Bitcoins: Information Cascades and Herding
December 15th, 2017, Bitcoin reached its all time high at $19,650. The price of one bitcoin was $7,777 a month before the peak and $1793 half a year before. Bitcoin as an asset, along with other cryptocurrencies generated waves of media and public attention.
As shown in the graph above, the price movement of Bitcoin is characterized by repeating boom-bust cycles. I’d like to think that part of the cause for this extreme and unprecedented boom-bust cycle is a lack of information, leading to Information Cascades and Herding.
Bitcoin as a new asset class lacks definitive theoretical framework for analyzing, conducting valuations, or using any kinda of fundamentals. Globally, Bitcoin prices are largely based on volatility and momentum at the start of each boom-bust cycle. In other words, peaks are usually a result of price movements at the beginning of each peak, leading to exponentially more investors buying in.
In Networks terms, since there is a lack of fundamentals and information on valuing bitcoins, investors and people resort to Information Cascades. As demonstrated in class, investors can observe what other investors traded, but don’t have access to private information such as why they made the trade to buy Bitcoin. Since there is limited information, they make a judgement based on other people’s judgement, ignoring their own valuations, resulting in the Herding effect.
Link: https://blogs.lse.ac.uk/businessreview/2019/10/07/bitcoin-ethereum-and-ripple-a-fractal-and-wavelet-analysis/