正反馈交易与证券投资基金在证券市场中的作用

本文通过正反馈交易模型直观的描述了作为机构投资者的证券投资基金在面对正反馈交易者时不是套利而是顺势搭车,这就加剧了证券市场价格的波动.为了使机构投资者能够发挥稳定市场的作用,一是要设计出具有激励效应的契约,二是要引导投资者形成价值投资理念,三是要使机构投资者多元化.     

指令驱动市场交易机制对交易策略的影响研究

文章建立人工股票市场模型,研究市场交易机制对市场交易策略的影响。文章设计实验分别在不同指令簿透明度和最小报价单位的指令驱动市场条件下研究市场交易者的交易策略。结果表明,交易机制对不同交易者比例的市场交易策略的影响效果不同,说明相同的机制设计可能对于不同特征的市场会产生完全相反的效果。因此在制定市场政策时,要充分考虑市场本身的特征,制定符合市场需要的市场政策和交易规则。     

交易机制与短期收益的波动

证券交易机制是证券市场中的一项制度安排。分为狭义和广义交易机制。狭义的交易机制仅指证券价格的决定机制,包含三个方面的内容:一是交易优先级的设置。二是指令撮合方式,分为集合竞价和持续竞价两种。三是为防止市场发生剧烈波动,指令执行中某些强制性的价格稳定机制,如涨跌幅限制。广义的交易机制是各种交易制度的总称,包括价格决定机制、清算机制、信息传播机制等内容。在狭义的交易机制中,两类指令撮合方式代表了两种不同的价格形成机制。在集合竞价方式下,交易指令累积到一定程度,再按“价格优先,时间优先”的原则集中进行撮合。持续…     

正反馈交易模型及机构投资者交易行为的作用

一、引言证券市场存在内幕交易的情况下,由于机构投资者要获得企业内幕信息需要大量成本,而内幕人通常不需花费什么成本即可获得内幕信息,相比而言,机构投资者在与内幕人的竞争中处于劣势,内幕交易并不利于机构投资者,甚至可能被逐出内幕交易活跃的领域。由于机构投资者在股价形成中起着重要的引领作用,引导投资者进行价值投资。他们一旦被逐出证券市场,价值投资理念很难形成,市场上的投机气氛就会很浓,导致股价严重偏离其真实价值。但是,在内幕交易被禁止的条件下,情况变得对机构投资者有利,因而受益人也主要是机构投资者而非中小投资者。…     

机构投资者交易与股票定价错误的关系研究

文章研究中国资本市场中机构投资者交易与股票定价错误的关系.以股票市价与内涵价值之差定义了股票定价错误,以大笔交易表示机构投资者交易,采用分组比较及多元回归方法进行实证检验.结果发现:我国机构投资者未表现出买入股价被低估的股票及抛售股价被高估股票的交易偏好;在控制了流通盘规模、市场状态等影响因素后,机构投资者交易与股票定价错误显著正相关,这表明我国机构投资者不仅未能修正股票定价错误,反而加剧了市价偏离其价值的程度,扭曲了市场定价机制.     

流动性风险度量:最优出清策略下的La_RVaR模型

在评估投资者的风险水平时必须要考虑到流动性的内生性,即交易量对于价格的冲击效应(market impact)。对于考虑交易量市场冲击效应的La_RVaR计算,Hisata和Yamai(2000)给出了详细的分析框架和思路,认为投资者首先要在考虑市场冲击效应的基础上求出最优的交易策略,     

基于非同步交易的国内外期货市场价格发现贡献度研究

针对我国期货市场与国际成熟期货市场交易时间的非同步性,本文给出了基于非同步交易的信息共享模型,并对国内、外主要期货市场之间的价格发现贡献度进行了实证研究。研究结果显示：基于非同步交易的信息共享模型可以很好地刻画非同步期货市场之间的价格发现贡献度;并且,国外发达市场的价格发现贡献度要明显大于国内市场,由此表明国外期货市场的价格发现仍居于主导地位,这进一步支持了价格发现被期望在较低交易成本市场发生的交易成本假说。     

混合预期噪声交易模型及我国证券市场非理性交易的实证分析

 证券资产作为以获取未来收益为目的投资工具，它在价格形成及其市场运行模式上都取决于投资者的预期。基于有效市场假说（EMH）的资产定价理论虽然在理论体系及其形式化上都给出了完美的解决方案，但投资者理性和投资者具有完全一致的预期这两个基本假定在现实证券市场投资中却难以得到满足。本文更现实地依据投资者预期形成的差异，讨论了非一致有限理性预期下的证券市场价格的决定，提出了基于混合预期的噪声交易模型。同时本文还利用上海证券市场的相关实际数据，对该模型进行了实证检验，从而克服了行为金融学中噪声交易模型不能用于实证分析的障碍。     

中国证券投资基金动量交易行为的实证研究

作为中国股市的主力投资机构，投资基金的交易行为对证券市场的影响始终是市场关注的焦点。而基金的动量交易正是基金投资策略、投资行为和投资理念的体现。文章首先通过对股改后2005年第3季度至2009年第4季度证券投资基金的交易数据对其动量交易行为进行总体上的研究，然后将基金持股按不同投资风格进行划分，对其动量交易行为进行实证比较分析。在此基础上，还通过对基金动量交易和投资绩效关系的实证检验，展开对基金投资策略有效性的探讨。     

短期收益率与限价指令薄信息

一、引言 上海证券交易所采用自动化电脑交易系统,接受交易者的限价指令,按照"时间优先,价格优先"的原则,对买卖双方提交的订单进行自动匹配,达成交易.不断提交的一系列指令构成了指令流,它实际上反映了交易者的指令提交策略.在电子化的交易环境中,买卖双方不断提交的限价指令形成了一个随时准备交易的买卖承诺"池",以便与相匹配的指令成交.限价指令中包含交易者所意愿交易的价格和数量信息,这些信息可能会对未来交易价格的形成和变化产生重要的影响.     

A delayed dual risk model

In this article, we study a dual risk model with delays in the spirit of Dassios–Zhao. When a new innovation occurs, there is a delay before the innovation turns into a profit. We obtain large initial surplus asymptotics for the ruin probability and ruin time distributions. For some special cases, we get closed-form formulas. Numerical illustrations will also be provided.     

限价订单信息含量分布：理论模型及中国市场实证研究

投资者订单决策过程是研究不完全市场信息释放的逻辑起点。订单的信息分布对市场结构设计有重要的作用。构建非对称环境中投资者订单选择策略模型,并利用高频误差修正模型对理论研究结论进行检验。研究发现中国证券市场订单具有递减信息分布。     

市场流动性的状态转换及其突变点检测研究

通过构建AR-MS-GARCH模型,分析了市场流动性的状态转换机制,并设计了一种新的突变点检测指标。实证结果表明,市场流动性存在明显的"低—高"波动状态交替转换特征,两种状态都有较强的波动持续性,但不同状态转换和持续期存在一定的非对称性;计算突变点检测指标发现,市场流动性在样本期内存在五个突变点,而它们所对应的时刻往往是市场流动性"强—弱"转换的临界点。这些结论有助于监管部门及时采取政策措施,减少市场流动性突然逆转的可能性,以维护金融系统稳定。     

经济政策不确定性如何影响金融市场间的流动性协同运动？——基于中国金融周期的视角

金融市场间流动性出现高协同运动是发生危机传染的重要表现之一，因此，针对流动性动态联动效应的研究显得极为重要。本文基于中国金融市场数据测算了2003-2018年间我国股市、债市流动性，并对Colacito等（2011）的混频数据抽样动态条件相关系数模型（DCC-MIDAS）进行了扩展，同时从金融周期视角出发，运用扩展后的模型考察了经济不确定性在不同时间区间内对于流动性波动率和相关性是否存在不同的作用效果。研究结果表明，相较于单因子混频模型，引入经济政策不确定性的多因子混频模型可以更好地捕捉我国股债两市相关性的动态变化；同时，经济政策不确定性的提高会降低股债两市流动性的正相关性，但这一作用效果会在金融周期的拐点处转为加强两者的正相关性。本文不仅为讨论股债两市联动效应提供了流动性的新视角，也为金融市场风险监管提供了重要的参考依据。     

Establishing decision tree-based short-term default credit risk assessment models

ABSTRACT

Traditional credit risk assessment models do not consider the time factor; they only think of whether a customer will default, but not the when to default. The result cannot provide a manager to make the profit-maximum decision. Actually, even if a customer defaults, the financial institution still can gain profit in some conditions. Nowadays, most research applied the Cox proportional hazards model into their credit scoring models, predicting the time when a customer is most likely to default, to solve the credit risk assessment problem. However, in order to fully utilize the fully dynamic capability of the Cox proportional hazards model, time-varying macroeconomic variables are required which involve more advanced data collection. Since short-term default cases are the ones that bring a great loss for a financial institution, instead of predicting when a loan will default, a loan manager is more interested in identifying those applications which may default within a short period of time when approving loan applications. This paper proposes a decision tree-based short-term default credit risk assessment model to assess the credit risk. The goal is to use the decision tree to filter the short-term default to produce a highly accurate model that could distinguish default lending. This paper integrates bootstrap aggregating (Bagging) with a synthetic minority over-sampling technique (SMOTE) into the credit risk model to improve the decision tree stability and its performance on unbalanced data. Finally, a real case of small and medium enterprise loan data that has been drawn from a local financial institution located in Taiwan is presented to further illustrate the proposed approach. After comparing the result that was obtained from the proposed approach with the logistic regression and Cox proportional hazards models, it was found that the classifying recall rate and precision rate of the proposed model was obviously superior to the logistic regression and Cox proportional hazards models.     

A Finite Horizon Dynamic Programming Model for Production and Repair Decisions

In this research, a novel optimal single machine replacement policy in finite stages based on the rate of producing defective items is proposed. The primary objective of this paper is to determine the optimal decision using a Markov decision process to maximize the total profit associated with a machine maintenance policy. It is assumed that a customer order is due at the end of a finite horizon and the machine deteriorates over time when operating. Repair takes time but brings the machine to a better state. Production and repair costs are considered in the model and revenue is earned for each good item produced by the end of the horizon, there is also a cost for the machine condition at the end of the horizon. In each period, we must decide whether to produce, repair, or do nothing, with the objective of maximizing expected profit during the horizon.     

AN INVENTORY PROBLEM APPLIED TO A RENTAL SITUATION

An inventory problem, applied to a rental situation business, has been considered. If no item is in stock when a demand occurs, the company borrows the units from other concerns in the same line of business. The profit function has been calculated and it has been shown how the inventory level increases with penalty cost. A review of the literature on inventory control reveals that not much work has been done in holding inventories of rental items. In a recent paper, Tainiter (1964) considered the situation in which a company rents out items such as cars, trucks, farm equipment, books, furniture, etc., and obtained the profit function by taking “rental-out” time as a negative exponential and demand as a general random variable. The model is equally applicable to companies which rent out “service personnel”, repair men, taxi cabs, etc. “We consider a company renting out items to customers. The company starts its business by purchasing a total number of M items in the inventory. The term inventory, defined by Arrow, Earlin and Scarf (1958) as the stock of goods which is kept for future sale or production, is applicable here. Whenever a demand occurs the item is rented out immediately, if it is available in the stock. But if the inventory is zero, i.e. all the items are rented out, the demand will be satisfied by borrowing items from other companies which are dealing in the same line of business. For example, a manufacturer of refrigerators maintains and repairs his product at the customer's house after sale. If a complaint arrives when no repairmen are available, the company will “borrow” repairmen from elsewhere and will attend to the complaint immediately. The borrowing cost may be negative or positive, representing a penalty or a profit. On the other hand if the company does not borrow and the customer has to wait (and such situations occur very often) the loss of the customer's goodwill may occur. It is also not possible to keep large numbers of items because of the storage costs and tied up capital. The problem is then to devise an optimal policy such that the profits of the company are maximized.     

经济新常态下货币政策中介目标的改进与评估

货币政策实施是否有效,关键在于选择合适的中介目标。经济新常态下,传统的货币供应量指标由于缺乏对各层次货币资产流动性差异的考量,与实体经济指标的相关性不断减弱。基于消费理论,通过引入中国人民银行存贷款综合抽样利率,计量各层次货币资产流动性选择的机会成本,并借鉴Divisia指数构建方法,尝试编制中国Divisia货币供应量。评估结果显示:新的Divisia货币供应量对货币资产结构变动引起的流动性改变反应更加敏锐,且稳定性、可控性良好,可以作为经济新常态下货币政策中介目标的参考指标。     

持续期间、交易量、波动率与知情交易

内容提要：Admati和Pfleiderer [1]认为交易强度的增加,可能来自于知情交易也可能来自于流动性交易。本文通过分析中国股票市场上持续期间、交易量和波动率之间的关系,提供了识别知情交易和流动性交易的证据。与国外相关研究结论均不同的是,本文的实证结果认为：波动率与持续期间之间存在非线性关系,交易量较小时,交易强度的增加主要来自于流动性交易;而交易量较大时,交易强度的增加主要来自于知情交易。最后,本文对以上实证结果进行了稳健性检验,通过分析波动率日内特征对实证结果的影响,本文还发现,中国股票市场的知情交易通常发生在刚开盘的阶段。     

潜在流动性约束与城镇家庭消费

笔者认为,收入不平等与家庭消费的关系与信贷约束程度以及家庭社会地位偏好有关。住房是典型的地位性商品,收入差距扩大时,人们为了维持或提高现有的相对地位会努力改善居住条件,住房攀比最终会导致全社会住房面积标准提高和房价上涨。在信贷缺乏的环境中,购房标准提高和房价上涨意味着家庭未来遭遇流动性约束的风险加大,为此,家庭在增加购房预算的同时会抑制日常消费。利用2010年、2012年和2014年的微观跟踪调查数据所做的实证分析支持了我们的观点：（1）周围人群的住房面积的扩大,会促使家庭选择购买更大的房子。并且,攀比效应对住房需求的刺激作用明显大于房价上涨对住房需求的抑制作用。（2）家庭平均住房面积扩大和房价上涨都与收入不平等引发的住房攀比有关。（3）收入不平等对城镇家庭消费皆有拉动作用和抑制作用。（4）潜在流动性约束对家庭消费的抑制作用与家庭地位等级的高低有关。