A Starting Point: Distributed Capital
I’m doing more research on EquityBot —the project for my Impakt Works residency, which I just started a couple of days ago.
EquityBot is a stock-trading algorithm that explores the connections between collective emotions on social media and financial speculation. It will be presented at the Impakt Festival at the end of October.
It will also consist of a sculptural component (presented post-festival), which is the more experimental form.
Many of you are familiar with Paul Baran’s work on designing a distributed network, but many others may not be. He worked for the U.S. Air Force and determined that a central communications network would be vulnerable to attack, and suggested that the United States use a distributed network.
Interestingly, there is a widespread myth that the Internet, derived from APANET, was designed to withstand a nuclear attack using this model. This isn’t the case, just that the architects of the internet transmission protocol heard of Rand’s work and adapted it for packet use. Yet, the myth persists.
On a side note, perhaps military technology could be useful for the public good. If only we could declassify the technology, like Baran did.
The distributed network reminds me of a 3D polygon mesh I think this could be a good source of 3D data-visualization: Distributed Capital. I’ll research this more in the future.
But EquityBot isn’t about networks in the formal sense, it is a project about constructing a predictive model of stock changes based on the idea that Twitter sentiments correlate with fluctuations in stock prices.
Do I know there is a correlation? Not yet, but I think there is a good possibility. One of my reading sources, The Computational Beauty of Nature, sums up the value of simulated models in its introduction. The predictive model might fail in its results but it will likely reveal a greater truth in the economic system that it is trying to predict. Thus, knowing the uncertainty ahead of time will provide a sense of certainty. EquityBot may not “work” but then again, it may.
My source of dissent is the excellent book, The Signal and The Noise: Why So Many Predictions Fail — but Some Don’t by Nate Silver. After reading this, last summer, I was convinced that any predictive analysis would be simply be noise. I was disheartened and halted the EquityBot project (previously called Grantbot) for many months.
However, now I’m not so sure. It seems likely that people’s moods would affect financial decisions, which in turn would affect stock prices. With studies such as this one by Vagelis Hristidis, which found some correlation to Twitter chatter and stock, I think there is something to this, which is why I’ve revisited the EquityBot project.
I’ll follow the Buddhist maxim with this project and embrace its uncertainty.
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