期权视角下房屋预售合约定价模型

房屋预售合约赋予了购房者以给定的价格购买房屋的权利,具有期权性质。首先基于房地产市场具有摩擦的事实,将房屋预售合约视为房价的期权合约,然后通过将房价演变过程模型化为Ornstein-Uhlenbeck过程,导出了预售合约的合理价格(即首付)的解析表达式,最后比较了采用几何布朗运动与Ornstein-Uhlenbeck过程模拟房价变化所得房屋预售价格的差异。结论认为,基于Ornstein-Uhlenbeck过程导出的房屋预售合约价格相较于几何布朗运动下的预售合约价格具有更小的套利空间。     

经济结构变化对商品房价格的影响:来自1999-2011年省际面板数据的实证分析

本文以经济结构变化作为切入点对中国住房价格持续高涨现象进行分析,在构建理论分析模型的基础上,运用我国1999年至2011年省际面板数据进行了实证分析。研究结果表明:经济结构对商品房价格具有决定性的影响,长期来看,城乡收入分配结构、城镇化水平、工业化水平、以及财政分权水平决定了房价水平;短期来看,除了经济结构外,房价偏离长期均衡价格的水平决定了房价水平。     

基于MIV-BP型网络实验的房地产价格影响因素研究

房地产价格是保证房地产经济健康运行和资源有效配置的关键.影响房地产价格的因素复杂,各因素的变化势必将对房地产价格的涨跌产生影响.以经济学中的供求理论为基础,以上海市商品住宅价格为研究对象,对BP神经网络进行训练,计算各因素对房价的平均影响值(MIV),构建MIV-BP模型,实证分析各因素对房地产价格的影响作用.结果表明:生产总值,贷款利率,居民人均可支配收入成为影响我国房地产价格的主要因素.居民消费价格指数,土地增值税对房价产生较显著影响.而在上述变量作用下,房地产供给面积与销售面积已经很难影响房地产价格的走势.因此应将生产总值,贷款利率,人均可支配收入作为房地产价格调控的着力点.     

涟漪效应还是空间互动——基于空间面板联立方程模型的房价与地价关系研究

本文通过构建包含房价和地价在内的空间面板联立方程模型,利用2009~2016年中国286个地市的数据,构建空间面板联立方程模型,以研究房价和地价的空间自相关性和空间溢出效应。实证结果表明:房价与地价之间的空间互动作用明显,房价不但受到当地地价的影响还会受到周边城市房价的影响;而城市地价也会受到当地房价引起的引致需求影响,并且受到周边城市地价的影响。分区域来看,地价对房价的作用强度在东、中、西部地区依次下降,房价对地价作用强度呈现出相反的趋势。而从价格的溢出效应来看,无论是房价还是地价,西部地区的价格溢出效应都最为明显,表明相对于东、中部地区,西部地区城市在房价和地价上都更会受到周围城市的影响。     

基于一般均衡的不同税制对住房价格影响的比较分析

针对参与者预期具有异质性的房地产市场,在一般均衡模型框架下对以营业税为代表的住房转让环节税收和对住房持有环节征收的房产税对房价的影响作用进行分析和比较.理论研究结果表明,房地产税通过影响预期较为中性的参与者的交易决策改变市场均衡(价格),且转让环节与持有环节的税收具有相反的价格效应:征收住房转让环节营业税或提高营业税税率会使房价升高,无法起到抑制价格泡沫的作用;征收住房持有环节房产税或提高房产税税率则会使房价降低.对于房产税政策,如果对增量和存量住房统一征收房产税,则市场均衡价格较仅对增量征税时低,即存量房产税通过扩大市场供给降低房价.此外,文章提出了相关政策建议并证明了模型设定的连续性.     

采用层次分析法确定住房价格的探讨

通过综合分析影响商品房价格的各类因素,充分考虑供房者和受房者的共同利益,以综合房价为目标层,供方房价和承受房价为决策层,建立AHP模型,通过问卷调查的数据构造判断矩阵,最终制定能够被双方都接受的房价.     

人民币汇率波动与我国房价关系的实证分析

分析了汇率影响房价的机制,利用人民币实际有效汇率、房地产价格指数和银行同业拆借利率共30组数据(2005,07～2007,12)建立了向量自回归模型(VAR),并使用协整、Granger因果检验,脉冲响应分析对人民币汇率波动与我国房地产价格之间的关系进行实证检验.研究结果表明,人民币实际有效汇率对房地产价格产生正向影响,人民币升值是引起房价上涨的格兰杰原因.在现阶段,控制因人民币升值而进入中国的境外资金过度流入房地产市场,有利于保持我国房地产价格稳定.     

基于实物期权的物流企业能力外购策略

探讨物流企业面临客户需求以及市场物流能力价格的双重不确定环境,物流企业的能力外购策略。通过引入实物期权的思想,构建物流企业能力外购模型,寻找使物流企业期望收益最大的能力预定量。分析表明,最优预定量随着期权价格和期权执行价格的增加而减小。最后,通过算例分析进一步探讨不同期权执行价格对物流企业最优外购策略选择的影响。     

基于改进PSR模型的限购政策对房价影响研究——以海南省为例

运用2018年全国研究生电工杯数学建模竞赛B题的数据资料,针对海南省主要城市商品住宅价格问题的第四问展开研究.在前三问中,首先通过搜集数据并对数据进行合理的处理,对海南省(主要考虑海口和三亚)商品住宅价格的影响因素进行定量分析,得出各因素之间的关系.问题四中,考虑限购政策,在综合分析房价影响因素的基础上,筛选新的指标,构建了基于改进粒子群算法模糊层次分析法——PSR模型的房地产调控政策对于房价影响的评价体系,得到了海南省的房地产宏观调控政策的对房价上涨的影响结果.最后,根据建立的评价体系利用matlab神经网络工具箱按月预测了2018年6月-2019年5月海南省(主要考虑海口和三亚)商品住宅价格.     

土地市场波动与房地产价格的关系分析:基于VAR模型的实证研究

随着中国经济增长、城市化的发展,房价不断攀升,居民面临巨大的购房压力,而政府也开始对房地产市场进行调控,在房价构成因素中,土地成本占有很大比重,因此土地价格,土地供应面积与房地产价格之间的关系研究对促进房地产市场的合理发展有十分重要的意义.以2002年到2011年我国土地供应面积,土地购置价格和房地产价格的月度数据为样本,对土地供应面积,土地购置价格与房地产价格进行协整检验后,构建VAR模型进行格兰杰因果检验后发现土地供应价格,面积和房地产价格互为因果;对城市土地购置价格和房地产价格进行脉冲响应分析和方差分解后发现房地产价格和土地价格之间的存在相互影响,且在短期内都受土地供应面积的影响但程度不高.     

Dynamic pricing of inventory/capacity with infrequent price changes

We consider a problem of dynamically pricing a single product sold by a monopolist over a short time period. If demand characteristics change throughout the period, it becomes attractive for the company to adjust price continuously to respond to such changes (i.e., price-discriminate intertemporally). However, in practice there is typically a limit on the number of times the price can be adjusted due to the high costs associated with frequent price changes. If that is the case, instead of a continuous pricing rule the company might want to establish a piece-wise constant pricing policy in order to limit the number of price adjustments. Such a pricing policy, which involves optimal choice of prices and timing of price changes, is the focus of this paper.We analyze the pricing problem with a limited number of price changes in a dynamic, deterministic environment in which demand depends on the current price and time, and there is a capacity/inventory constraint that may be set optimally ahead of the selling season. The arrival rate can evolve in time arbitrarily, allowing us to model situations in which prices decrease, increase, or neither. We consider several plausible scenarios where pricing and/or timing of price changes are endogenized. Various notions of complementarity (single-crossing property, supermodularity and total positivity) are explored to derive structural results: conditions sufficient for the uniqueness of the solution and the monotonicity of prices throughout the sales period. Furthermore, we characterize the impact of the capacity constraint on the optimal prices and the timing of price changes and provide several other comparative statics results. Additional insights are obtained directly from the solutions of various special cases.     

Pricing strategies for perishable products: the case of Vienna and the hotel reservation system hrs.com

Consider a retailer who sells perishable products for which there is uncertain demand. Yield management with dynamic pricing is a standard practice that firms use for revenue management. For perishable products, recent analysis has focused on the distribution of flight capacity, referred to as ticket sales. Other non- storable, non-transportable, immaterial hospitality products include hotel capacity. The article discusses the extent to which hotel pricing strategies vary within the internet distribution system hrs.com. This study focuses on the distribution of hotel rooms available for booking on the internet for Vienna and gives an outlook to Euroland capitals. The main research interests are the underlying pricing models and the setting of the end price. Data was taken from hrs.com, which is the most important specialist for hotel room internet distribution in Germany according to recent studies by KMPG and others. The results include the identification of different pricing strategy clusters with regard to hotel category and hotel availability over a 22-day period for Vienna and one city from all Euroland countries (the capitals were studied for all cases except for the Netherlands, for which data was collected for Amsterdam). The study took the arrival days Mondays, Tuesdays, Wednesdays and Thursdays into account, and used data for all these days from the 11th of July, 2005, to the 10th of October, 2005, for Vienna, and the first and the last of these dates as a comparison base for the other Euroland cities.     

The impact of dynamic pricing on the economic order decision

This paper analyzes the impact of dynamic pricing on the single product economic order decision of a monopolist retailer. Items are procured from an external supplier according to the economic order quantity (EOQ) model and are sold to customers on a single market without competition following the simple monopolist pricing problem. Coordinated decision making of optimal pricing and ordering is influenced by operating costs – including ordering and inventory holding costs – and the demand rate obtained from a price response function. The retailer is allowed to vary the selling price, either in a fixed number of discrete points in time or continuously. While constant and continuous pricing have received much attention in the literature, problems with a limited number of price changes are rather rare. This paper illustrates the benefit of dynamically changing prices to achieve operational efficiency in the EOQ model, that is to trigger high demand rates when inventories are high. We provide structural properties of the optimal time instants when the price should be changed. Taking into account costs for changes in price, it provides numerical guidance on number, timing, and size of price changes during an order cycle. Numerical examples show that the benefits of dynamic pricing in an EOQ framework can be achieved with only a few price changes and that products being unprofitable under static pricing may become profitable under dynamic pricing.     

Pricing policy in dynamic markets and a generalization of the Ramsey rule

Pricing policy in a regulated monopoly industry is usually based on maximizing welfare or some other measure of utility level of return on investment. Previously, the Ramsey pricing policy which states that the percentage deviation of quasi-optimal price from marginal cost for each product must be inversely proportional to its price elasticity of demand, has been developed for a static market. The Ramsey framework assumes instantaneous demand response to price changes; empirical evidence suggests demand changes occur dynamically through time.In this paper an optimum pricing rule for a profit maximizing firm based on a general time varying demand model in a dynamic market is obtained assuming a single price change at the beginning of the planning period. A dynamic market equivalent of the well known inverse elasticity law of the static market is developed. Defining the concept of average price elasticity for dynamic markets we show that the inverse elasticity law of static markets takes an inequality form in dynamic markets. For demand functions which decrease, increase or are constant with time the optimum price markups are greater than, less than, or equal to the inverse of the average price elasticity, respectively.The results are then generalized to the case of a constrained welfare maximizing firm. This leads to the development of a dynamic market generalization of the well known Ramsey pricing rule. A simple rule for making quantitative arguments about the relative size of the optimum price in static and dynamic markets is also derived.This work was completed when the author was with Bell Laboratories, USA.     

Dominance,bargaining power and service platform performance

In this paper we study the relationship between a firm (hotel) and a service platform (Ctrip.com). We start with a newsvendor hotel facing two kinds of customers. D-customers order the room directly from the hotel front desk; C-customers order the room through Ctrip.com. Ctrip.com charges the hotel while introducing its members to the hotel. The hotel decides how many rooms are allotted to Ctrip.com to achieve optimal profit. We consider the situation where one party’s demand cannot be observed by another, and study the commonly used wholesale price contract. Interestingly, the contract can always coordinate the system. We then investigate the influence of bargaining power on the profit division under situations where Ctrip.com and hotel, respectively, dominate the system, and find that increasing (or decreasing) a party’s bargaining power without considering the other does not necessarily benefit (or damage) the first party. Further, we discuss how the parties choose dominance and appropriate bargaining power to make a trade-off for better cooperation. An interesting phenomenon is that bargaining power for each party can be identical when any party dominates the system. We also propose a threshold at which the wholesale price contracts can always be the Pareto optimal for the channel.     

Optimal ordering and pricing policies in a single-period environment with multivariate demand and markdowns

This paper investigates a single-period inventory model in which the demand of the product is a deterministic, multivariate function of price, time, and level of inventory. Models are formulated for the basic pricing case and the case with a price markdown during the season. Solution methodologies are presented for each case when the pricing decisions are predetermined and when they are decision variables. Comments on the practical use of this model are presented, and sensitivity analysis is conducted on the decision variables and demand parameters.     

Periodic pricing and replenishment policy for continuously decaying inventory with multivariate demand

This paper deals with the joint decisions on pricing and replenishment schedule for a periodic review inventory system in which a replenishment order may be placed at the beginning of some or all of the periods. We consider a single product which is subject to continuous decay and a demand which is a function of price and time, without backlogging over a finite planning horizon. The proposed scheme may adjust periodically the selling price upward or downward that makes the pricing policy more responsive to structure changes in supply or demand. The problem is formulated as a dynamic programming model and solved by numerical search techniques. An extensive numerical study is conducted to attend qualitative insights into the structures of the proposed policy and its sensitivity with respect to major parameters. The numerical result shows that the solution generated by the periodic policy outperforms that by the fixed pricing policy in maximizing discount profit.     

Efficient formulations for pricing under attraction demand models

We propose a modeling and optimization framework to cast a broad range of fundamental multi-product pricing problems as tractable convex optimization problems. We consider a retailer offering an assortment of differentiated substitutable products to a population of customers that are price-sensitive. The retailer selects prices to maximize profits, subject to constraints on sales arising from inventory and capacity availability, market share goals, bounds on allowable prices and other considerations. Consumers’ response to price changes is represented by attraction demand models, which subsume the well known multinomial logit (MNL) and multiplicative competitive interaction demand models. Our approach transforms seemingly non-convex pricing problems (both in the objective function and constraints) into convex optimization problems that can be solved efficiently with commercial software. We establish a condition which ensures that the resulting problem is convex, prove that it can be solved in polynomial time under MNL demand, and show computationally that our new formulations reduce the solution time from days to seconds. We also propose an approximation of demand models with multiple overlapping customer segments, and show that it falls within the class of demand models we are able to solve. Such mixed demand models are highly desirable in practice, but yield a pricing problem which appears computationally challenging to solve exactly.     

乘客策略行为下考虑需求学习的航空客运动态定价策略研究

研究航空公司在需求学习下的动态定价策略。通过假设乘客到达率不确定以及具有策略等待行为,运用贝叶斯理论和博弈论对航空公司需求学习下的多周期动态定价问题进行建模,探讨了机票最优定价策略的充分条件,并通过分析航空公司收益函数的性质,得到了最优定价随时间和已出售机票数量的变化趋势。最后应用算例分析了需求学习的效果,得出:需求学习能够缓解需求不确定带来的损失,但不能完全消除;乘客策略程度越大,需求学习效果越明显。     

考虑保质期的非即时易腐品最优订购与定价决策

针对有保质期约束的非即时易腐品,零售商可以在产品非腐败阶段和腐败阶段进行差异化定价来调整市场需求。即零售商可以调整产品非腐败阶段的定价策略,使得非即时易腐品在进入腐败阶段之前全部售出;或者在产品腐败阶段降低零售价格以刺激市场需求。因此,在需求依赖价格的假设下,本文研究了零售商关于有保质期约束的非即时易腐品的最优订购与定价决策。通过分析零售商单位时间利润函数的理论性质,得到了零售商的最优订购与定价策略。基于线性和指数型两种需求函数形式进行数值算例,可以发现针对保质期较长或者非腐败阶段较长的易腐品,零售商会延长订货周期来增加销售收入。特别是在指数型需求函数情境下,当市场需求与零售价格高度相关时,零售商更有意愿降价来刺激销量,从而使得易腐品在非腐败阶段内销售完毕。