基于爬坡约束条件下的多时段竞价模型

本文建立了基于爬坡约束的多时段竞价模型,并通过数据模拟计算,分析比较,从中得出一些有用的结论.这些结论对进一步改善现有的竞价模型可以起到启发指导的作用.     

Stochastic optimal budget decision for advertising considering uncertain sales responses

Firms are faced with uncertain sales responses even though they advertise appropriately. To help marketing managers make optimal budget decisions in this situation, we develop a stochastic model, depicting the problem of advertising budget decision as a special Markov decision process where a new objective, maximizing expected market utility, is proposed. In the model we introduce a two-dimension state variable including accumulative sales, which vary randomly with advertising budget, and the predicted probability that an advertising campaign obtains a full sales response. We make an analysis of the model on the premise of growing infinite market potential, deriving the property of optimal policies and that of optimal value function. These results are successfully used to make advertising budget decisions for a private university in Xi’an, China.     

Portfolio insurance and synthetic securities

This paper aims to look at the situation of portfolio insurance, both from a theoretical and a practical standpoint, a decade after the methodology was first introduced by Leland and Rubinstein, and a few years after management strategies based on portfolio insurance were hurt by the crash of 1987. After a general introduction in Section 1, Section 2 presents a survey of different portfolio strategies and more specifically those related to portfolio insurance. Section 3 underlines the different issues raised by the market plunge of 1987, namely the problem of volatility misspecification, and studies the possible answers offered at this point by academics and practitioners. Section 4 contains some concluding comments.     

转点识别在VaR估计中的应用

本文深入分析了VaR估计结果对市场比率运动规律假设的依赖性 .文献 [1 ],[2 ][4 ]都没有考虑市场因素出现结构性的转变对VaR估计的影响 .事实上 ,市场因素受到其它各种因素的影响 ,很可能发生结构性的转变 .故本文在引入转点识别的基础上对VaR估计方法作出改进 ,从而把市场因素结构性转变引入到VaR估计之中 ,且随机模拟实验结果表明引入转点后的预报有更高的可信度 .     

市场风险值VaR的算法与应用

进行金融风险管理时可以将风险划分为四类，即信用风险、经营风险、流动性风险和市场风险。其中市场风险是指金融市场价格（包括股票价格、利率、汇率和大宗可交易商品的价格）波动而引起的未来收益的不确定性。市场风险值VaR(Value at Risk）就是用来评价给定资产所面临的市场风险大小。本文介绍了VaR的定义、相关的计算方法和在证券投资决策中的应用实例。     

VaR optimal portfolio with transaction costs

We consider the problem of portfolio optimization under VaR risk measure taking into account transaction costs. Fixed costs as well as impact costs as a nonlinear function of trading activity are incorporated in the optimal portfolio model. Thus the obtained model is a nonlinear optimization problem with nonsmooth objective function. The model is solved by an iterative method based on a smoothing VaR technique. We prove the convergence of the considered iterative procedure and demonstrate the nontrivial influence of transaction costs on the optimal portfolio weights.     

Behavioural simulations in spot electricity markets

We study the consistency of behavioural simulation methods used to model the operations of wholesale electricity markets. We include different supply and demand representations and propose the Experience-Weighted Attractions method (Camerer and Ho, 1999) to encompass several behavioural paradigms. We compare the results across assumptions and to standard economic theory predictions. The match is good under flat and upward-slopping supply bidding, and also for plausible demand elasticity assumptions. Learning is influenced by the number of bids per plant and the initial conditions. The simulations perform best under reinforcement learning, less well under best-response and especially poorly under fictitious play. The overall conclusion is that simulation assumptions are far from innocuous. We link their performance to underlying features, and identify those that are better suited to model liberalised electricity markets.     

Using conditional probability to identify trends in intra-day high-frequency equity pricing

By examining the conditional probabilities of price movements in a popular US stock over different high-frequency intra-day timespans, varying levels of trend predictability are identified. This study demonstrates the existence of predictable short-term trends in the market; understanding the probability of price movement can be useful to high-frequency traders. Price movement was examined in trade-by-trade (tick) data along with temporal timespans between 1 s to 30 min for 52 one-week periods for one highly-traded stock. We hypothesize that much of the initial predictability of trade-by-trade (tick) data is due to traditional market dynamics, or the bouncing of the price between the stock’s bid and ask. Only after timespans of between 5 to 10 s does this cease to explain the predictability; after this timespan, two consecutive movements in the same direction occur with higher probability than that of movements in the opposite direction. This pattern holds up to a one-minute interval, after which the strength of the pattern weakens.     

Ups and downs of economics and econophysics — Facebook forecast

What is econophysics and its relationship with economics? What is the state of economics after the global economic crisis, and is there a future for the paradigm of market equilibrium, with imaginary perfect competition and rational agents? Can the next paradigm of economics adopt important assumptions derived from econophysics models: that markets are chaotic systems, striving to extremes as bubbles and crashes show, with psychologically motivated, statistically predictable individual behaviors? Is the future of econophysics, as predicted here, to disappear and become a part of economics? A good test of the current state of econophysics and its methods is the valuation of Facebook immediately after the initial public offering — this forecast indicates that Facebook is highly overvalued, and its IPO valuation of 104 billion dollars is mostly the new financial bubble based on the expectations of unlimited growth, although it’s easy to prove that Facebook is close to the upper limit of its users.