The geometry of relative arbitrage

Consider an equity market with n stocks. The vector of proportions of the total market capitalizations that belong to each stock is called the market weight. The market weight defines the market portfolio which is a buy-and-hold portfolio representing the performance of the entire stock market. Consider a function that assigns a portfolio vector to each possible value of the market weight, and we perform self-financing trading using this portfolio function. We study the problem of characterizing functions such that the resulting portfolio will outperform the market portfolio in the long run under the conditions of diversity and sufficient volatility. No other assumption on the future behavior of stock prices is made. We prove that the only solutions are functionally generated portfolios in the sense of Fernholz. A second characterization is given as the optimal maps of a remarkable optimal transport problem. Both characterizations follow from a novel property of portfolios called multiplicative cyclical monotonicity.     

全面质量管理与统计技术

本文指出了ISO90 0 0论证中存在的问题 ,并提出了相应的挽救措施 ,特别是在全面质量管理中更应该重视统计技术的应用     

MONOPOLY,POTENTIAL COMPETITION AND PRIVATE STOCK INFORMATION IN EXHAUSTIBLE RESOURCE MARKETS

ABSTRACT. This paper develops an exhaustible resource model with an incumbent monopolist that faces future potential entry of a single rival or backstop technology. The model is characterized by private stock information in the sense that firms do not know with certainty the size and/or quality of their rival's reserve stock. Results indicate that if such information is private, the strategic response of the monopolist to an entry threat is to extract reserves in the pre‐entry era at a rate faster than would a pure monopolist in an uncontested market, and thus could lead to an improvement in economic welfare relative to the situation where entry is restricted.     

The behavior of individual and aggregate stock prices

News about an individual stock normally has only a trivial impact on the aggregate economy. The news of the aggregate stock market, however, may have a significant impact on the prospects of the economy, and so has a large impact on the pricing kernel. This difference between the aggregate stock market and individual stocks is analyzed in a dynamic general equilibrium setting with incomplete information. The main findings are as follows. First, consistent with existing empirical evidence, the correlation between stock returns and earnings surprises is, on average, positive at the individual stock level and is lower or even negative at the aggregate level. Second, a stock’s return is less sensitive to its earnings surprises if the expected earnings growth of the stock is more pro-cyclical. Third, a decrease of information quality of a stock increases its risk premium if the stock accounts for a small fraction of the economy, but decreases its risk premium if the stock accounts for a large fraction.     

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.     

投资者情绪和市场利率对证券市场指数收益影响特点的动态刻画

本文基于2006年10月到2015年6月市场层面的投资者情绪和上证综指收益率,刻画了投资者情绪和市场利率对证券市场指数收益率的影响。首先,本文通过误差修正模型研究了短期层面投资者情绪对证券市场收益的影响特点,补充了以往在长期层面和整体收益水平上投资者情绪对市场收益影响的研究。由于市场层面的投资者情绪会受到宏观政策影响,之后本文将市场利率作为政策因素,通过分位数回归分析了不同市场收益水平下,市场利率和剔除了宏观政策因素的投资者情绪对市场收益的影响。研究结果表明:投资者情绪和证券市场收益之间的关系在短期层面上更为显著;当我国的证券市场环境处于“牛市”时,市场利率和投资者情绪均会对证券市场指数收益产生显著的影响,且随着市场收益水平的逐步上升,市场利率的反向作用和投资者情绪的正向作用均会逐渐加强。     

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。     

A new method for mean-variance portfolio optimization with cardinality constraints

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM) model, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model based on a reformulation as a Standard Quadratic Program, on a new lower bound that we establish, and on other recent theoretical and computational results for such problem. These results lead to an exact algorithm for solving the LAM model for small size problems. For larger problems, such algorithm can be relaxed to an efficient and accurate heuristic procedure that is able to find the optimal or the best-known solutions for problems based on some standard financial data sets that are used by several other authors. We also test our method on five new data sets involving real-world capital market indices from major stock markets. We compare our results with those of CPLEX and with those obtained with very recent heuristic approaches in order to illustrate the effectiveness of our method in terms of solution quality and of computation time. All our data sets and results are publicly available for use by other researchers.     

On the (R,s, Q) inventory model when demand is modelled as a compound Bernoulli process

In this paper we present an approximation method to compute the reorder point s in an (R, s, Q) inventory model with a service level restriction. Demand is modelled as a compound Bernoulli process, i.e., with a fixed probability there is positive demand during a time unit; otherwise demand is zero. The demand size and the replenishment leadtime are random variables. It is shown that this kind of modelling is especially suitable for intermittent demand. In this paper we will adapt a method presented by Dunsmuir and Snyder such that the undershoot is not neglected. The reason for this is that for compound demand processes the undershoot has a considerable impact on the performance levels, especially when the probability that demand is zero during the leadtime is high, which is the case when demand is lumpy. Furthermore, the adapted method is used to derive an expression for the expected average physical stock. The quality of both the reorder point and the expected average physical stock, calculated with the method presented in this paper, rum out to be excellent, as has been verified by simulation.     

Measuring the coupled risks: A copula-based CVaR model

Integrated risk management for financial institutions requires an approach for aggregating risk types (such as market and credit) whose distributional shapes vary considerably. The financial institutions often ignore risks’ coupling influence so as to underestimate the financial risks. We constructed a copula-based Conditional Value-at-Risk (CVaR) model for market and credit risks. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks, such as skewness and fat-tails while allowing for a rich dependence structure. Finally, the numerical simulation method is used to implement the model. Our results indicate that the coupled risks for the listed company’s stock maybe are undervalued if credit risk is ignored, especially for the listed company with bad credit quality.     

再论中国股票市场的弱有效性

本文利用检验鞅差序列的非参数统计量来检验中国股票市场的弱有效性问题,本文给出的方法不同于文献中已有的方法,实证分析表明本文使用的检验股票市场弱有效的方法比文献中的大多数方法更有效。实证结果显示,中国的股市在发展过程中,表现山渐进有效的态势;中国A股市场比B股市场更有效率:沪市比深市更趋于有效。文中的有些结论是以前的实证研究所没有的。另外,本文比较了中国股市和境外成熟股市之间有效性程度的差异,并得出香港市场对深市影响显著的结论。     

我国大类资产信息溢出机制研究——基于方差分解的网络拓扑分析

采用广义溢出指数法对2011年至2017年我国股票、期货及债券三个市场之间的信息溢出机制进行了研究,结果发现:股市对期市和债市均有收益率溢出影响,而股市和期市对债市均有波动率溢出影响;三个市场的整体溢出指数值偏低,表明我国不同资产市场之间的关联性相对来说较小;时变特征也表明股市大多数情况处于溢出状态,期市方向不明确,债市则大多数情况处于被溢出状态;对溢出值的非对称检验发现,正向波动比负向波动的溢出值更大,但是统计上并不显著。对2015年6月股灾前后三个市场的波动率溢出情况进行分析后发现,股市的极端风险更容易向期市传染,而债市相对更为稳定,不容易被极端风险感染。     

Patterns in stock market movements tested as random number generators

This paper shows that tests of Random Number Generators (RNGs) may be used to test the Efficient Market Hypothesis (EMH). It uses the Overlapping Serial Test (OST), a standard test in RNG research, to detect anomalous patterns in the distribution of sequences of stock market movements up and down. Our results show that most stock markets exhibit idiosyncratic recurrent patterns, contrary to the efficient market hypothesis; also that OST detects a different kind of non-randomness to standard econometric long- and short-memory tests. Exposure of these anomalies should contribute to making markets more efficient.     

一种区间数的因子分析技术及其在证券市场中的应用

传统的因子分析技术能够有效地对高维变量空间进行降维处理,但它对于样本空间却缺乏行之有效的降维效果.为了解决这一问题,一种针对大量样本数据、新的因子分析技术———区间数因子分析技术(intervaldatafactoranalysis,IFA)被提出并得到了迅速的发展。IFA方法对传统的数据概念做了本质性的扩张,运用'数据打包'的理念,对海量原始数据在不破坏其原有内在逻辑关系的前提下,可以进行变量和样本点维度的双重降维。本文详细阐述了区间数因子分析技术的原理,并以中国股票市场为案例研究背景,结果表明IFA分析技术对大规模多维数据系统做综合简化是十分有效的。     

基于门限混合Copula的股市和债市波动变相关结构

股市和债市的波动相关结构是研究金融市场信息流动、风险传递的重要内容.利用拓展的Copula模型——门限混合Copula模型,并结合EM算法等实证检验了我国股市和债市的关联特征.结果表明:两市波动关联性的不同分歧很大程度是注重对样本区间内整体关联性的检验,忽视了不同阶段与市场波动的特定关系;同时新的Copula模型捕捉到...     

货市与股市波动的超前滞后关系 ——基于复主成分分析法

在传统主成分分析的基础上,复数希尔伯特主成分分析通过将希尔伯特变换与随机矩阵理论相结合获取滤噪经济数据的频域信息,为揭示股票市场与货币市场波动的超前滞后关系提供了途径.实证研究结果显示,在样本区间内,中国股票市场指标相对于货币市场指标来说大部分呈现出超前的变化,而在货币市场中,数量型指标波动较为靠前,价格型指标的反应则较为滞后.此外,股票价格与货币供应量的波动之间存在反馈效应.探索两市场间这样一种动态关系能为政府对金融市场的监管工作提供相应的政策建议.     

General linear formulations of stochastic dominance criteria

We develop and implement linear formulations of general Nth order stochastic dominance criteria for discrete probability distributions. Our approach is based on a piece-wise polynomial representation of utility and its derivatives and can be implemented by solving a relatively small system of linear inequalities. This approach allows for comparing a given prospect with a discrete set of alternative prospects as well as for comparison with a polyhedral set of linear combinations of prospects. We also derive a linear dual formulation in terms of lower partial moments and co-lower partial moments. An empirical application to historical stock market data suggests that the passive stock market portfolio is highly inefficient relative to actively managed portfolios for all investment horizons and for nearly all investors. The results also illustrate that the mean–variance rule and second-order stochastic dominance rule may not detect market portfolio inefficiency because of non-trivial violations of non-satiation and prudence.     

应用微模拟方法分析交易费用对股票市场影响的研究

基于对中国股票市场的连续竞价交易机制和投资者构成特征的分析,本文构建了一个人工模拟订单驱动股票市场模型。模型能够得出一系列与实际股票市场一致的典型事实,如收益率分布的胖尾特征以及波动率的聚集等。通过在模拟实验中设定不同的交易费用约束,分析了不同程度的交易费用约束对股票市场的影响。结果表明,交易费用的增加会导致股票换手率的大幅下降;由于流动性不足,提高交易费用水平并不一定能够达到降低市场波动的目的。     

Identifying critical financial networks of the DJIA: Toward a network‐based index

The purpose of this article is twofold. First, we introduce a novel definition of financial networks obtained from time series data from the stock market. Second, we demonstrate that these networks can be used as an index with the property to reflect critical states of the market, respectively, crashes sufficiently. Our work aims to advocate a network‐based analysis in the context of the stock market, because such a collective phenomenon can not only be economically described by networks but also analyzed as demonstrated in this article. © 2010 Wiley Periodicals, Inc. Complexity 16: 24–33, 2010     

A rolling stock circulation model for combining and splitting of passenger trains

This paper addresses the railway rolling stock circulation problem. Given the departure and arrival times as well as the expected numbers of passengers, we have to assign the rolling stock to the timetable services. We consider several objective criteria that are related to operational costs, service quality and reliability of the railway system.Our model is an extension of an existing rolling stock model for routing train units along a number of connected train lines. The extended model can also handle underway combining and splitting of trains.We illustrate our model by computational experiments based on instances of NS Reizigers, the main Dutch operator of passenger trains.