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

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AN - SCOPUS:80055017442

SN - 1539-3755

VL - 84

JO - Physical Review E

JF - Physical Review E

IS - 4

M1 - 046112

ER -