Show Notes

[00:02:44] – Changes in data science through the lens of Michael’s career

[00:05:17] – The basic overview of using data and machine learning to create an edge

[00:06:58] – How the state of business is more than just a single data point

[00:07:53] – How you know when you’ve pulled a real signal from the noise of data

[00:10:49] – The advantages that data provides

[00:13:01] – Is there still an edge in decaying data

[00:15:34] – Building data that would predict stock prices

[00:19:43] – Prospectors vs miners in data mining

[00:22:18] – Knowing when your prospectors are on to truth

[00:27:09] – Understanding machine learning

[00:30:10] – Defining partition

[00:32:17] – Applying the parameters of selection process to stocks

[00:36:05] – What’s the first step people could take to use data and machine learning to improve their investment process

[00:38:54] – Building a sustainable advantage within data science

[00:41:35] – Predicting the uncapped positive vs what’s seemingly easier, eliminating the negative

[00:43:58] – How do we know to stop using a signal

[00:46:22] – The importance of asking the right question

[00:47:09] – Categories of objective functions that are interesting to measure data against

[00:48:37] – Most exciting things he’s found with data

[00:51:17] – What investors, individual or firms, has impressed him most with their use of data

[00:52:17] – Will everyone eventually shift to being data-informed or data-driven

[00:55:33] – Wall Street’s use of data vs other industries

[00:57:48] – Why everyone should know how to code

[00:58:52] – Kindest thing anyone has done for Michael