15.450  Analytics of Finance

Additional office hour

I will hold an additional office hour this Friday at 10-12 (E62-637).

Announced on 17 May 2017  9:37  a.m. by Hui Chen

Q&A for Final Project (check for updates)

1. There's a single data point in the Borders data with a return of 3.33333. Is this a real data point?

Answer: Yes. This is a real data point.

2. Should we stick to the monthly data provided to the project or can we use data from other sources (e.g., daily data)?

Answer: Please only use the monthly data provided in the project.

3. In Q2, what does "Support your finding with statistical evidence" mean?

Answer: Measure the magnitude of the effect in the data and test whether it is statistically significant or not.

4. Quarterly earnings are filed after the end of the fiscal quarter. Do we need to find out the exact filing dates?

Answer: Since no filing date information is provided in the project, you should not be looking at strategies that require the exact filing dates.

5. Questions about what firms to include in the study, and how to compare/measure seasonality.

Answer: Feel free to do what you think is necessary and reasonable. State your assumptions clearly and try to justify them in your memo.

Announced on 15 May 2017  1:17  p.m. by Hui Chen

Recitations this week

Recitation will be held tomorrow at 4PM in E51-149 and Friday at noon in E52-315. I will go over some of the practice exam questions. Additionally, I will hold an office hour this coming Monday in E51-242 from 4-5PM.

Announced on 10 May 2017  11:04  p.m. by Peter G Hansen

Recitation

I will hold recitation tomorrow at 4PM in E51-149 and Friday at noon in E52-315. The recitation will review logistic regression. Additionally, I will hold an office hour this coming Monday in E51-242 from 4-5PM.

Announced on 26 April 2017  10:00  p.m. by Peter G Hansen

Guest Lecture on April 20, 2017

For tomorrow's lecture, we have Mikey Shulman from Kensho to tell us what his team is working on with finance analytics. (We will be taking attendance for this lecture, just like the regular lectures.)

Mikey is head of machine learning at Kensho, a financial technology company that services the banking industry as well as the intelligence community. Prior to joining Kensho Mikey received a PhD in physics from Harvard University where he studied quantum computing. At Harvard, Mikey built a two-bit quantum processor and he published work using machine learning both to improve the efficiency of quantum computers and to understand trends in physics research. Mikey graduated summa cum laude with a BS in applied physics and mathematics from Columbia University.

Announced on 19 April 2017  10:52  p.m. by Hui Chen