基于策略型消费者的电商平台折扣销售期定价策略研究

电商平台折扣销售期的双重折扣现象激发了巨大的消费需求,本文构建了具有折扣销售期的电商平台和商家的斯坦伯格博弈模型,研究了在电商平台不提供消费者返利和提供消费者返利的情况下商家和电商平台的最优定价策略。从消费者效用出发,结合最优化方法和博弈论,力图为商家和电商平台的决策提供参考。研究结果表明:(1)在电商平台不提供返利时,消费者的策略性越高,正常销售期的价格越高,折扣率越低。(2)当电商平台给消费者提供返利时,正常销售期的价格会升高,而折扣销售期的价格会降低,差异化定价现象愈加明显。(3)当消费者的麻烦成本高于某一阈值时,电商平台提供顾客返利时的收益相比不提供顾客返利时更高且最优利润随着消费者的麻烦成本的增加而增加。(4)拓展部分考虑了过高麻烦成本造成的消费者流失,发现适当的提高消费者的麻烦成本能增加平台和商家的收益,但是当超过一定的范围,会引起用户流失,反而损害双方的利润。     

棉花双关税后进口价格、期货价格与现货价格的感知及传导研究——基于VAR模型

随着我国棉花市场开放程度逐渐提高,探索国内外棉花价格感知和传导机制也愈显重要.国内外棉花价格传递必然受进出口贸易政策的影响,研究征收双关税后的棉花进口价格与国内期、现货价格之间的传递效应,对完善和优化我国棉花价格传导和形成机制更具现实意义.通过VAR模型、格兰杰因果检验、脉冲响应和方差分解等方法检验和探讨三者间的价格感知及传导机制.研究结果表明:征收双关税后的棉花进口价格、国内棉花期货和现货价格三者存在长期协整关系;双关税能够在一定程度上削弱国际棉价对国内棉价的传递能力,双关税后棉花进口价格不是国内棉价的Granger原因;三者在不同时期受到的冲击方向、力度和时间均有差异,据此提出优化国内棉花市场价格感知与传递机制的对策和建议.     

大额资产清仓的自动化交易策略

市场的机构投资者经常需要清仓手中持有的大额资产, 因此清仓的交易策略成为了关心的问题. 以工商银行的股票为例,给出适用于计算机执行的自动化清仓策略. 首先将高频的工商银行股票历史数据在每个交易日分别划分出48个交易期, 将问题简化为处理每个交易日交易期的数据. 在此基础上, 综合考虑用神经网络模拟预测清仓时股票价格随时间下降的风险和用信息流理论模型衡量的价格冲击和交易时刻, 并通过优化模型得到清仓持续的交易日天数. 此后, 再制定出每个交易日的具体自动化交易策略.在制定日内交易策略 时, 首先用神经网络对交易时刻做出预测, 然后综合考虑使用 VWAP 预测出的交易量和通过 Kalman 滤波方法修正过的期权定价公式预测出的各时刻股票的初始价格, 最终给出详细的交易策略及交易的成本.     

网络团购的定价与收益协调策略研究

如何实现团购网站和团购参与商家之间的双赢是我国网络团购目前面临的一大挑战性问题。结合我国网络团购的特点,构建团购网站和商家之间定价与收益分配的博弈模型,针对博弈结果运用纳什谈判模型给出协调策略。最后,通过数值算例分析主要参数的变化对价格与收益的影响。结果表明,敏感市场的规模和团购网站的广告效应越大、商品的单位成本越小、开展网络团购对商家和团购网站越有利。     

金融系统的非线性分析:交易量对股价波动的非线性影响

如何研究股价波动和成交量之间的关系一直是金融系统研究中感兴趣的话题.Lamoureux 和 Lastrapes 认为选择日交易量度量每天流入市场的信息量是合理的,但他们假定交易量对波动率的影响是线性的.提出部分非线性GARCH模型分析交易量对股票市场波动率的影响,基于GARCH模型局部线性化非参数似然估计方法,对中国证券市场股票价格和交易量数据进行实证研究.结果表明,交易量对股价波动的影响具有显著的非线性性.     

夜盘交易对我国农产品期货市场影响的实证研究

随着我国农产品期货与国际市场的联动性进一步加强,为防止相关期货产品的隔夜风险和价格跳水问题,对部分农产品期货实行夜盘交易制度。为测度夜盘交易制度是否有益于农产品期货市场朝着稳定、理性的方向发展,本文采用了适合刻画金融序列波动性的GARCH族模型,实证检验得出GARCH、GARCH-M和EGARCH模型能够高度拟合农产品期货的价格序列并显著衡量夜盘交易对于我国农产品期货市场的影响。研究结论如下:第一、基于GRACH模型实证结果,夜盘交易制度变量的回归结果显著,该制度能减轻农产品期货的价格波动,且其影响是显著的;第二、EGARCH模型的回归结果同样显著,分别对比不同样本期的EGARCH模型实证结果可以得到,夜盘交易的开放减少了农产品期货市场的非对称性,使得市场趋向于理性的方向发展。     

Chance and necessity in sociological theory

This paper proposes a mathematical model of financial markets as networks. The model examines the effect of network structure on market behavior (price volatility and trading volume). In the model, investors are arrayed in various network configurations through which they gather information to make trading decisions. The basic network considered is a chain graph with two parameters, number of investors (n) and the length of time in which information is transmitted (k). Closed‐form expressions for price volatility and expected trading volume are provided. The model is generalized to more complex networks, focusing on the hub‐and‐spoke network. The network configurations analyzed do not represent the real (and unknown) communication network among investors, but predictions from the model are consistent with price and volume patterns observed in sociological and economic research on financial markets. The main result is that network structure alone influences price volatility and expected trading volume even though investors are homogeneous and the information introduced into the system is unbiased and random. This result suggests that the structure of the real communication network among investors may influence market behavior.     

Valuation of futures options with initial margin requirements and daily price limit

The paper presents a valuation model of futures options trading at exchanges with initial margin requirements and daily price limit, and this result gives an academic guidance to design trading rules at exchanges. Unlike the leading work of Black, certain trading rules are considered so as to be more fit for practical futures markets. The paper prices futures options with initial margin requirements and daily price limit by duplicating them with the help of the theory of backward stochastic differential equations （BSDEs, for short）. Furthermore, an explicit expression of the price Of the call （or the put） futures option is given and also is shown to be the unique solution of the associated nonlinear partial differential equation.     

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...     

A micro-movement model with Bayes estimation via filtering: Application to measuring trading noises and costs

We highlight a general hybrid system as the micromovement model for asset price using counting processes recently introduced with its Bayes estimation via filtering. We construct a new simple micromovement model and apply it to analyze trade-by-trade stock price data in the light of the series of works initiated by Christie and Schultz [Why do NASDAQ market makers avoid odd-eighth quotes?, Finance 49 (1994) 1813–1840]. Through the new model, we propose more reasonable, but computationally intensive measures for trading noise including clustering noise and non-clustering noise, and for trading cost. We employ Bayes estimation via filtering to obtain parameter estimates of the new model and to provide numerical measures of trading noise and trading cost for three stocks from four chosen periods. Our empirical results support the important findings in [Christie, Harris, Schultz, Why did NASDAQ market makers stop avoiding odd-eighth quotes?, Finance 49 (1994) 1841–1860; Barclay, Christie, Harris, Kandel, Schultz, The effects of market reform on the trading costs and depths of NASDAQ stocks, J. Finance 54(1) (1999) 1–34].     

An Optimal Trading Rule Under a Switchable Mean-Reversion Model

This work provides an optimal trading rule that allows buying and selling an asset sequentially over time. The asset price follows a switchable mean-reversion model with a Markovian jump. Such a model can be applied to assets with a “staircase” price behavior and yet is simple enough to allow an analytic solution. The objective is to determine a sequence of trading times to maximize an overall return. The corresponding value functions are characterized by a set of quasi-variational inequalities. A closed-form solution is obtained under suitable conditions. The sequence of trading times can be given in terms of a set of threshold levels. Finally, numerical examples are given to demonstrate the results.     

A multistage exchange trading model with asymmetric information and elements of bargaining

A modification of the discrete multistage exchange trading model with risky securities is considered. At each stage of trading, the players place their integer bids. One of the players knows the real price, while the other knows only its probability distribution. The transaction price is defined as a convex combination of the proposed bids with some given coefficient. The solution to an infinitely long game is obtained.     

Mean–variance optimal trading problem subject to stochastic dominance constraints with second order autoregressive price dynamics

The efficient modeling of execution price path of an asset to be traded is an important aspect of the optimal trading problem. In this paper an execution price path based on the second order autoregressive process is proposed. The proposed price path is a generalization of the existing first order autoregressive price path in literature. Using dynamic programming method the analytical closed form solution of unconstrained optimal trading problem under the second order autoregressive process is derived. However in order to incorporate non-negativity constraints in the problem formulation, the optimal static trading problems under second order autoregressive price process are formulated. For a risk neutral investor, the optimal static trading problem of minimizing expected execution cost subject to non-negativity constraints is formulated as a quadratic programming problem. Whereas, for a risk averse investor the variance of execution cost is considered as a measure for the timing risk, and the mean–variance problem is formulated. Moreover, the optimal static trading problem subject to stochastic dominance constraints with mean–variance static trading strategy as the reference strategy is studied. Using Static approximation method the algorithm to solve proposed optimal static trading problems is presented. With numerical illustrations conducted on simulated data and the real market data, the significance of second order autoregressive price path, and the optimal static trading problems is presented.     

状态依赖下的股市正反馈交易

在Sentana和Wadhwani的正反馈模型基础上,本文利用前期涨跌进行状态划分,建立了正反馈交易的Markov状态依赖模型,考察市场中的正反馈交易行为与羊群效应。通过对中国股市的实证研究,可以发现,股价不服从随机游走,在前期股价连续上涨或下跌的情况下,转移概率具有惯性;中国股市存在显著的状态相依的正反馈行为,在前期股价连续上涨的情况下,易激发羊群行为。监管者应注重市场价格的持续变动,投资者可以采用正反馈交易策略。     

Dynamic spanning without probabilities

The paper presents a non-probabilistic approach to continuous-time trading where, in analogy to the binomial option-pricing model, terminal payoffs resulting from a given trading strategy are meaningful ‘state-by-state’, i.e., path-by-path. In particular, we obtain results of the form: “If a certain trading strategy is applied and if the realized price trajectory satisfies a certain analytical property, then the terminal payoff is.…” This way, derivation of the Black and Scholes formula and its extension become an exercise in the analysis of a certain class of real functions. While results of the above forms are of great interest if the analytical property in question is believed to be satisfied for almost all realized price trajectories (for example, if the price is believed to follow a certain stochastic process which has this property with probability 1), they are valid regardless of the stochastic process which presumably generates the possible price trajectories or the probability assigned to the set of all paths having this analytical property.     

基于机器学习的智能TWAP和VWAP算法的研究及应用

TWAP与VWAP算法为两类较常见的经典交易算法.传统的VWAP算法在TWAP算法的基础上,大多使用预测日内成交量分布的方法指导算法下单.传统成交量分布的预测效果严重依赖于市场交易惯性,但交易量分布受到日内诸多突发因素的影响,导致算法对市场突发状况的应对能力较弱.本文对传统TWAP与VWAP算法进行改进,利用滚动的1分钟粒度高频实时资金博弈数据,基于Logistic分类器训练量价模型,以该预测结果为入参构建最优化期望执行均价模型,求出当下各个价格档位对应委托数量的最优解.通过相对高频的分钟级价格预测机制,保证算法实时跟踪市场行情走势并寻求相对优势的交易机会.该算法经测试可以稳定地跑赢市场均价,具备推广应用的可行性.     

ENERGY‐USE CHOICES AND ALLOWANCE TRADING UNDER THE PERSONAL CARBON TRADING SCHEME

Carbon emissions caused by the household sector have become a major contributor to total emissions. Personal carbon trading (PCT), although untested in practice, could potentially be a powerful tool to induce change in consumer behavior. In this paper, we present an optimization model to determine the energy use choices and allowance trading, and a market equilibrium model to obtain the total supply and demand functions of allowances and then to derive the equilibrium allowance price. It is shown that the level of allocated allowance, energy price, emission rate, and transaction costs could influence the equilibrium allowance price and traded volume. Furthermore, the allowance price is affected negatively and slightly by changes in energy prices, so the total energy price variations will be lessened relatively in the PCT scheme. To further demonstrate these relationships, numerical simulations are conducted. On the basis of the simulation results, the implications of this study are discussed and suggestions for future study are provided.     

电力行业碳排放权资源影子价格模型:以海南为例

在电力行业碳排放受限情况下,碳排放权成为电力企业生产必须获取的一种资源。碳排放权资源影子价格可以成为排放权交易定价机制构建和碳税税率制订的重要参考。本文构建了以系统发电总成本最小化为目标的电力系统数学规划模型,利用对偶原理求解碳排放权的影子价格。以海南电网为案例,得到电力系统碳排放权的影子价格并分析了其主要影响因素。研究结果表明,碳排放权影子价格随着碳排放总量上限的降低呈现阶梯状增长走势。碳排放强度高的煤电和排放强度低的风电对排放权的影子价格影响截然相反。     

Stochastic Volatility: Option Pricing using a Multinomial Recombining Tree

In this paper, we present a natural mathematical framework to model trader behavior as a continuous time discrete event process, and derive stochastic differential equations for aggregate behavior and price dynamics by passing to diffusion limits. In particular, we model extraneous, value, momentum and hedge traders. Through analysis and numerical simulation we explore some of the effects these trading strategies have on price dynamics.     

连续交易制度与价格发现功能——基于我国黄金期货市场的实证研究

连续交易制度是提升我国黄金期货市场国际竞争力的重要举措。采用2011年1月至2014年9月中美黄金期货市场日收盘价数据,利用VEC模型、信息份额模型、VEC-BEKK-MGARCH模型、DCC-MGARCH模型,研究了该制度对上海黄金期货市场价格发现功能的影响。结果表明:制度推出后,上海黄金期货市场的价格发现功能得到提升,不过仍弱于美国市场,美国市场对上海市场的收益率传递效应减弱,两市场之间的波动溢出效应有所增强,时变动态相关系数振动幅度明显降低。