Become a Quantitative Analyst

Financial Timeseries Analysis & Optimization

What is this Course About?

Wall Street needs more quants and data scientists.

This course will allow you to build the essential initial programming skills and tool belt of statistical techniques required for quantitative analysis.

First, we'll teach you how to program with financial timeseries before diving deep into multivariate regressions using factor analysis to explain Berkshire Hathaway's performance.

Next, we'll examine the performance of 9 different hedge fund strategies and compare the risk and return characteristics of each type of fund.

Finally, we'll construct our own fund strategy using quadratic optimization to track a benchmark on a rolling basis, and we'll build our own backtesting engine in R to analyze our strategy.

Am I Ready for this Course?

Whether you're a hedge fund manager or a business student, this course is for you if you're looking to upgrade your game and begin investing intelligently.

We'll provide you with commented source code, guided video tutorials and high quality animations to help you understand every line of code and concept.

Become a Quant.


How Does Warren Buffet Do It?

Use multivariate rolling regression techniques on market factors to explain Warren Buffet's returns

Create Your Own Indexing Strategy

Use quadratic optimization to create an indexing strategy and then build a rolling backtesting engine to compare your results to the benchmark

Your Instructor

Dakota Wixom
Dakota Wixom

Dakota is a Quantitative Analyst at an AI startup, where he built out the first few financial products and sells complex signals and factors on global securities to the most sophisticated hedge funds in the world, and helps to construct advanced network-based products and create specialized indexes for leading index providers, such as the STOXX AI powered AI Index and the NASDAQ Yewno Global Disruptive Technology Benchmark Index. Dakota previously worked in NYC for Mizuho Bank as a front office investment banking quant on the corporate finance advisory team as well as in San Francisco for Charles Schwab's Investment Risk quant group.

He has an M.Sc. in Financial Analytics with high honors sponsored by Accenture, and a B.Sc. in Quantitative Finance from the Stevens Institute of Technology, where Dakota's work included research on risk averse two-stage stochastic programming problems for portfolio optimization.

Frequently Asked Questions

When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I don't know how to program?
No worries. R is one of the easiest programming languages to learn, and we'll have you up and running in no time. We'll step you through every single line of code as we go, and we'll provide the downloadable source code for every lecture in case you get lost. If you can use Excel, you're not going to have a problem learning R with our help!
Do I get the source code?
You sure do! Every single section is comprised of multiple video tutorials with hours of content, as well as source code and useful links to help you along the way. We'll continue to add resources and answer any questions you might have in the course discussion boards.
Do I need to know stochastic calculus?
Absolutely not! Unless you're planning on developing a new options pricing strategy for 3X leveraged ETFs - stochastic calculus is not necessary for implementation, but of course it could help you understand some of the concepts at a deeper level.
Is this a replacement for a PhD or an MFE?
Of course not! There are certainly some quant jobs which will require these advanced degrees, but Wall Street and top hedge funds also consistently hire engineers, data scientists, physicists, and others who have a good background in technology and/or finance. The best possible candidate for this course will have a finance or tech background, and this course will help you to build a portfolio and hone your skills to apply directly to quantitative finance. Those without that background can still use this course to help you land entry level finance, tech, or analytics jobs at top banks, and differentiate yourself from the crowd.
Why is [cool topic] not in the curriculum?
We might already be working on adding it. We are continuously updating this course, and we're even considering hiring other teachers to help out. If you're looking for a topic that's not currently in our curriculum, or you're wanting to help out with the course, send us a message!
Other Questions?

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