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Statistical Analysis and Quantitative Finance in Bitcoin Trading

June 27, 2013 at 19:53 by BitcoinNews

Move over, Nate Silver. Bitcoin now has its own statistics guru, Noah Silverman, who provided a brief talk on the “Statistical Analysis of Bitcoin Trading Markets” at the Bitcoin 2013 Conference in May. In his talk, Dr. Silverman conveys his excitement in the wide and free availability of market data, such as tick-by-tick historical data from Mt. Gox.

Applying quantitative financial formulas to the data, he finds that timeframes below 24 hours are particularly predictable, based on past historical data, for a quant trader. Above 24 hours, the market already appears to be efficient, with no expected edge in the random walk.

Additionally, Dr. Silverman addresses the problem of the valuing an asset without cashflows or an interest rate, an asset which trades purely on traders’ expectations of value, such as expecting value to increase along with an increasing “difficulty factor” and increased hash rate. He analyzes the latter question on his blog post here:

His full presentation may be viewed on Youtube here: v=3l03tgnC59I

And a full copy of his slides are available for download here: wpdmact=process&did=MS5ob3RsaW5r

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