Simple measure of similarity for the market graph construction

A simple measure of similarity for the construction of the market graph is proposed. The measure is based on the probability of the coincidence of the signs of the stock returns. This measure is robust, has a simple interpretation, is easy to calculate and can be used as measure of similarity between any number of random variables. For the case of pairwise similarity the connection of this measure with the sign correlation of Fechner is noted. The properties of the proposed measure of pairwise similarity in comparison with the classic Pearson correlation are studied. The simple measure of pairwise similarity is applied (in parallel with the classic correlation) for the study of Russian and Swedish market graphs. The new measure of similarity for more than two random variables is introduced and applied to the additional deeper analysis of Russian and Swedish markets. Some interesting phenomena for the cliques and independent sets of the obtained market graphs are observed.     

基于成交量分解模型的改进VWAP策略

传统VWAP(交易量加权平均价格)策略通过拆分大额委托订单,跟踪市场成交均价,达到最小化冲击成本的目的,而准确预测成交量日内分布是运用VWAP策略的关键。通过详细考察现有的改进VWAP策略中成交量预测模型的建模方式和预测结果,发现由于无法分离成交量日内周期结构,现有模型样本依赖性较大且难以适用于多数股票。因此,本文从个股与市场成交量变化趋势的关系角度出发,推导个股成交量与市场趋势的关系,通过构造个股成交量关于市场因素的因子载荷,将日内成交量分解为市场共同部分和个股特殊部分,预测成交量日内分布并构建动态VWAP策略。实证结果表明新的成交量分解模型可以有效分离个股的成交量日内周期结构,在此基础上构造的改进VWAP策略不仅具有较为广泛的适用性,且跟踪误差减少幅度比现阶段同类型的改进VWAP策略更大,能更好的降低市场冲击成本。     

金融系统的非线性分析:交易量对股价波动的非线性影响

如何研究股价波动和成交量之间的关系一直是金融系统研究中感兴趣的话题.Lamoureux 和 Lastrapes 认为选择日交易量度量每天流入市场的信息量是合理的,但他们假定交易量对波动率的影响是线性的.提出部分非线性GARCH模型分析交易量对股票市场波动率的影响,基于GARCH模型局部线性化非参数似然估计方法,对中国证券市场股票价格和交易量数据进行实证研究.结果表明,交易量对股价波动的影响具有显著的非线性性.     

NP-hardness of the recognition of coordinated graphs

A graph G is coordinated if the minimum number of colors that can be assigned to the cliques of H in such a way that no two cliques with non-empty intersection receive the same color is equal to the maximum number of cliques of H with a common vertex, for every induced subgraph H of G. In previous works, polynomial time algorithms were found for recognizing coordinated graphs within some classes of graphs. In this paper we prove that the recognition problem for coordinated graphs is NP-hard, and it is NP-complete even when restricted to the class of {gem, C ₄, odd hole}-free graphs with maximum degree four, maximum clique size three and at most three cliques sharing a common vertex. F.J. Soulignac is partially supported by UBACyT Grant X184, Argentina and CNPq under PROSUL project Proc. 490333/2004-4, Brazil.     

Computational study of the US stock market evolution: a rank correlation-based network model

This paper presents a computational study of global characteristics of the US stock market using a network-based model referred to as the market graph. The market graph reflects similarity patterns between stock return fluctuations via linking pairs of stocks that exhibit “coordinated” behavior over a specified period of time. We utilized Spearman rank correlation as a measure of similarity between stocks and considered the evolution of the market graph over the recent decade between 2001–2011. The observed market graph characteristics reveal interesting trends in the stock market over time, as well as allow one to use this model to identify cohesive clusters of stocks in the market.     

基于CARR模型的交易量与股价波动性动态关系的研究

股市交易量与股价变化的关系就一直是学术界与实务界所共同关心的主题。基于Chou(2005)提出的CARR模型对两者的动态关系问题进行了研究。首先分析了作为量价关系理论基础的混合分布假说理论在CARR模型中的适川性,进而基于混合分布假说理论对我国上证综合指数、深证成份指数以及随机抽取的十只个股进行了量价关系的实证检验。研究发现:混合分布假说理论同样适用于CARR模型,这证实了股价波动性的CARR效应的存在。实证的结果也证实了CARR模型无论是对于股票指数还是单只股票交易量都具有了良好的解释作用。因此,CARR模型与GARCH模型相比,在交易量与股价波动关系动态关系的研究领域可以得到更为稳健的结果。     

复杂网络视角下的我国股票之间信息溢出研究

理解股票市场内部股票间的信息溢出规律,对于股票定价、投资组合以及风险防范具有重要的意义。将传统计量经济方法与复杂网络的建模分析方法相结合,从复杂网络的视角出发,实证研究了我国股票市场内股票间的信息溢出关系及其影响因素、个股信息溢出能力分布及其影响因素。研究发现,股票间较长期收益的相互影响要强于较短期收益;股票收益率相关性较强的股票间存在更显著的信息溢出;市场因素显著增强了股票间的信息溢出效应;股票间的信息溢出效应会随着市场行情的上涨(下跌)而增强(减弱);股票的信息溢出能力呈现尖峰、厚右尾的分布;股票成交金额对个股的信息溢出能力具有显著的正向影响。最后,最小生成树能快速而准确有效地揭示股票间信息溢出规律。     

Information-based multi-assets artificial stock market with heterogeneous agents

In this paper, an artificial stock market characterized by heterogeneous and informed agents is presented. The heterogeneous agents are seen as nodes of sparsely connected graphs. The agents trade risky assets and are characterized by sentiments, amount of cash and stocks owned. Agents share information and sentiments by means of interactions determined by graphs. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and supply curves. In this framework, the statistical properties of the univariate and multivariate process of prices and returns are studied. Importantly, concerning univariate price processes, the proposed model is able to reproduce unit root, volatility cluster and fat tails of returns. The multivariate price process exhibits both static and dynamic stylized facts, in particular the presence of static factors and common trends. Static factors are studied making reference to the cross-correlation between returns of different stocks, whereas the common trends are investigated considering the variance–covariance matrix of prices. The proposed approach allows to endogenously reproduce the multivariate stylized facts.     

The informational content of insider trading disclosures: empirical results for the Polish stock market

In this paper, we try to answer the question as to whether insider trading disclosures convey valuable information to market participants, valuable in the sense of the profitability of an investment strategy that faithfully mirrors insider behaviour. Our interest in this subject is limited to the case of announcements concerning insider transactions issued over a 6 year-period on the Warsaw Stock Exchange (WSE). Initially, we use event study methodology to check whether insider trading disclosures are accompanied by a performance of stock returns as well as trading volume. Two different models generating expected returns (expected volume) are employed to verify the robustness of our results. The first of these is the regime switching model, with the results then being recalculated by using a GARCH-type model which seem to be most useful for dealing with some of the inconvenient statistical properties of stock return and trading volume data. Afterwards, a technique based on the reference return strategies is used to examine whether or not outsiders who imitate insider behaviour are able to profit from it. The major findings are as follows: firstly, announcements about the sale of stocks by insiders convey no information to market participants. Secondly, a statistically significant market response to insider disclosures of purchases of stocks in their own company can be observed in the three days prior to the announcement release for both return as well as trading volume series, and finally, outsiders who purchased stocks previously bought by insiders experience negative returns whereas outsiders disposing of stocks previously sold by insiders earned a return of 8.57% over the 6 month-period.      

Test case generators and computational results for the maximum clique problem

In the last years many algorithms have been proposed for solving the maximum clique problem. Most of these algorithms have been tested on randomly generated graphs. In this paper we present different test problem generators that arise from a variety of practical applications, as well as graphs with known maximum cliques. In addition, we provide computational experience with two exact algorithms using the generated test problems.     

投资者过度反应与牛熊市波动非对称性

论文针对沪深股市牛熊市中所呈现出的波动非对称性的差异,从牛熊市中投资者对信息反应的差异角度予以解释。论文以非预期交易量变化率作为投资者对信息冲击反应的代理变量,研究显示投资者在牛市行情中的过度反应,是造成沪深股市牛市行情波动正向非对称性的重要原因。与此同时论文通过对比美国、香港和沪深股市上牛熊市波动非对称性差异,进一步验证沪深市场上不完善的市场机制加剧了投资者在牛市行情中的过度反应,进而导致牛市行情中的波动正向非对称性。     

中国股市大公司与小公司股票动态价格关系研究——以钢铁行业为例

从中国上海和深圳股票市场选择了钢铁股票22家,根据差别信息集理论,探究了该行业内股票价格的长期协动关系以及收益的领先—滞后关系,发现钢铁大公司股票与其小公司股票价格的长期协动关系仅存在于牛市阶段.在熊市阶段,大公司股票的收益对小公司股票收益存在信息领先趋势.并给出了实际操作建议.     

Two remarks on circular arc graphs

In our first remark we observe a property of circular arcs which is similar to the Helly property and is helpful in describing all maximal cliques in circular arc graphs (as well as allowing us to genralize a result of Tucker). Our main result is a new simple characterization of circular arc graphs of clique covering number two. These graphs play a crucial role in recognition algorithms for circular arc graphs, and have been characterized by several authors. Specifically, we show that a graph with clique covering number two is a circular arc graph if and only if its edges can be coloured by two colours so that no induced four-cycle contains two opposite edges of the same colour. Our proof of the characterization depends on the lexicographic method we have recently introduced. Both remarks could be useful in designing efficient algorithms for (maximum cliques in, respectively recognition of) circular arc graphs     

Algorithmic aspects of clique-transversal and clique-independent sets

A minimum clique-transversal set MCT(G) of a graph G=(V,E) is a set SV of minimum cardinality that meets all maximal cliques in G. A maximum clique-independent set MCI(G) of G is a set of maximum number of pairwise vertex-disjoint maximal cliques. We prove that the problem of finding an MCT(G) and an MCI(G) is NP-hard for cocomparability, planar, line and total graphs. As an interesting corollary we obtain that the problem of finding a minimum number of elements of a poset to meet all maximal antichains of the poset remains NP-hard even if the poset has height two, thereby generalizing a result of Duffas et al. (J. Combin. Theory Ser. A 58 (1991) 158–164). We present a polynomial algorithm for the above problems on Helly circular-arc graphs which is the first such algorithm for a class of graphs that is not clique-perfect. We also present polynomial algorithms for the weighted version of the clique-transversal problem on strongly chordal graphs, chordal graphs of bounded clique size, and cographs. The algorithms presented run in linear time for strongly chordal graphs and cographs. These mark the first attempts at the weighted version of the problem.     

基于双重加权网络的股票强相关性分析

为分析股票间的强相关性,合理构建投资组合,选择中国股市煤炭电力板块93支股票,以股票上市时间至2011年2月11日每日收盘价和成交量,建立双重加权网络模型.在模型中,顶点是股票,双重边分别由股票间的成交量相关和回报相关建立,边上的权就是相关系数值.研究结果表明,网络顶点度服从幂律分布,负幂指数δ值约为0.02;单网络顶点度呈现"翘翘板"特点,即一个单网络中度大的顶点在另一个单网络中度很小;网络的模块具有同源性,即模块中顶点来自同一板块;网络的最大生成树明显以板块形成树分枝;网络树EGO结构体现企业间存在的生产材料和业务供求关系.     

基于复杂网络的沪深300股票重要节点的评估和分析

利用复杂网络方法将股票之间的复杂关系抽象为网络,能够更好地掌握股票市场的整体和局部特性以及股票之间内在的联动关系,以沪深300数据为研究样本,通过相关系数构建网络,利用最佳阈值法对网络进行去噪,保留主要股票之间的相互影响.借鉴PageRank算法对社团网络进行重要节点的挖掘,从宏观和微观视角分析各行业股票在市场中的地位.研究发现整个沪深300市场中,采矿业、制造业和金融业是市场"大户",其股票与市场中的其他股票之间存在紧密联系;网络中的同类型股票存在聚集现象,且股票之间影响关系显著.     

股指极端波动下中国股市复杂网络结构及中心性分析

基于复杂网络理论,以2015年、2008年国内两次股灾为背景,分别构建股灾发生前、中、后的中国股市网络,通过度、度分布、平均路径长度等基本拓扑指标,分析中国股市网络特性及网络结构的变化,综合利用度中心性、介数中心性及接近度中心性,筛选出各时期网络中的核心股票、核心行业并分析其变化情况,基于网络特征向量中心性分析股市的系统性风险及变化情况,通过仿真实验分析股市网络的鲁棒性。研究表明:两次股灾背景下的中国股市复杂网络均具有小世界性和无标度性;与2008年国际金融危机相比,2015年国内股灾对中国股市的影响强度更大,且2015年中国股市对金融风险的弹性更大;股灾期间各行业版块具有明显的风险传染性,指出各行业板块对稳定股市、修复股指的作用;股指极端波动时,股灾的外生冲击会使股市的系统性风险加大,与2015年国内股灾时期相比,2008年国际金融危机时期的股市系统性风险更大;中国股市网络对随机攻击具有一定鲁棒性,但对蓄意攻击具有脆弱性,股灾的外生冲击会降低中国股市网络的鲁棒性。研究为把握股市极端波动风险下的市场结构特征、股市风险管理提供了参考。     

Pricing stock and bond derivatives with a multi-factor Gaussian model

The martingale approach to pricing contingent claims can be applied in a multiple state variable model. The idea is used to derive the prices of derivative securities (futures on stock and bond futures, options on stocks, bonds and futures) given a continuous time Gaussian multi-factor model of the returns of stocks and bonds. The bond market is similar to Langetieg's multi-factor model, which has closed-form solutions. This model is a generalization of Vasicek's model, where the term structure depends on state variables following correlated mean reverting processes. The stock market is affected by systematic and unsystematic risk.     

Partial characterizations of clique-perfect and coordinated graphs: Superclasses of triangle-free graphs

A graph G is clique-perfect if the cardinality of a maximum clique-independent set of H equals the cardinality of a minimum clique-transversal of H, for every induced subgraph H of G. A graph G is coordinated if the minimum number of colors that can be assigned to the cliques of H in such a way that no two cliques with non-empty intersection receive the same color equals the maximum number of cliques of H with a common vertex, for every induced subgraph H of G. Coordinated graphs are a subclass of perfect graphs. The complete lists of minimal forbidden induced subgraphs for the classes of clique-perfect and coordinated graphs are not known, but some partial characterizations have been obtained. In this paper, we characterize clique-perfect and coordinated graphs by minimal forbidden induced subgraphs when the graph is either paw-free or {gem, W₄, bull}-free, both superclasses of triangle-free graphs.     

The edge intersection graphs of paths in a tree

The class of edge intersection graphs of a collection of paths in a tree (EPT graphs) is investigated, where two paths edge intersect if they share an edge. The cliques of an EPT graph are characterized and shown to have strong Helly number 4. From this it is demonstrated that the problem of finding a maximum clique of an EPT graph can be solved in polynomial time. It is shown that the strong perfect graph conjecture holds for EPT graphs. Further complexity results follow from the observation that every line graph is an EPT graph. The class of EPT graphs is equivalent to the class of fundamental cycle graphs.