Experimentation for Engineers: A Trader’s Perspective
The basic principle of successful investing says that you need to figure out the real value of something and then pay a lot less. So what is the value of things?
The fundamental theory of finance says that the cost of any financial investment depends on what the amount of discounted cash flow from this investment will be since as the famous French philosopher Voltaire put it — “Paper money eventually returns to its intrinsic value — zero.”
On the other hand, behavioral finance argues that for us, humans, psychology is more important than fundamentals, so a successful investor devotes more time to analyzing the behavior of other investors rather than studying the fundamental value of companies. The essence of these psychological factors is very well reflected in the expression of the ancient Roman author Publilius Syrus: “Every thing is worth what its purchaser will pay for it.”
Still, there are people who do not pay any particular attention to either fundamental or psychological factors. They simply devote their time to studying stock price charts following Napoleon’s principle that “a good sketch is better than a long speech.” In other words, these investors rely on technical analysis.
They justify this approach by arguing that, first, all information about a company (profit and dividend expectations, its prospects and outlook, etc.) is already reflected in its stock price. As a result, it can be extracted by studying company stock price charts. Second, they also rely on the principle that “history repeats itself” and prices tend to follow some trend. Why is this happening? Because under the impact of “herd mentality” people tend to join the prevailing trend. Third, access to fundamental information is not uniform and its dissemination occurs only gradually. Any important information regarding a company initially is absorbed by insiders who are followed by financial market professionals. Non-professional market participants are the last ones in this information dissemination line.
When I was writing my PhD thesis, I spent many sleepless nights wondering what was this debilitating error that was interfering with the proper functioning of my economic model programmed in GAMS.
And when I started working in the investment industry, I was coming to my work earlier to run my Excel regression models seeking to identify statistically significant patterns for various currency pairs.
I am sure that many traders who use technical analysis and algorithmic trading have been in this situation. Thus, they know very well what it means.
That is why for tech-savvy people it would be interesting and useful to check out David Sweet’s recently published Experimentation for Engineers (see the image above).
David has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram. He also teaches in the AI and Data Science master’s programs at Yeshiva University. So he knows this subject well, both as an academic and a practitioner.
After reading this book, hopefully, predicting the future will become somewhat easier!
P.S. If you would like to get a discount code, please let me know.
