Abstract
Although supply and demand are perhaps the most fundamental concepts in economics, finding any general form for their behavior has proved to be elusive. Here we discuss our recent findings [1] on the price impact function empirically detected in the New York Stock Exchange (NYSE). Our study builds on earlier studies of how trading affects prices [2, 3, 4, 5, 6, 7, 8, 9, 10, 11]. In particular, we look at the short term response to a single trade. This is done by using huge amounts of data and by measuring the market activity in units of transactions rather than seconds, so that we can more naturally aggregate data for many different stocks. This allows us to find regularities in the response of prices to new orders that have previously been hidden by the extremely high noise levels that dominate financial prices. We study the 1000 largest stocks of the NYSE, from (1995–1998), and we find that, by appropriate averaging and rescaling, it is possible to collapse the price shift caused by a transaction onto a single curve [1]. In our study, we showed that the price shift grows slowly with the transaction size, with a power that is the order of 1/2 in the small volume limit and much more slowly in the large volume limit. These findings are observed across many stocks and for four different years. KeywordsCapitalization StockPrice ImpactOrder BookLarge Volume LimitTransaction SizeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call