Fall 2015 Computer Science 458 10/7/15

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/

• hw2 extension: since Ronghui is out of town and unable to have office hours today, I have pushed the deadline to Saturday night at midnight.

• Next Monday's guest speaker is Professor Andrew Lo from MIT. There will be dinner at Mory's afterwards as well.

  Here some of his recent papers. He will discuss one or more of them. You are welcome to ask him questions about any of them.

  • Privacy-Preserving Methods for Sharing Financial Risk Exposures
  • Consumer credit-risk models via machine-learning algorithms
  • Moore’s Law versus Murphy’s Law: Algorithmic Trading and Its Discontents
  • Risk and Risk Management in the Credit Card Industry

• Conduct lottery for Monday dinner. Four students.

• Next Wednesday's guest speakers are 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

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.

Discussion

• See R package: stockPortfolio

• Example code

• Modern Portfolio Theory Continue with Efficient Market Hypothesis.

  Answers to exercies have been posted.

• Case Based Systems