TY - JOUR
T1 - Langevin modelling of high-frequency Hang-Seng index data
AU - Tang, Lei Han
N1 - Funding Information:
We wish to acknowledge useful discussions with J.-P. Bouchaud and E.S.C. Ching on the Langevin model. The work is supported in part by the Hong Kong Baptist University under grant FRG/99-00/II-53.
PY - 2003/6/1
Y1 - 2003/6/1
N2 - Accurate statistical characterization of financial time series, such as compound stock indices, foreign currency exchange rates, etc., is fundamental to investment risk management, pricing of derivative products and financial decision making. Traditionally, such data were analyzed and modeled from a purely statistics point of view, with little concern on the specifics of financial markets. Increasingly, however, attention has been paid to the underlying economic forces and the collective behavior of investors. Here we summarize a novel approach to the statistical modeling of a major stock index (the Hang Seng index). Based on mathematical results previously derived in the fluid turbulence literature, we show that a Langevin equation with a variable noise amplitude correctly reproduces the ubiquitous fat tails in the probability distribution of intra-day price moves. The form of the Langevin equation suggests that, despite the extremely complex nature of financial concerns and investment strategies at the individual's level, there exist simple universal rules governing the high-frequency price move in a stock market.
AB - Accurate statistical characterization of financial time series, such as compound stock indices, foreign currency exchange rates, etc., is fundamental to investment risk management, pricing of derivative products and financial decision making. Traditionally, such data were analyzed and modeled from a purely statistics point of view, with little concern on the specifics of financial markets. Increasingly, however, attention has been paid to the underlying economic forces and the collective behavior of investors. Here we summarize a novel approach to the statistical modeling of a major stock index (the Hang Seng index). Based on mathematical results previously derived in the fluid turbulence literature, we show that a Langevin equation with a variable noise amplitude correctly reproduces the ubiquitous fat tails in the probability distribution of intra-day price moves. The form of the Langevin equation suggests that, despite the extremely complex nature of financial concerns and investment strategies at the individual's level, there exist simple universal rules governing the high-frequency price move in a stock market.
KW - Langevin equation
KW - Non-Gaussian statistics
KW - Time series analysis
UR - http://www.scopus.com/inward/record.url?scp=0038237657&partnerID=8YFLogxK
U2 - 10.1016/S0378-4371(03)00034-7
DO - 10.1016/S0378-4371(03)00034-7
M3 - Conference article
AN - SCOPUS:0038237657
SN - 0378-4371
VL - 324
SP - 272
EP - 277
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
IS - 1-2
T2 - Proceedings of the International Econophysics Conference
Y2 - 29 August 2002 through 31 August 2002
ER -