Fall 2015 Computer Science 458 10/14/15

Announcements

• export DISPLAY - another try.

• Here is a draft list of sample final projects.

• Final projects are due the last day of reading period.

• Office hours. Ronghui Gu is holding office hours at 305 AKW.

  Wednesday 2-4 pm.
  Thursday 7-9 pm.
  

  Kun Run has office hours at 203 AWK.

  Monday 7-9 pm
  Friday 10am - 12pm
  

• Ronghui has created a class Piazza site for the course. You should have received an email on friday notifying you of your enrollment. This should facilitate communication. https://piazza.com/

• Monday's guest speaker wass Professor Andrew Lo from MIT. Here are slides from his presentation.

• Today's guest speakers are Mike Bailey and Chinmay Karande from Facebook. Here is a paper that is related to one of the topics they will discuss.
  • Pairwise choice as a simple and robust method for inferring ranking data

• Here are the slides from Mike Bailey's talk

Mid Term Exam

• There will be a mid term exam in class on Monday October 19th. I understand that CS 323 has a midterm scheduled that day as well. I will offer a make up exam,Friday October 30th at 4pm, no deans excuse required. It is your choice.

• The exam will mostly comprise programming questions in R and Python. Any finance questions will be framed as programming questions. For example, here is the formula for computing the beta of a stock portfolio. Implement that in R or Python.

• The scope of the questions will be as follows:
  • R: The R Cookbook, chapters 1 - 9.
  • R: stockPortfolio package.
  • R: the swirl tutorial.
  • Python: The Python Cookbook, chapters 1 - 8.

• The questions will primarily be short answer, e.g., what output does this code produce? or what code would produce this output?

• You are not allowed to bring books or computers or other electronic devices. However, you are permitted to bring a single sheet of letter sized paper containing notes on Python and or R on both sides. You must handin your sheet along with your exam.

• Below is the basic structure of the exam:
  1. Write the values of each of the following R expressions.
  2. Write the values of each of the following Python expressions.
  3. Write a Python function that replicates the behavior of the following R function.
  4. Write an R function that replicates the behavior of the following Python function.
  5. Below is an edited transcript of an R session using the stockPortfolio package. Please fill in the missing elements (either commands or output).
  6. A description of a Monte Carlo simulation problem. Implement it in either R or Python.
  7. A description of a capital budgeting problem. Implement it in either R or Python.
  8. (Actual question) Write a descrition of a final project for this course. You should indicate whether this is a project you would like implement, or that it is purely speculative. You should specify the problem domain (e.g., finance, politics, medicine, dating, movies, etc.), the implementation language (e.g., R, Python, etc.), the decision making paradigm (e.g, Monte Carlo, expected value, linear regression, rule based system, case base system, etc.). Describe the behavior of the program, e.g., use cases or "for this input, the program gives this output." You should describe how the system would work. This could be a process model, a flow chart, list of data structures, etc. You are welcome to choose one of the sample final projects. [Note: given that I am telling you this ahead of time, it should be very difficult to lose points.]

Discussion

• See R package: stockPortfolio

• Example code

• Modern Portfolio Theory Continue with Efficient Market Hypothesis.

  Answers to exercies have been posted.

• Case Based Systems