Time Travel

Mike Schilli uses a Go program to check whether a strategy for trading stocks is making gains or losses on the basis of historical price data.

- Mike Schilli

People say that you’re always smarter with the benefit of hindsight; of course, this also applies to stock market trading. Based on the ups and downs in the historical performance of a stock, it seems as clear as the light of day when an investor should have bought or sold stocks in order to leverage upswings and reap huge profits.

It goes without saying that it is infinitely more difficult to speculate successfully with stocks whose price development is still unknown. Chemistry wizard Niels Bohr once quipped that forecasts are generally difficult, especially those concerning the future.

Random Fools

I recently stumbled across a book titled Fooled by Randomness [1] and read about a theory stating that most successful stock market speculators were simply lucky. This may sound unlikely to the average person, but it does seem plausible given the tiny proportion of successful speculators. Be that as it may, one section of the book made me sit up and take notice. In this section, author Nassim Nicholas Taleb mentions that he had commissioned a software company to write a “backtester,” a program that is familiar with the historical price data of interesting stocks and that checks trading strategies packaged into algorithms to see whether the strategies would have succeeded in a historical context.

How difficult could it be to write something like this in Go? For some sample data, I’ll take the price performance of Netflix stock (NASDAQ: NFLX) over the past two years (Figure 1). After a huge price slump from $600 (January 2022) to $180 (April 2022), Netflix stock slowly came back and as of recently has fully recovered.

Strategy or Random Walk