Day 4 of Our AI Course for Investors

Start adding science to "art of investing"

Here is another session of our AI course for busy investment professionals. Also check out the previous post if you like.

We will take a break from Berkeley’s COMPSCI 188 after this post. I’d like to move on and broaden the scope to data science, machine learning, deep learning, generative AI and etc. Since our launch, companies like Microsoft and Google also started offering AI trainings, which are not customized for investors but worth checking out…

As we go deeper into COMSCI 188, the math and the algorithms become more complicated. Honestly, I got less than 50% of the materials below. You should still go through the following if you can. No need to understand everything. The goal is to develop an appreciation for AI as a rigorous science, and value the intensity of the scientific research behind all the amazing AI tools today.

In equity research, the projected 3-5 year growth rate is an important yet mythical number. It can be as random as a lottery. I don’t think people do much thinking - not to mention any rigorous research - to arrive at this number. Many would choose the first figure that came to their mind. “15-20%”, they say, “And that’s good enough”. Qi Wang

With the advent of modern AI, I hope we can inject more scientific spirit into our investment analysis. This is one of the changes that we need to make within ourselves.

“The man who is striving to solve a problem defined by existing knowledge and technique is not, however, just looking around. He knows what he wants to achieve, and he designs his instruments and directs his thoughts accordingly.” Thomas S. Kuhn, The Structure of Scientific Revolutions

Key Takeaways