Some comments on Hurst exponent and the long memory processes on capital markets

The analysis of long memory processes in capital markets has been one of the topics in finance, since the existence of the market memory could implicate the rejection of an efficient market hypothesis. The study of these processes in finance is realized through Hurst exponent and the most classical method applied is R/S analysis. In this paper we will discuss the efficiency of this methodology as well as some of its more important modifications to detect the long memory. We also propose the application of a classical geometrical method with short modifications and we compare both approaches.     

Use and misuse of some Hurst parameter estimators applied to stationary and non-stationary financial time series

The detection of long range dependence (LRD) is an important task in time series analysis. LRD is often summarized by the well-known Hurst parameter (or exponent) H∈[0,1], which can be estimated by a number of methods. Some of these techniques are designed to be applied to signals behaving as a stationary fractional Gaussian noise (fGn), whereas others imply that the analyzed time series behave as a non-stationary fractional Brownian motion (fBm). Moreover, some estimators do not yield the Hurst parameter but indexes related to H and ranging outside the unit interval. Therefore, the fGn or fBm nature of the studied time series has to be preliminarily analyzed before applying any estimation method, and the relationships between H and the indexes resulting from the analyses have to be taken into account to obtain coherent results. Since fGn-like series represent the increments of fBm-like processes and both the signals are characterized by the same H value by definition, estimators designed for fGn-like series can be applied to fBm-like sequences after preventive differentiation, and conversely estimators designed for fBm-like processes can be applied to fGn-like series after preventive integration. The signal characterization is particularly important when H is estimated on financial time series because the returns represent the first difference of price time series, which are often assumed to behave like self-affine sequences. The analysis of simulated fGn and fBm time series shows that all the considered methods yield comparable H values when properly applied. The reanalysis of several market price time series already studied in the literature points out that a correct application of the estimators (supported by a preventive signal classification) yields homogeneous H values allowing for a useful cross-validation of results reported in different works. Moreover, some conclusions reported in the literature about the anti-persistence of some financial series are shown to be incorrect because of the inappropriate application of the estimation methods.     

Market segmentation strategy in internet market

This paper presents a model to describe the competitive dynamics of web sites on the WWW market and analyze the stability of the model which is composed of one powerful site and two small sites. One of the most important results that emerge from this simple model is that strong competition among websites does not necessarily lead to the demise of the small website on the WWW market. From the stability analysis of the model, we obtain a series of conditions in which small sites can obtain competitive advantages by using the market segmentation strategy.     

Fluctuation scaling of quotation activities in the foreign exchange market

We study the scaling behavior of quotation activities for various currency pairs in the foreign exchange market. The components’ centrality is estimated from multiple time series and visualized as a currency pair network. The power-law relationship between a mean of quotation activity and its standard deviation for each currency pair is found. The scaling exponent α and the ratio between common and specific fluctuations η increase with the length of the observation time window . The result means that although for , the market dynamics are governed by specific processes, and at a longer time scale the common information flow becomes more important. We point out that quotation activities are not independently Poissonian for , and temporally or mutually correlated activities of quotations can happen even at this time scale. A stochastic model for the foreign exchange market based on a bipartite graph representation is proposed.     

Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis

The multifractal nature of WTI and Brent crude oil markets is studied employing the multifractal detrended fluctuation analysis. We find that two crude oil markets become more and more efficient for long-term and two Gulf Wars cannot change time scale behavior of crude oil return series. Considering long-term influence caused by Gulf Wars, we find such “turning windows” in generalized Hurst exponents obtained from three periods divided by two Gulf Wars so that WTI and Brent crude oil returns possess different properties above and below the windows respectively. Comparing with the results obtained from three periods we conclude that, before the First Gulf War, international crude oil markets possessed the highest multifractality degree, small-scope fluctuations presented the strongest persistence and large-scope fluctuations presented the strongest anti-persistence. We find that, for two Gulf Wars, the first one made a greater impact on international oil markets; for two markets, Brent was more influenced by Gulf Wars. In addition, we also verified that the multifractal structures of two markets’ indices are not only mainly attributed to the broad fat-tail distributions and persistence, but also affected by some other factors.     

The topology of the federal funds market

We explore the network topology of the federal funds market. This market is important for distributing liquidity throughout the financial system and for the implementation of monetary policy. The recent turmoil in global financial markets underscores its importance. We find that the network is sparse, exhibits the small-world phenomenon, and is disassortative. Centrality measures are useful predictors of the interest rate of a loan.     

A network model of the interbank market

This work introduces a network model of an interbank market based on interbank credit lending relationships. It generates some network features identified through empirical analysis. The critical issue to construct an interbank network is to decide the edges among banks, which is realized in this paper based on the interbank’s degree of trust. Through simulation analysis of the interbank network model, some typical structural features are identified in our interbank network, which are also proved to exist in real interbank networks. They are namely, a low clustering coefficient and a relatively short average path length, community structures, and a two-power-law distribution of out-degree and in-degree.     

一般均衡下基于产品市场和资本市场的单名CDS定价

次贷危机呼吁新的信用衍生品定价模型, 因此为存在产品市场和资本市场的经济结构建立一般均衡的单名CDS定价模型, 使用最优化求解一般均衡下的商品价格和CDS价格. 可以发现一般均衡的CDS定价具有资本市场和产品市场的因素, 这表示CDS的价格不再是由单纯的资本市场因素决定的, 而是由无风险利率、资本产出弹性、违约率、回收率同时决定的. 通过数量约束用模拟的方式研究多个均衡的动态变化, 发现违约风险的增加使得价格剧烈波动且市场交易萎缩. 在为以中国工商银行为参考资产的CDS定价过程中, 发现各种因素在不同的时期都可能成为定价的主要影响因素. 可以发现, 次贷危机的定价体系存在着信用调整问题和定价与实体经济脱节的问题. 可以认为, 一般均衡下基于产品市场和资本市场的单名CDS定价可以囊括多个市场的交叉影响, 为衍生品定价提供一个新的方向.     

非平稳市场中适应性在线投资组合策略设计与分析

考虑到股票市场的表现往往是非平稳的, 过去较长时间的股票价格对当前的投资决策影响较小, 因此基于近期股票价格数据设计在线投资组合策略. 首先, 将上一期的策略与固定长度的股票价格近期数据对应的最优定常再调整策略加权平均, 设计了一个在线投资组合策略. 其次, 进一步采用在线学习的方法选择加权平均的权重, 设计了一个适应性的在线投资组合策略. 利用实际股票价格数据对构造的策略进行数值分析, 结果表明与基准策略和已有的在线投资组合策略相比, 设计的策略具有较好的性能.     

美国光伏市场调研及前景研究

为加强对美国光伏市场情况的研究,对美国太阳能资源、光伏装机、光伏系统价格、光伏相关政策等资料进行了收集整理,并对美国光伏行业的发展前景进行了分析。参考美国能源部、太阳能学会等提供的光伏行业相关资料,对美国光伏行业概况进行概括梳理;通过查找光伏政策相关资料并与美国投资银行、光伏项目开发商进行座谈,对影响美国光伏行业的投资信用补贴、可再生能源配额标准等政策进行介绍;最后,结合美国太阳能学会研究成果,对美国光伏行业的发展前景提出预期。在美国光伏补贴政策的影响下,美国光伏装机截止2016年已超过40 000 kW,世界排名第四位,预计2018年光伏装机增长将放缓,2019-2022年光伏装机增长将逐步加快。