Investment Factor/Model Optimization & Backtesting and Introduction of New Data Sets for Investment Optimization - AB-037

Preferred Disciplines: Mathematics, Physics, Computer Science, Engineering, Statistics. PhD or Masters
Project length: 8-12 months per position
Desired start date: September 1, 2018
Location: Calgary, AB
No. of Positions: 3
Preferences: No preference
Language: English
Company: Anonymous

About Company:

We are a financial services company focused on bringing alternative funds to both the Canadian and global marketplace. Our strategies are focused on quantiative methods that seek to identify factors that have generated market-beating returns historically that can be combined to generate returns for shareholders in a low-risk framework. Our team brings over a decade of experience in the hedge fund industry.

Project Description:


1)Investment Factor/Model Optimization & Backtesting

  • We are looking to refine our investment models prior to fund launch. This will require the backtesting of factors and interpretation of the raw data to provide insight into the alpha generating capacity of the specific factor and in combination with others.


2)Introduction of New Data Sets for Investment Optimization

  • Research the usefulness of both new data sets and factors for our quantitative investment model.



Research Objectives/Sub-Objectives:

  • Bring our investment products to commercialization
  • Introduce new data sets that are beyond the scope of traditional investment companies


  • TBD

Expertise and Skills Needed:

  • Knowledge of one or more programming languages (MATLAB, C++, SQL, Java, etc.)
  • Experience working with advanced data sets
  • Mathematical and statistical ability to solve problems that require a quantitative and sometimes creative approach
  • Preference will be given to candidates with a desire to learn or ability to apply machine learning concepts


For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects.
  2. Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed!
  3. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Oba Harding at, oharding(a)