Prices seem random in fluctuations unless you are Tesla 😉
🛠 The Tools To Predict
Whether it be the hedge fund managers or Movie Studio Execs trying to predict and make a bet on a film’s likely success, data seems to suggest that ‘experts’ aren’t generally very good at predictions. In most attempts of predicting what will happen, with streaks of successes, the human guesses are not too different to statistical estimates of a stochastic process.
A larger amount of data and a new array of techniques plus technology may make us better at prediction. Cliodynamics and applying machine learning to large datasets (similar to DeepMind’s success with AlphaFold in protein folding) may of course change this.
We will cover in more depth next week, on certain techniques and tools that can be used for more data predictive models.
🎯 Predictive Hits & Misses.
With Tesla’s soaring stock prices and investors following the thesis of Tesla being more of a tech company than car company, we can look back into past predictions. The cheery GM Motorama Exhibit of 1956, shows the Firebird ‘self driving’ (“safe, cool and comfortable”) car as being coordinated with control towers (like airport terminal) and running on magnetic car strip roads.
The GM ad reflected the fascination of the 1900s with aviation and automation. Cars were influenced by turbines. It was imagined that in the 2000s, automobiles would be replaced by flying contraptions.
One leading German chocolate company, Hildebrands, made a series of commemorative postcodes and speculated that people would take to the skies. They predicted that people would travel by personal airships and gliders, that buildings would be movable (aka Howl’s moving castle) through trains, and that cities would be encased in glass to be protected from the weather elements.