37 research outputs found
Institutional Investors and Stock Market Volatility
We present a theory of excess stock market volatility, in which market movements are due to trades by very large institutional investors in relatively illiquid markets. Such trades generate significant spikes in returns and volume, even in the absence of important news about fundamentals. We derive the optimal trading behavior of these investors, which allows us to provide a unified explanation for apparently disconnected empirical regularities in returns, trading volume and investor size.
Quantifying Stock Price Response to Demand Fluctuations
We address the question of how stock prices respond to changes in demand. We
quantify the relations between price change over a time interval
and two different measures of demand fluctuations: (a) , defined as the
difference between the number of buyer-initiated and seller-initiated trades,
and (b) , defined as the difference in number of shares traded in buyer
and seller initiated trades. We find that the conditional expectations and of price change for a given or
are both concave. We find that large price fluctuations occur when demand is
very small --- a fact which is reminiscent of large fluctuations that occur at
critical points in spin systems, where the divergent nature of the response
function leads to large fluctuations.Comment: 4 pages (multicol fomat, revtex
Economic Fluctuations and Diffusion
Stock price changes occur through transactions, just as diffusion in physical
systems occurs through molecular collisions. We systematically explore this
analogy and quantify the relation between trading activity - measured by the
number of transactions - and the price change ,
for a given stock, over a time interval . To this end, we
analyze a database documenting every transaction for 1000 US stocks over the
two-year period 1994-1995. We find that price movements are equivalent to a
complex variant of diffusion, where the diffusion coefficient fluctuates
drastically in time. We relate the analog of the diffusion coefficient to two
microscopic quantities: (i) the number of transactions in
, which is the analog of the number of collisions and (ii) the local
variance of the price changes for all transactions in , which is the analog of the local mean square displacement between
collisions. We study the distributions of both and , and find that they display power-law tails. Further, we find that
displays long-range power-law correlations in time, whereas
does not. Our results are consistent with the interpretation
that the pronounced tails of the distribution of w_{\Delta t}|
G_{\Delta t} |N_{\Delta t}$.Comment: RevTex 2 column format. 6 pages, 36 references, 15 eps figure
Scaling of the distribution of price fluctuations of individual companies
We present a phenomenological study of stock price fluctuations of individual
companies. We systematically analyze two different databases covering
securities from the three major US stock markets: (a) the New York Stock
Exchange, (b) the American Stock Exchange, and (c) the National Association of
Securities Dealers Automated Quotation stock market. Specifically, we consider
(i) the trades and quotes database, for which we analyze 40 million records for
1000 US companies for the 2-year period 1994--95, and (ii) the Center for
Research and Security Prices database, for which we analyze 35 million daily
records for approximately 16,000 companies in the 35-year period 1962--96. We
study the probability distribution of returns over varying time scales , where varies by a factor of ---from 5 min up to
4 years. For time scales from 5~min up to approximately 16~days, we
find that the tails of the distributions can be well described by a power-law
decay, characterized by an exponent ---well outside the
stable L\'evy regime . For time scales days, we observe results consistent with a slow
convergence to Gaussian behavior. We also analyze the role of cross
correlations between the returns of different companies and relate these
correlations to the distribution of returns for market indices.Comment: 10pages 2 column format with 11 eps figures. LaTeX file requiring
epsf, multicol,revtex. Submitted to PR