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
Dakota is one of the top ranked online instructors teaching financial analytics, R, and Python programming to thousands of students around the world.
He currently works as the Chief Data Scientist at a venture debt company, focusing on building analytical models for asset-heavy companies and decision-making infrastructure for automated loan processes.
Dakota also worked as a Quantitative Analyst at an AI startup called Yewno, where he built complex signals and factors on global securities, which were sold to some of the most sophisticated hedge funds in the world.
Dakota has a Master's in Financial Analytics, and did his undergrad in Quantitative Finance at the Stevens Institute of Technology, where his work included research on risk averse two-stage stochastic programming problems for portfolio optimization.
Frequently Asked Questions
Regardless, most quants can program in multiple languages. Once you learn how to apply quantitative concepts to make investment decisions, you can pick the best language for the job. Many financial institutions have entire teams dedicated to taking models from one language to another for deployment in their specific languages. In fact, some of these companies even write their own programming languages!