基于MF-DFA的中国股指期货价格的多重分形实证研究

本文通过应用多重分形谱分析法和多重分形消除趋势波动分析（MF-DFA）法,研究了新产生的中国股指期货市场的多重分形性。通过对2942个股指期货最后十分钟结算价格的分析,我们发现中国股指期货的收益率具有长程相关性和多重分形性,期货价格波动并不能用单一的标度指数进行充分描述。进一步通过将原始序列和转换后的收益序列进行比较,转换过程包括重排以及相位随机化,我们发现导致中国股指期货市场多重分形性的两种不同成因。研究结果表明,虽然厚尾分布是造成多重分形性的一个方面,但长程相关性才是引起中国股指期货市场多重分形的主要原因。     

基于Lotka-Volterra模型的中国股票市场非线性特征—— 一个生态学的视角

股票市场是一个非线性的复杂动力系统,将生态学的多种群Lotka-Volterra竞争模型进行改进后引入到股票市场,通过系统仿真,模拟中国股市运行,得出了类似于股票市场运行的非线性特征,为研究股市复杂性提供了新思路。     

Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis

We divided the whole series of Shenzhen stock market into two sub-series at the criterion of the date of a reform and their scale behaviors are investigated using multifractal detrended fluctuation analysis (MF-DFA). Employing the method of rolling window, we find that Shenzhen stock market was becoming more and more efficient by analyzing the change of Hurst exponent and a new efficient measure, which is equal to multifractality degree sometimes. We also study the change of Hurst exponent and multifractality degree of volatility series. The results show that the volatility series still have significantly long-range dependence and multifractality indicating that some conventional models such as GARCH and EGARCH cannot be used to forecast the volatilities of Shenzhen stock market. At last, the abnormal phenomenon of multifractality degrees for return series is discussed. The results have very important implications for analyzing the influence of policies, especially under the environment of financial crisis.     

Evidences for a structural change in the oil market before a financial crisis: The flat horizon effect

There are growing evidences that the commodity bubble in the 2000s had a major impact in the 2007–08 financial crisis. A salient feature of this commodity bubble was the dramatic increasing in the correlation of indexed commodities with oil price following the financialisation of the oil market. In this paper we suggest that, besides the growing demand from emerging economies and the following inflow of money from speculative traders, the introduction of the electronic platform could have had an important and underestimated effect on the oil market. Our analysis of the spot and futures oil prices at the NYMEX based on the Generalized Hurst Exponent confirms that the period 2004–2007 is pivotal in the oil market and corroborates the hypothesis that a structural change occurred in both markets. The evident decrease in multifractality suggests a flattening of the time horizon in financial oil markets and the coexistence of long-termism and short-termism. This structural change could partially explain the observed increase of correlations between commodities and oil price.     

Unifractality and multifractality in the Italian stock market

Tests for random walk behaviour in the Italian stock market are presented, based on an investigation of the fractal properties of the log return series for the Mibtel index. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Critical values for the test statistics are generated using Monte Carlo simulations of random Gaussian innovations. Evidence is reported of multifractality, and the departure from random walk behaviour is statistically significant on standard criteria. The observed pattern is attributed primarily to fat tails in the return probability distribution, associated with volatility clustering in returns measured over various time scales.     

互联网货币基金的多重分形分析——以余额宝、理财通为例

本文以余额宝、理财通为互联网货币基金代表,选取两种货币基金2013-2020年的七日年化收益率数据为研究区间,运用多重分形分析方法研究了两种货币基金的对数日收益率序列的多标度行为及其之间的非线性动态关系。研究结果表明,余额宝与理财通两收益率序列均存在时变的多重分形特征。比较而言,理财通收益率序列的多重分形强度更大,而余额宝收益率序列的正持续性更强;在小波动下,两收益率序列均表现出强持续性;两种互联网货币基金之间的交互相关关系是正相关的,具有多重分形性。同时,讨论了新冠肺炎疫情对互联网货币基金收益率的影响,并针对当前新冠肺炎疫情形势,给出投资理财建议。     

Disentangling the impact of economic and health crises on financial markets

This paper explores the impact of different crises on the informational efficiency of financial assets. The study covers stock markets indices (ASX200, DAX30, EuroStoxx50, S&P500 and Nikkei), commodities (gold and oil) and volatility (VIX). The study analyzes, using a rolling window method, the long memory profile and the multifractality of the time series by means of the DFA and generalized Hurst exponents. This dynamic analysis is important as it uncovers the time-varying behavior of returns characteristics, affecting the investment decisions and trading strategies at different moments of time. The paper extends the current literature on informational efficiency, providing evidence of the distinct impact on the long memory and on the multifractality of the time series, depending on the nature of the crisis and the market. The results could be of interest for investors as well as for academics, regarding the hedging limits of the models during calm or turbulent times.     

Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence

This paper introduces a new method for measuring nonlinear predictability in financial price changes: the so-called intermittency coefficient, a parameter of the multifractal random walk model by Bacry et al. (2001). As the intermittency coefficient can quantify the degree of nonlinear deviation from a random walk, we employ its estimates from financial data as a proxy for the loss of financial market efficiency. In addition, we propose a new statistical test of the random walk hypothesis. In an empirical application using data from the largest currently existing market for tradable pollution permits, the European Union Emissions Trading Scheme (EU ETS), we show that the degree of efficiency of this market remains largely unchanged over the period of observation 2008–2019. This suggests that the market has reached a mature state: informational efficiency in Phase III remains at a level comparable to Phase II. What is more, the EU ETS is found to be more efficient than the US stock market. This result, surprising as such, is largely attributable to the lower exposure to global economic shocks of the EU ETS.