since 1965  (really?)

Quantitative Trading

This course listing applies to a Spring 2014 course. To find current courses, check out the Find a Course page.

Spring 2014
UGBA 98/198
2 Unit(s)

Human friendly URL (OBSOLETE)


About the Course:

The Quantitative Trading DeCal will prepare you for the future. As financial markets become more efficient, connected, globalized and integrated, interdisciplinary skills become more valued in the industry. Quantitative trading is a merge between business, finance, economics, statistics, math, and computer science – training you in how to collaborate with others of complimentary skills to gain an edge in an ever increasingly competitive market.

The lectures and guest speakers will introduce you to the field and explain the main topics, listed below. We welcome all relevant majors to apply. In this class, you will comprise a group of likeminded peers who will research, plan, construct, test, and implement a successful algorithmic trading strategy that will hopefully be able to be used to generate real money. This is entirely doable.

Ultimately, this DeCal should help you get a job – and stand a chance in making it on your own.  Quant trading is a field which is already hungry for talent and pays well.  Past alumni of this class have gone to Goldman Sachs, Morgan Stanley, JP Morgan, RGM Advisors, Ronin Capital, Cerebellum Capital, Headlands Technologies, and others. They came in very qualified and determined, and found a sense of direction in this DeCal as no class at UC Berkeley is specially designed to address this topic.


          Equity Trading
          Machine Learning
          Risk Management
          Strategies and Algorithms
          Programming and Hardware
          Market Behavior and Psychology


You will be assigned weekly tasks that contribute to a class project. All homework will be practical--no busywork.

How to Enroll:

Prerequisites – Strong interest in at least óne of these fields:
• Event-Driven and Mathematical Programming

• Machine Learning and Artificial Intelligence

• Technical or Fundamental analysis

• Probability and Statistics

• Behavioral Finance

• Equity Trading


Recommended experience
- Mathematics

- Probability (Stat 134, semi-professional poker player wannabe, or lots of reading and implementing statistical learning algorithms or something similar on your own time)

- Strong interest in trading (you've traded regularly in a personal account, interned at a trading firm, or tested some models on historical data on your own) 

- Programming


Application Process
Please email with the following subject line: 
[QuantDecal] Application

In the email, please answer the following questions:

Who are you? 
1. First Name, Last Name

2. Student ID Number

3. Email Address

4. Phone Number 


What are you studying? 
1. Major(s) and Graduation Year

2. Current Work Experience

3. Prior Work Experience

4. What unique talent or expertise do you bring to the class? 


Why this class?
1. How did you hear about the course?

2. Why do you want to take it?  


What relevant Quant Experience do you have?
1. Event-Driven and Mathematical Programming

2. Machine Learning and Artificial Intelligence

3. Technical or Fundamental analysis

4. Probability and Statistics

5. Behavioral Finance

6. Equity Trading


Why you?
If there was one spot left in the class and we were choosing between you and another applicant, tell us why you should be selected for the class.

Email with answer to questions listed above, with the following subject line:
[QuantDecal] Application   


In the email, please attach a PDF copy of your resume and name the file "QuantDeCal_FirstName_LastName.pdf".

We wish you good luck in the application process and please feel free to contact us. The deadline for the application is 11:59pm February 6th, but we will approve strong candidates on an ongoing basis - so applying early is recommended, as we have a quota!

The facilitators will decide who will be enrolled in the course after reviewing all the applications. CCN's will be sent by email to those who are admitted.

Course Contact: paultawfik AT


Faculty Sponsor: Terrence Hendershott

Time & Location:

Quantitative TradingPaul Tawfik
31Haas C335W 7p-9p1/22started

Uploaded Files:

Syllabus: Quantitative Trading Syllabus.pdfDec 1683kbAdobe PDF (Viewer)View Download
Course Material: maxdama.pdfDec 7445kbAdobe PDF (Viewer)View Download

Course info last modified July 21, 2014. This page has been viewed 7016 times.

Could not update hit count.

Table './decalwebsite/d_coursevisitors' is marked as crashed and last (automatic?) repair failed