TY - JOUR
T1 - Financial factor influence on scaling and memory of trading volume in stock market
AU - Li, Wei
AU - Wang, Fengzhong
AU - Havlin, Shlomo
AU - Stanley, H. Eugene
PY - 2011/10/24
Y1 - 2011/10/24
N2 - We study the daily trading volume volatility of 17 197 stocks in the US stock markets during the period 1989-2008 and analyze the time return intervals τ between volume volatilities above a given threshold q. For different thresholds q, the probability density function Pq(τ) scales with mean interval τ as Pq(τ)=τ-1f(τ/τ), and the tails of the scaling function can be well approximated by a power law f(x)∼x-γ. We also study the relation between the form of the distribution function Pq(τ) and several financial factors: stock lifetime, market capitalization, volume, and trading value. We find a systematic tendency of Pq(τ) associated with these factors, suggesting a multiscaling feature in the volume return intervals. We analyze the conditional probability Pq(τ|τ0) for τ following a certain interval τ0, and find that P q(τ|τ0) depends on τ0 such that immediately following a short (long) return interval a second short (long) return interval tends to occur. We also find indications that there is a long-term correlation in the daily volume volatility. We compare our results to those found earlier for price volatility.
AB - We study the daily trading volume volatility of 17 197 stocks in the US stock markets during the period 1989-2008 and analyze the time return intervals τ between volume volatilities above a given threshold q. For different thresholds q, the probability density function Pq(τ) scales with mean interval τ as Pq(τ)=τ-1f(τ/τ), and the tails of the scaling function can be well approximated by a power law f(x)∼x-γ. We also study the relation between the form of the distribution function Pq(τ) and several financial factors: stock lifetime, market capitalization, volume, and trading value. We find a systematic tendency of Pq(τ) associated with these factors, suggesting a multiscaling feature in the volume return intervals. We analyze the conditional probability Pq(τ|τ0) for τ following a certain interval τ0, and find that P q(τ|τ0) depends on τ0 such that immediately following a short (long) return interval a second short (long) return interval tends to occur. We also find indications that there is a long-term correlation in the daily volume volatility. We compare our results to those found earlier for price volatility.
UR - http://www.scopus.com/inward/record.url?scp=80055017442&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.84.046112
DO - 10.1103/PhysRevE.84.046112
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
AN - SCOPUS:80055017442
SN - 1539-3755
VL - 84
JO - Physical Review E
JF - Physical Review E
IS - 4
M1 - 046112
ER -