluebook. Work all problems. Best strategy is not to spend more than the indicated time on any question (minutes = points, total of 140). Open book, open notes. Note to Instructor: use of book m...
Rochester >> CS >> 242 (Fall, 2009)
2nd Midterm Exam CSC 242 6 May 2005 Write your NAME legibly on the bluebook. Work all problems. You may use three double-sided pages of notes. Please hand your notes in with your bluebook. The best strategy is not to spend more than the indicated tim...
Rochester >> CS >> 242 (Fall, 2009)
Midterm with Answers and FFQ (tm) CSC 242 6 March 2003 Write your NAME legibly on the bluebook. Work all problems. Best strategy is not to spend more than the indicated time on any question (minutes = points). Open book, open notes. 1. Search: 5 Min....
Rochester >> CS >> 242 (Fall, 2009)
Mabel Extending Human Interaction and Robot Rescue Designs Thomas Kollar, Jonathan Schmid, Eric Meisner, Micha Elsner, Diana Calarese, Chikita Purav, Jenine Turner, Dasun Peramunage, Gautam Altekar, and Victoria Sweetser Advised by Dr. Chris Brown De...
Rochester >> CS >> 242 (Fall, 2009)
Jess: AProductionSystemLanguage 4.209AgentBasedVirtualWorlds MaryLouMaherMITFall2002 JessKnowledgeBase A rule-based system maintains a collection of knowledge nuggets called facts. This collection is known as the knowledge base. It is somewhat a...
Rochester >> CS >> 242 (Fall, 2009)
Second Midterm CSC 242 May 2008 Write your NAME legibly on the bluebook. Work all problems. You may use two double-sided pages of notes. Please hand your notes in with your bluebook. The best strategy is not to spend more than the indicated time on a...
Rochester >> CS >> 242 (Fall, 2009)
Optical Character Segmentation and Recognition from a Rochester Flag Thomas Kollar and Jonathan Schmid 05/07/02 Abstract This project investigated segmentation and recognition of characters from a Rochester Flag as visual behaviors for landmark reco...
Rochester >> CS >> 242 (Fall, 2009)
Creating a Computer Cop An Integrated Approach to Recognizing Human Eating Activity Peter Barnum, Dominic Marino, Evan Merz, Matt Pelmear, and Dasun Peramunage Under Randall Nelson University of Rochester May 2003 Abstract Food damage causes untold d...
Rochester >> CS >> 242 (Fall, 2009)
Artificial Intelligence in Games: A look at the smarts behind Lionhead Studios Black and White and where it can and will go in the future James Wexler University of Rochester Rochester, NY 14627 jw005i@mail.rochester.edu Keywords: artificial intell...
Rochester >> CS >> 242 (Fall, 2009)
Practical applications of Philosophy in Artificial Intelligence Karim Oussayef Among the sciences, Artificial Intelligence holds a special attraction for philosophers. A.I. involves using computers to solve problems that seem to require human reason...
Rochester >> CS >> 242 (Fall, 2009)
Intelligent Autonomous Agents in Quake David Ganzhorn, William de Beaumont University of Rochester February 27th, 2004 Abstract For several weeks we researched and developed agents that interact with Quake2UR, a version of Quake2 that has been modifi...
Rochester >> CS >> 242 (Fall, 2009)
Adressing CML by Using Line Detection Techniques for More Reliable Sonar Information. Eric M. Meisner, CSC 242Term Project University of Rochester 2003 Abstract The purpose of this paper will be to describe a method for performing concurrent mapping...
Rochester >> CS >> 242 (Fall, 2009)
Kiana Ross CS242 3.23.00 UCPOP: ANALYSIS There are several aspects of partial order planners that are interesting and worth considering. The following paper will examine these aspects as they pertain to UCPOP. This paper will consider three domains: ...
Rochester >> CS >> 242 (Fall, 2009)
A Poker Player Chris Brown The University of Rochester Computer Science Department Rochester, New York 14627 Technical Report January 2006 Abstract This Texas Hold Em client relies on enumerations and probabilities. As parameters, it uses many funct...
Rochester >> CS >> 242 (Fall, 2009)
Artificial Intelligence Beating Human Opponents in Poker Stephen Bozak University of Rochester Independent Research Project May 08, 2006 Abstract In the popular Poker game, Texas HoldEm, there are never more than three moves an agent can make. Howev...
Rochester >> CS >> 242 (Fall, 2009)
Q-Learning and Collection Agents Tom O\'Neill Leland Aldridge Harry Glaser CSC242, Dept. of Computer Science, University of Rochester {toneill, hglaser, la002k}@mail.rochester.edu Abstract Reinforcement learning strategies allow for the creation ...
Rochester >> CS >> 242 (Fall, 2009)
Charles Balconi cbalconi@cs.rochester.edu CSC242 Term Project Due: 5/7/03 A Study of Methods Used to Solve NP Hard Optimization Problems Overview: Many optimization algorithms have been implemented to provide solutions to computationally hard probl...
Rochester >> CS >> 242 (Fall, 2009)
CS 242 Final Project: Reinforcement Learning Albert Robinson May 7, 2002 Introduction Reinforcement learning is an area of machine learning in which an agent learns by interacting with its environment. In particular, reward signals are provided to ...
Rochester >> CS >> 242 (Fall, 2009)
Alexander Wang and Corey Proscia CSC 242: Vision, May 8, 2006 Chart Supplement to Write-Up Chart Notes Color is required to view the charts properly! The normalized scale in Chart 2 is different from all other normalized scales. This is because the...
Rochester >> LEARNING >> 242 (Fall, 2009)
Quagent control via Passive and Active Learning Computer Science 242: Artificial Intelligence March 5, 2004 Rob Van Dam and Greg Briggs Abstract: Artificial intelligence algorithms using passive and active learning versions of direct utility estimat...
Rochester >> LEARNING >> 242 (Fall, 2009)
Learning Algorithms and Quake David Ganzhorn, William de Beaumont University of Rochester March 19th, 2004 Abstract We experimented with implementing various classic learning algorithms. We implemented value iteration and modified policy iteration, a...
Rochester >> CS >> 242 (Fall, 2009)
The Applicability of Uninformed and Informed Searches to Maze Traversal Computer Science 242: Artificial Intelligence Dept. of Computer Science, University of Rochester Nicole Dobrowolski Abstract: There are many strategies for maze traversal: always...
Rochester >> CS >> 242 (Fall, 2009)
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Rochester >> CS >> 242 (Fall, 2009)
Modeling Priority Management Strategies Using UR-Quagents and JESS Tom O\'Neill Harry Glaser Leland Aldridge CSC242, Dept. of Computer Science, University of Rochester {toneill, hglaser, la002k}@mail.rochester.edu Abstract Complex agents with int...
Rochester >> CS >> 242 (Fall, 2009)
Authors: Michael Rotondo Undergraduate, Computer Science, University of Rochester mr001m@mail.rochester.edu Jon Ruskin Undergraduate, Computer Science, University of Rochester jr003m@mail.rochester.edu David Sloan Undergraduate, Computer Science...
Rochester >> CS >> 242 (Fall, 2009)
Quagent Manipulation through Natural Language Understanding Computer Science 242: Artificial Intelligence April 16, 2004 Rob Van Dam and Greg Briggs Abstract: Artificial intelligence algorithms designed to simulate an agent with the Quake II enviro...
Rochester >> CS >> 242 (Fall, 2009)
Representation for N Jug Problem Chris Brown February 17, 2003 ; generate successors for n-jug problem ; For N jugs, state is N+1 long list giving the current contents ; of all the jugs. ; The zeroth jug is an infinite source and sink of water and ...
Rochester >> CS >> 242 (Fall, 2009)
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Rochester >> CS >> 254 (Fall, 2009)
Midterm Exam CSC 254 18 October 2005 Directions; PLEASE READ This exam comprises a mixture of short-answer and problem-solving questions. Values are indicated for each; they total 90 points. Question 6(e) is worth 8 extra credit points; it wont fact...
Rochester >> CS >> 254 (Fall, 2009)
Midterm Exam CSC 254 16 October 2008 DirectionsPLEASE READ This exam comprises a mixture of multiple-choice, short-essay and problem-solving questions. Values are indicated for each; they total 65 points. Questions 16 and 17 are worth 6 and 10 extra...
Rochester >> CS >> 254 (Fall, 2009)
A Guide to the Rochester PL/0 Compiler Michael L. Scott Computer Science Department University of Rochester Revised August 2004 Rochesters PL/0 compiler attempts to illustrate the characteristics of a real compiler on a modest scale. It runs on Un...
Rochester >> CS >> 254 (Fall, 2009)
Midterm Exam CSC 254 17 October 2006 Directions; PLEASE READ This exam comprises a mixture of short-answer and problem-solving questions. Values are indicated for each; they total 100 points. Questions 5(f) and 7 are worth 10 and 8 extra credit poin...
Rochester >> CS >> 254 (Fall, 2009)
Final Exam CSC 254 18 December 2007 Directions; PLEASE READ This exam comprises a mixture of short-answer and problem/essay questions. Values are indicated for each; they total 70 points. Question 15 is worth 8 extra credit points; it wont factor in...
Rochester >> CS >> 254 (Fall, 2009)
End-term Exam CSC 254 11 December 2008 DirectionsPLEASE READ This exam comprises a mixture of short-answer and essay questions. Values are indicated for each; they total 90 points. Questions 9 and 10 are worth 10 extra credit points each; they wont ...
Rochester >> CS >> 254 (Fall, 2009)
Final Exam CSC 254 19 December 2006 Directions; PLEASE READ This exam has 23 questions: 15 multiple-choice, 6 short-answer, and (for extra credit) 2 essays. The non-extra-credit questions total 100 points; values are indicated for each. (Several of ...
Rochester >> CS >> 254 (Fall, 2009)
Midterm Exam CSC 254 18 October 2007 Directions; PLEASE READ This exam comprises a mixture of multiple-choice, short-answer and problem-solving questions. Values are indicated for each; they total 67 points. Question 16 is worth 8 extra credit point...
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