对金融衍生品市场内幕交易的一些新思考--澳大利亚现行的反内幕交易法及其带给我们的若干启示

本文着眼于澳大利亚在治理金融衍生品市场内幕交易中积累的丰富经验,针对一个崭新的前瞻性课题,即金融衍生品市场的内幕交易问题展开研究。作者认为,由于内幕交易与信息非对称性之间存在的内在冲突,实际上反内幕交易法规很难有效地阻止金融衍生品的内幕交易行为,过于复杂的反内幕交易法规会对市场产生一些负面影响,而放松内幕交易监管这一新思维将对市场的良性发展更为有益,应该让市场来决定内幕交易行为的“存亡”。但目前最为现实、温和的选择仍然是修改现行反内幕交易法,以维护市场的公平性和有效性。最后,笔者对如何缓解中国目前内幕交易猖獗的现状提出建议。     

另类交易系统的法律界定

作为一种新型证券交易场所，另类交易系统是一种以互联网为基础的，依据一定规则自动聚集并撮合投资者委托买卖证券指令的电子交易系统。它属于场外交易场所的范畴，与传统交易所相比，其交易对象更广，交易流程更为便捷，交易规则特殊，同投资者之间的法律关系也不同。它的出现，不仅对传统交易所和中介机构的地位产生了强烈冲击，而且对传统的证券监管体制和证券诉讼也产生了深刻影响。本文在国外对另类交易系统概念界定的基础上，论述了其基本概念和特征，以期为将来我国另类交易系统的立法和监管提供理论参考。     

金融期货价格波动限制机制探讨

金融期货价格稳定机制延缓了价格发现过程，并造成了流动性干扰，但从降低期货、现货交易总成本来讲，它还是利大于弊，因此设置价格波动限制是一种可行的政策，而且在期货、现货市场同时设定的效果最好。此外，从不同价格波动限制方式的影响来看，选择弹性涨跌幅限制可较好地发挥价格限制的好处，减小价格限制的不利影响。     

权证对投资者投资偏好影响的实证研究

金融衍生产品的出现提高了证券市场信息传递的速度，知情交易者通过对衍生品的投资提高传递的效率。本文通过对我国权证市场和相应标的股票市场交易高频数据的研究，探讨知情交易者在权证市场出现后是否改变了投资的对象。实证结果表明，尽管有部分知情交易者投资了认购权证，但是并没有证据表明知情交易者偏好认沽权证。造成这一结果的原因可能是权证制度自身的缺陷。     

状态方程计算高分子共混物的比体积

基于一个简单的非均核链流体分子热力学模型,采用不同形式的微扰项,可构筑不同形式的高分子共混物系统的状态方程。方程已被应用于关联聚苯乙烯/聚2,6-二甲基苯醚(PS/PPO)、聚苯乙烯/聚乙烯甲醚(PS/PVME)、聚苯乙烯/聚丁二烯(PS/PBD)、聚醚砜/聚氧乙烯(PESP/PEO)等高分子共混物的比体积。结果显示,用一个与温度无关的二元相互作用可调参数可满意关联所选体系的比体积,并可预测所选体系的比体积。     

对加入WTO后"以市场换技术"的思考

“以市场换技术”是20世纪80年代中后期以来我国吸引外国直接投资的重要目标之一。本文首先简要回顾了中国在加入WTO前的“以市场换技术”战略,在此基础上,分析了在加入WTO后“以市场换技术”的政策环境和外资在华行为的变化以及国际产业发展呈现出的新趋势,最后对如何促进“以市场换技术”提出了若干建议。     

Relative Liquidity,Fund Flows and Short‐Term Demand: Evidence from Exchange‐Traded Funds

We show that highly liquid Exchange‐Traded Funds (ETFs), especially those that are more liquid than their underlying basket of securities (i.e., positive relative liquidity), are particularly attractive to investors. Using three definitions of liquidity, we find that relative liquidity predicts net fund flows, as well as inflows and outflows positively and significantly. We further document a liquidity clientele among institutional investors: (i) relative liquidity is significantly more important for short‐ than for long‐term investors; and (ii) relative liquidity is inversely related to investors’ average holding duration in the ETFs. These two findings provide evidence that relative liquidity encourages short‐term demand.     

Optimal pair-trading strategy over long/short/square positions—empirical study

Suzuki [Automatica, 2016, 67, 33–45] solves the optimal, finitely iterative, three-regime switching problem for investing in a mean-reverting asset that follows an Ornstein–Uhlenbeck price process and find explicit solutions. The remarkable feature of this model is that the investor can explicitly take either a long, short or square position and can switch the position, with transaction costs, during the investment period. We run empirical simulations of such multiple-regime switching models. There are very few such attempts in the existing literature because it is difficult to find, first, an explicit solution to the problem and second, appropriate financial assets that follow the artificial stochastic process required by the mathematical model. According to the Monte Carlo simulations of the optimal pair-trading strategy, the mean daily Sharp ratio is more than 2.3, whereas the mean Sharp ratio for the historical simulation of the ‘stub’ pairs (combinations of parent/subsidiary companies) is 0.6886. We believe that the results obtained from performing the empirical simulations are remarkable and consider that the optimal switching strategy of the rigorous mathematical model is applicable to businesses in the real world. For the reference many pseudo-program codes are added, which can help to replicate the optimal trading strategies.     

Measuring the liquidity part of volume

Based on the concept that the presence of liquidity frictions can increase the daily traded volume, we develop an extended version of the mixture of distribution hypothesis model (MDH) along the lines of Tauchen and Pitts (1983) to measure the liquidity portion of volume. Our approach relies on a structural definition of liquidity frictions arising from the theoretical framework of Grossman and Miller (1988), which explains how liquidity shocks affect the way in which information is incorporated into daily trading characteristics. In addition, we propose an econometric setup exploiting the volatility–volume relationship to filter the liquidity portion of volume and infer the presence of liquidity frictions using daily data. Finally, based on FTSE 100 stocks, we show that the extended MDH model proposed here outperforms that of Andersen (1996) and that the liquidity frictions are priced in the cross-section of stock returns.     

Does high frequency algorithmic trading matter for non-AT investors?

The extant literature has typically measured the impact of high frequency algorithmic trading (HFT) on short term outcomes, in seconds or minutes. We focus on outcomes of concern for longer term non-algorithm investors. We find in some cases HFT increases volatility arising from news relating to fundamentals. Furthermore HFT is associated with the transmission of that volatility across industries, and that transmission is based on short term correlations. Finally, we find that the period since the introduction of algorithmic trading (AT) has seen increases in both the variances and covariances of return volatility in most industries. However increases in the variances has not been uniform in that it has fallen sharply in a few industries. The magnitudes are such that, overall, AT has coincided with reduced return volatility variance.