交易行为可作为价格波动的先行指标吗?——基于线性与非线性模型的比较研究

本文基于沪深300股指期货四个不同样本期的1分钟交易数据,比较研究了静态线性的马尔可夫转换自回归模型MSA(Markov Switch Autoregress Model)和动态非线性Symmetrised Joe-Clayton Copula模型在对金融变量间相互关系上建模的适用性。研究结果表明,当期价格波动与滞后一期交易行为间不存在稳定的线性关系,但存在明显的尾部相关结构,并且其相关性在趋势行情中尤为显著。这一结果不但表明,趋势行情中滞后一期的交易行为可以作为当期价格波动的先行指标,还展现出了非线性Copula模型在描述金融变量间的相互关系上的适用性和显著优势。     

带约束的零智能交易系统的实验模型的研究

仿真实验分析是研究交易系统规律的一种重要手段,带约束的零智能系统(ZI-C)是业界研究双向交易系统的重要基准.本文针对ZI-C的典型仿真实验进行分析,揭示其中系统内价格出清过程和实验设置的关系,并量化了各交易者在市场匹配中的难易程度.在分析中,首次提出了一种概率仿真模型,使用了迭代计算来估计每一时刻系统中各种价格产生的...     

Modeling stock index returns by means of partial least‐squares methods: An out‐of‐sample analysis for three stock markets

We analyze the underlying economic forces of the stock markets in Germany, the U.K. and the U.S. Identifying a number of variables evincing return predictability, we follow a partial least‐squares (PLS) approach to combine these observables into a few latent factors. Conditional on European markets, our findings indicate (i) superior prediction performance of PLS‐based schemes in comparison with both, a random walk and a first‐order autoregressive benchmark model, (ii) consistent profitable trading on the German and British market, (iii) profitable linear forecast combinations, (iv) the U.S. stock market is diagnosed as informationally efficient. Copyright © 2010 John Wiley & Sons, Ltd.     

证券市场内幕交易有信息含量的临界点值推算

中国证券市场内幕交易的同时存在市场操纵行为,使得独立判断内幕交易的信息含量存在困难.为解决判断纯粹内幕交易是否具有信息含量问题,需要确定内幕交易具有信息含量的临界点值.采用我国证券市场内幕交易与操纵样本数据,先在操纵均衡点附近排除市场操纵的影响,然后推算出无消息、无操纵状态下证券随同大盘运动的理论增长路径,在此基础上比较基于内幕信息操纵和理论增长情况,通过设定与理论增长的倍数关系,推算纯粹内幕交易具有信息含量的临界点值:异常收益应大于3%.该值可以解释现有文献认为内幕交易有或没有信息含量的矛盾与争论.应用于中国内幕交易实际情况及与近年国际相关研究文献对照,临界点值得到支持.     

Insider Trading in Convergent Markets

Optimal trading strategies are found for an insider who is trading in two convergent stocks and is bound by margin constraints.     

A股上市公司内部人股票买卖行为及获利能力分析

系统地分析了2006年至2011年我国A股市场上市公司的内部人在二级市场的交易行为及其收益预测.结论表明:尽管在我国证券市场中存在针对内部人交易的法律法规,但总体上内部人在交易中仍然表现出良好的时机把握能力.不论是买入还是卖出,均能获得显著的超额收益.内部人交易超额收益的大小受到公司所有权性质、内部人类型等因素的影响.一方面,较于董事、监事等内部人,高管获利能力普遍较强,而其中董事长和总经理的获利能力最强;另一方面,由于我国特殊的公司所有权性质与晋升机制,使得国有上市公司的董事长和总经理利用内部人交易获利的动机小于非国有企业;规模越大的国有上市公司,其董事长和总经理通过内部人交易获取超额收益的程度也越小.     

Fuzzy adaptive decision-making for boundedly rational traders in speculative stock markets

The development of new models that would enhance predictability for time series with dynamic time-varying, nonlinear features is a major challenge for speculators. Boundedly rational investors called “chartists” use advanced heuristics and rules-of-thumb to make profit by trading, or even hedge against potential market risks. This paper introduces a hybrid neurofuzzy system for decision-making and trading under uncertainty. The efficiency of a technical trading strategy based on the neurofuzzy model is investigated, in order to predict the direction of the market for 10 of the most prominent stock indices of U.S.A, Europe and Southeast Asia. It is demonstrated via an extensive empirical analysis that the neurofuzzy model allows technical analysts to earn significantly higher returns by providing valid information for a potential turning point on the next trading day. The total profit of the proposed neurofuzzy model, including transaction costs, is consistently superior to a recurrent neural network and a Buy & Hold strategy for all indices, particularly for the highly speculative, emerging Southeast Asian markets. Optimal prediction is based on the dynamic update and adaptive calibration of the heuristic fuzzy learning rules, which reflect the psychological and behavioral patterns of the traders.     

Investment using evolutionary learning methods and technical rules

In this paper, I propose a genetic learning approach to generate technical trading systems for stock timing. The most informative technical indicators are selected from a set of almost 5000 signals by a multi-objective genetic algorithm with variable string length. Successively, these signals are combined into a unique trading signal by a learning method. I test the expert weighting solution obtained by the plurality voting committee, the Bayesian model averaging and Boosting procedures with data from the S&P 500 Composite Index, in three market phases, up-trend, down-trend and sideways-movements, covering the period 2000–2006. Computational results indicate that the near-optimal set of rules varies among market phases but presents stable results and is able to reduce or eliminate losses in down-trend periods.     

ANALYSIS OF FINANCIAL DERIVATIVES BY MECHANICAL METHOD (Ⅰ)—BASIC EQUATION OF PRICE OF INDEX FUTURES

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碳交易机制下考虑竞争和信息非对称的供应链协调研究

本文在碳交易机制下,考虑制造商之间存在竞争且减排成本系数为低碳制造商私有信息的情况,分别构建信息完全对称和信息非对称情形下的供应链模型,对低碳制造商减排率和产品销售价格进行决策。通过引入由批发价和成本共担组成的联合契约,促使低碳制造商传递真实的减排成本信息,并通过算例对碳交易价格和减排成本系数等进行灵敏度分析。研究发现:引入联合契约能够使得信息非对称下的供应链利润基本达到集中决策水平;碳交易价格的增加会激励制造商积极减排、降低碳排放总量、提高供应链利润;低碳制造商减排成本系数的降低有助于减少碳排放量、增加产品市场需求、实现供应链利润增长。