As a result of reading this article, I am thinking about potential algorithmic trading applications. At this exploratory stage, I can only ask questions, and I cannot provide any answers. This is what I am thinking about:
• When sharks can’t find food, “they abandon Brownian motion...for what’s known as Lévy flight.” Since financial markets provide scarce abnormal return opportunities, their participants might be following a Lévy flight in their search for these returns. Do participants get tripped up (compounding poor returns) by getting bored and moving from one Lévy flight cluster to the next?
• Modeling the stock market as a Brownian motion with a growth rate and some gapping mechanisms works very well. Is duality between output and behavior at work here, or is it just that the sum of Lévy flights approximates the regular Brownian motion?
• Toward the end of a bear market with long opportunities littering the landscape, do participants revert to a Brownian motion mode? If so, can we measure this migration? If so, can we use it to predict the end of the bear market?
• How do we decode opportunity markers? Can we gain insight from the sharks’ ability to decode food markers? Are abilities irrelevant? If so, are we left to the mercy of a stochastic process? Can one develop the ability to observe humans the same way scientists have the ability to observe the sharks from outside the system? Could that lead to the mother of all money-making insight?
• During a financial bubble, are participants leaving the stochastic process method for a linear process when following the leading lemmings?
Help me think about this, okay?
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