Applications of Information Cascades to Markets
https://pdfs.semanticscholar.org/fd94/c12a652da5f8355529f4a372127cfe266218.pdf
As is evident intuitively, herd thinking and information cascades are applicable to the stock market and other financial institutions. What causes market volatility is the unpredictability of the threshold, meaning the difficulty in measuring investors trust in the market at a certain time. This dynamic system is rather a system of dependencies where each consumer has a series of factors that they use to estimate what decision to make. A less involved investor would possibly wait till the major media outlets report significant changes and act accordingly, whereas an experienced investor may look at other external factors to predict a trend beforehand. Since there is so much variability in how people determine a market trend, it makes this scenario an information cascade, but one that is hard to quantify.
This decision making process is essentially built in two parts. One is more experienced or influential players in the market acting on external factors or advanced levels of experience predicting the market to make a decision. The trust the average investor has in these big players in the market would then be the cause for them to follow whatever action they set a precedent for. What makes this interesting is when people quantitatively set selling points for their stocks, which is automated buying/selling once the stock passes a certain threshold. This is essentially the buyer setting a predetermined point at which they are going to take action, and saying that regardless of what actually caused the price fluctuation, they trust the change in price enough for that to be their threshold for the information cascade. This is a very interesting concept that causes us to question whether this is valid investing strategy or not.