基于DFA的我国股票市场标度特性研究

将消除趋势波动分析法(DFA)应用于我国沪深两市不同时间标度收盘指数的对数收益率序列,全面分析了我国股市的标度特性.发现标度指数随着考察时间的长短,即数据个数的不同而不同,但从长期来看,两市波动都存在持久性特征,而且收益率的绝对值序列和平方值序列的持久性更明显;在相同时间范围内,不同时间标度序列的标度指数相差不大,存在标度不变性;小标度时间序列存在多重分形特征.这些结果说明我国股票市场存在复杂的非线性动力学特性.     

Analysis of Individual High-Frequency Traders’ Buy–Sell Order Strategy Based on Multivariate Hawkes Process

Traders who instantly react to changes in the financial market and place orders in milliseconds are called high-frequency traders (HFTs). HFTs have recently become more prevalent and attracting attention in the study of market microstructures. In this study, we used data to track the order history of individual HFTs in the USD/JPY forex market to reveal how individual HFTs interact with the order book and what strategies they use to place their limit orders. Specifically, we introduced an 8-dimensional multivariate Hawkes process that included the excitations due to the occurrence of limit orders, cancel orders, and executions in the order book change, and performed maximum likelihood estimations of the limit order processes for 134 HFTs. As a result, we found that the limit order generation processes of 104 of the 134 HFTs were modeled by a multivariate Hawkes process. In this analysis of the EBS market, the HFTs whose strategies were modeled by the Hawkes process were categorized into three groups according to their excitation mechanisms: (1) those excited by executions; (2) those that were excited by the occurrences or cancellations of limit orders; and (3) those that were excited by their own orders.     

Three Decades in Econophysics—From Microscopic Modelling to Macroscopic Complexity and Back

We explore recent contributions to research in Econophysics, switching between Macroscopic complexity and microscopic modelling, showing how each leads to the other and detailing the everyday applicability of both approaches and the tools they help develop. Over the past decades, the world underwent several major crises, leading to significant increase in interdependence and, thus, complexity. We show here that from the perspective of network science, these processes become more understandable and, to some extent, also controllable.     

Volatility return intervals analysis of the Japanese market

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold q for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval τ and its mean 〈τ〉. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.     

Trading by Quantum Rules: Quantum Anthropic Principle

This is a short review of the background and recent development in quantum game theory and its possible application in economics and finance. The intersection of science and society is discussed and Quantum Anthropic Principle is put forward. The review is addressed to nonspecialists.     

Endogenous and exogenous dynamics in the fluctuations of capital fluxes

A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is carried out on the Chinese stock market using mean-variance analysis, fluctuation analysis, and their generalizations to higher orders. Non-universal dynamics have been found not only in the scaling exponent α, which is different from the universal values 1/2 and 1, but also in the distributions of the ratio η= σ^exo / σ^endo of individual stocks. Both the scaling exponent α of fluctuations and the Hurst exponent H_i increase in logarithmic form with the time scale Δt and the mean traded value per minute 〈f_i 〉, respectively. We find that the scaling exponent α^endo of the endogenous fluctuations is independent of the time scale. Multiscaling and multifractal features are observed in the data as well. However, the inhomogeneous impact model is not verified.     

一类分数阶混沌金融系统的复杂性演化研究

物理学理论与方法在经济与金融领域中的成功应用催生了一个新的科学分支——经济物理学(econophysics).分数阶微积分系统的复杂动力学现象受到了越来越多学者的关注.本文定性地分析一类分数阶混沌金融系统的均衡解的稳定性及Hopf分岔发生的条件,并运用亚当斯-巴什福斯-莫尔顿预估-校正的有限差分法,通过分岔图、相图和时间序列图对该系统的复杂性演化行为进行仿真研究. 关键词： 经济物理学 分数阶微分方程 金融模型 混沌     

经济研究中的物理学

当前的金融危机再次表明,传统经济学作为一门学科缺乏解释力和预测力.造成这个令人失望的状况的根本原因是由于经济学家没有按照科学的范式来发展这个学科.经济学的现状吸引了一群物理学家进入这个学科并形成了一个新的交叉学科——经济物理学,人们期望它在促进经济学科学化的进程中起决定性作用.文章首先简要介绍了经济学的主要内容,说明经济学理论是建立在理性和均衡假定基础之上的;接着论述了为什么经济学还不是一门科学,指出经济学研究不是基于逻辑实证主义原则来开展的;文章还分析了物理学家是如何研究经济问题的,介绍了经济物理学的主要研究内容和研究方法;文章最后提出经济学范式的转变必须从观察和实验出发,经济学理论必须建立在一个合理设计的量纲体系和对实际经济运行过程的正确理解基础之上.     

Small scale behavior of financial data

A new approach is presented to describe the change in the statistics of the log return distribution of financial data as a function of the timescale. To this purpose a measure is introduced, which quantifies the distance of a considered distribution to a reference distribution. The existence of a small timescale regime is demonstrated, which exhibits different properties compared to the normal timescale regime for timescales larger than one minute. This regime seems to be universal for individual stocks. It is shown that the existence of this small timescale regime is not dependent on the special choice of the distance measure or the reference distribution. These findings have important implications for risk analysis, in particular for the probability of extreme events.     

Open dynamic behaviour of financial markets

Open dynamic behaviour of financial markets with internal interactions between agents and with external “fields” from other systems are investigated using the approach of Grossman and Stiglitz for inefficient markets, and Keynes for interference of the market using physics of finance (referred to hereafter as phynance). The simulation results indicate that the NYSE data analyzed in Plerou, V. et al., Nature 421, 130 (2003) can be fitted by an equation of order parameter Φ and local deviation R of type: -(R+0.03) Φ+ 0.6 Φ³ + 0.02 = 0, which is shown to be in remarkable agreement with Plerou's data.