Do predictions destroy predictability? A study focusing on stock markets

Abstract

Abstract Predicting stock markets is a problem that has generated many answers. According to one group of responses, the divergence thesis, it is impossible to accomplish this since the prediction has a ‘bending effect’ that would cause the market to behave in a way that would permanently depart from what was predicted, i.e. the prediction would falsify itself. There are at least three types of impossibility: logical, theoretical and empirical. A second class of responses argues that despite the ‘bending effect’ of predictions, it is still feasible to predicting stock markets. These responses, the convergence thesis, contend that we can achieve it by demonstrating that there are fixed points or that the prediction and market behavior will eventually converge. I expand this line of reasoning by showing that the performativity makes it possible certain predictions by an alignment between the ‘ontic’ and the ‘epistemic’ state of the markets. In addition, I show that performativity enables us to explain how a prediction is produced, why it works initially and then why it fails (i.e. why its predictive power is destroyed).