Emory Goizueta | Mr. Multimedia
GRE 308, GPA 3.4
IU Kelley | Mr. Construction Manager
GRE 680, GPA 3.02
UCLA Anderson | Mr. Commercial Banker
GMAT 700, GPA 3.3
NYU Stern | Mr. Military Officer
GRE In Progress, GPA 2.88
Stanford GSB | Ms. Artistic Engineer
GMAT 730, GPA 9.49/10
Duke Fuqua | Ms. Account Executive
GMAT 560, GPA 3.3
Harvard | Mr. Healthcare Fanatic
GMAT 770, GPA 3.46
Harvard | Mr. Sovereign Wealth Fund
GMAT 730, GPA 3.55
Harvard | Mr. Smart Operations
GMAT 760, GPA 4.0
Darden | Mr. Strategy Manager
GRE 321, GPA 3.5
Ross | Mr. Airline Engineer
GMAT 730, GPA 3.73
Stanford GSB | Mr. Corporate VC Hustler
GMAT 780, GPA 3.17
Wharton | Mr. Marketing Director
GMAT 710, GPA 3.3
Ross | Ms. Healthcare Startup
GRE 321, GPA 3.51
Kellogg | Mr. Real Estate Finance
GMAT 710, GPA 3.0
Georgetown McDonough | Ms. Air Force
GMAT 610, GPA 3.8
Stanford GSB | Mr. JD To MBA
GRE 326, GPA 3.01
Harvard | Mr. MacGruber
GRE 313, GPA 3.7
Berkeley Haas | Mr. Poet At Heart
GMAT 740, GPA 3.7
Yale | Mr. Ukrainian Biz Man
GRE 310, GPA 4.75 out of 5
Darden | Mr. Former Scientist
GMAT 680, GPA 3.65
Stanford GSB | Mr. Sustainable Business
GRE 331, GPA 3.86
Wharton | Mr. Microsoft Consultant
GMAT N/A, GPA 2.31
Yale | Ms. Impact Investing
GRE 323, GPA 3.8
Cornell Johnson | Ms. Food Waste Warrior
GMAT Not written yet (around 680), GPA 3.27
Stanford GSB | Ms. Future Tech Exec
GMAT 750, GPA 3.4
Kellogg | Mr. Finance To Education
GMAT 730, GPA 3.4

Essential MOOC Courses In Business For June

Introduction to Computational Finance and Financial Econometrics

 

School: University of Washington

Platform: Coursera

Registration Link:  Introduction to Computational Finance and Financial Econometrics

Start Date: June 1, 2015 (10 Weeks)

Workload: Not Specified

Instructor: Eric Zivot

Credentials: A Yale Ph.D., Zivot has taught economics, statistics, finance, and applied mathematics courses at the University of Washington for 18 years. A consultant in the finance and software industries, Zivot conducts research on financial risk measurement and the econometric analysis of high frequency financial data. He has also received the university’s Henry T. Buechel Award for Outstanding Teaching.

Graded: Not Specified

Description: Using the R statistical programming language, students will learn how to “analyze financial data, estimate statistical models, and construct optimized portfolios.” In addition, students will create probability models to project asset returns and measure portfolio risk. Along with video lectures, students will complete assignments on Datacamp.com, which provides instant feedback on student computations.

Review: “Most of the class is spent in a detailed review of basic statistics, with an eye to applying it to financial data series. I really needed that, plus we were taught how to do all computations in R, with useful examples. Great treatment of confidence and the bootstrap methods. Final weeks were about basics of portfolio theory (efficient frontier, etc.) again enabling us to do all computations. I also appreciated the teacher mentioning that the theory’s value decreases when the market is unstable (as correlation increases) and showing how wildly the theoretic results can vary depending on when the data is collected. Overall I now feel confident with basic statistics (also beyond financial applications) and have continued to use R for statistics and data analysis since this class.” For additional reviews, click here.

Additional Note: Dr. Zivot recommends several texts before participating in the course, which are listed on the course link above.