scholarly journals An Extended Speculation Game for the Recovery of Hurst Exponent of Financial Time Series

2020 ◽  
Vol 16 (02) ◽  
pp. 319-325
Author(s):  
Kei Katahira ◽  
Yu Chen
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
Financial Time Series ◽  
Price Change ◽  
Market Price ◽  
Agent Based ◽  
Financial Time ◽  
Real Market ◽  
Initial Price ◽  
Perturbative Part

The speculation game is an agent-based toy model to investigate the dynamics of the financial market. Our model has achieved the reproduction of 10 of the well-known stylized facts for financial time series. However, there is also a divergence from the behavior of real market. The market price of the model tends to be anti-persistent to the initial price, resulting in the quite small value of Hurst exponent of price change. To overcome this problem, we extend the speculation game by introducing a perturbative part to the price change with the consideration of other effects besides pure speculative behaviors.

scholarly journals DIFFUSION AND AGGREGATION IN AN AGENT BASED MODEL OF STOCK MARKET FLUCTUATIONS

2000 ◽  
Vol 11 (05) ◽  
pp. 865-879 ◽  
Author(s):  
FILIPPO CASTIGLIONE
Keyword(s):  
Time Series ◽  
Present Model ◽  
Financial Time Series ◽  
Market Price ◽  
Agent Based Model ◽  
Information Structures ◽  
Spatial Mobility ◽  
Dynamic Interactions ◽  
Agent Based ◽  
Financial Time

We describe a new model to simulate the dynamic interactions between market price and the decisions of two different kind of traders. They possess spatial mobility allowing to group together to form coalitions. Each coalition follows a strategy chosen from a proportional voting "dominated" by a leader's decision. The interplay of both kind of agents gives rise to complex price dynamics that is consistent with the main stylized facts of financial time series. The present model incorporates many features of other known models and is meant to be the first step toward the construction of an agent-based model that uses more realistic markets rules, strategies, and information structures.

ESTIMATION OF HURST EXPONENT FOR THE FINANCIAL TIME SERIES

2009 ◽  
Author(s):  
J. Kumar ◽  
P. Manchanda ◽  
A. H. Siddiqi ◽  
M. Brokate ◽  
A. K. Gupta
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
Financial Time Series ◽  
Financial Time

Fluctuation complexity of agent-based financial time series model by stochastic Potts system

2015 ◽  
Vol 26 (11) ◽  
pp. 1550123 ◽  
Author(s):  
Weijia Hong ◽  
Jun Wang
Keyword(s):  
Time Series ◽  
Dynamic System ◽  
Financial Time Series ◽  
Composite Index ◽  
Time Series Model ◽  
Agent Based ◽  
Financial Time ◽  
System A ◽  
Challenging Tasks ◽  
Financial Research

Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.

Hurst exponent analysis of financial time series

2001 ◽  
Vol 5 (4) ◽  
pp. 269-272 ◽  
Author(s):  
Hong-wei SANG ◽  
Tian Ma ◽  
Shuo-zhong Wang
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
Financial Time Series ◽  
Financial Time
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