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。     

A simple comparison between Skorokhod & Russo-Vallois integration for insider trading

We consider a simplified version of the problem of insider trading in a financial market. We approach it by means of anticipating stochastic calculus and compare the use of the Skorokhod and the Russo-Vallois forward integrals within this context. We conclude that, while the forward integral yields results with a clear financial meaning, the Skorokhod integral does not provide a suitable formulation for this problem.     

Optimal Decisions in a Time Priority Queue

We show how the position of a limit order (LO) in the queue influences the decision of whether to cancel the order or let it rest. Using ultra-high-frequency data from the Nasdaq exchange, we perform empirical analysis on various LO book events and propose novel ways for modelling some of these events, including cancellation of LOs in various positions and size of market orders. Based on our empirical findings, we develop a queuing model that captures stylized facts on the data. This model includes a distinct feature which allows for a potentially random effect due to the agent’s impulse control. We apply the queuing model in an algorithmic trading setting by considering an agent maximizing her expected utility through placing and cancelling of LOs. The agent’s optimal strategy is presented after calibrating the model to real data. A simulation study shows that for the same level of standard deviation of terminal wealth, the optimal strategy has a 2.5% higher mean compared to a strategy which ignores the effect of position, or an 8.8% lower standard deviation for the same level of mean. This extra gain stems from posting an LO during adverse conditions and obtaining a good queue position before conditions become favourable.     

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.     

基于碳交易的闭环供应链碳减排与定价策略研究

在消费者对低碳产品存在偏好的碳交易市场中,研究两级闭环供应链中的减排与定价决策问题.对于制造商负责回收模式下的回收再制造过程,采用指数分布来刻画废旧产品质量水平的不确定性.假设新产品和再制造品存在竞争关系,建立制造商和零售商间的Stackelberg博弈模型,给出制造商确定减排投资和回收参考价格以及零售商决定两种产品的差别定价策略,通过算例分析回收产品的残值和碳交易价格对最优策略和供应链成员利润的影响.研究表明,为了获得利润最大,当碳交易的市场价格升高时,制造商应加大减排投资,且零售商应采取提高产品零售价的策略.     

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.     

The Challenges of Machine Learning and Their Economic Implications

The deployment of machine learning models is expected to bring several benefits. Nevertheless, as a result of the complexity of the ecosystem in which models are generally trained and deployed, this technology also raises concerns regarding its (1) interpretability, (2) fairness, (3) safety, and (4) privacy. These issues can have substantial economic implications because they may hinder the development and mass adoption of machine learning. In light of this, the purpose of this paper was to determine, from a positive economics point of view, whether the free use of machine learning models maximizes aggregate social welfare or, alternatively, regulations are required. In cases in which restrictions should be enacted, policies are proposed. The adaptation of current tort and anti-discrimination laws is found to guarantee an optimal level of interpretability and fairness. Additionally, existing market solutions appear to incentivize machine learning operators to equip models with a degree of security and privacy that maximizes aggregate social welfare. These findings are expected to be valuable to inform the design of efficient public policies.     

Decidability of finite quasivarieties generated by certain transformation semigroups

No Abstract. Received January 2, 2000; accepted in final form August 28, 2000.     

Bifurcation and disaggregation in urban/regional spatial modelling: A technical note

Using the Lowry-Garin model as an example, we illustrate the complexity of bifurcation and aggregation issues in urban/regional spatial systems. As a first step, a disaggregate version of the Lowry-Garin model is formulated. Then the general conditions for bifurcation are identified in terms of disaggregate labor-force participation rate, population-serving ratio and accessibility indices. Physical interpretation of these conditions is also given.