Parametric Inference and Dynamic State Recovery From Option Panels

We develop a new parametric estimation procedure for option panels observed with error. We exploit asymptotic approximations assuming an ever increasing set of option prices in the moneyness (cross‐sectional) dimension, but with a fixed time span. We develop consistent estimators for the parameters and the dynamic realization of the state vector governing the option price dynamics. The estimators converge stably to a mixed‐Gaussian law and we develop feasible estimators for the limiting variance. We also provide semiparametric tests for the option price dynamics based on the distance between the spot volatility extracted from the options and one constructed nonparametrically from high‐frequency data on the underlying asset. Furthermore, we develop new tests for the day‐by‐day model fit over specific regions of the volatility surface and for the stability of the risk‐neutral dynamics over time. A comprehensive Monte Carlo study indicates that the inference procedures work well in empirically realistic settings. In an empirical application to S&P 500 index options, guided by the new diagnostic tests, we extend existing asset pricing models by allowing for a flexible dynamic relation between volatility and priced jump tail risk. Importantly, we document that the priced jump tail risk typically responds in a more pronounced and persistent manner than volatility to large negative market shocks.     

Generalized Method of Integrated Moments for High‐Frequency Data

We propose a semiparametric two‐step inference procedure for a finite‐dimensional parameter based on moment conditions constructed from high‐frequency data. The population moment conditions take the form of temporally integrated functionals of state‐variable processes that include the latent stochastic volatility process of an asset. In the first step, we nonparametrically recover the volatility path from high‐frequency asset returns. The nonparametric volatility estimator is then used to form sample moment functions in the second‐step GMM estimation, which requires the correction of a high‐order nonlinearity bias from the first step. We show that the proposed estimator is consistent and asymptotically mixed Gaussian and propose a consistent estimator for the conditional asymptotic variance. We also construct a Bierens‐type consistent specification test. These infill asymptotic results are based on a novel empirical‐process‐type theory for general integrated functionals of noisy semimartingale processes.     

基于高频数据的中国有色金属期货市场量价关系研究

根据Bessembinder和Seguin （1993）的研究成果,将成交量和持仓量分解为可预期部分和非可预期部分,并考虑了正负已实现半方差和成交量、持仓量的不同冲击对期货市场的不同影响,构建了量价关系基础模型、基于成交量和持仓量分解的量价关系模型和量价关系非对称模型,并利用中国铜铝期货高频数据分别对各模型进行实证分析。研究发现,中国有色金属期货市场的价格波动与成交量和成交相对增量均存在正向相关关系,与持仓量和持仓相对增量均存在负向相关关系。预期成交量和非预期成交量均对价格波动有正向影响,但非预期成交量对价格波动的影响更大;预期持仓量和非预期持仓量均对价格波动有负向影响,但非预期持仓量对价格波动的影响更大,即有色金属期货市场的价格波动主要是由代表新信息的非预期成交量和非预期持仓量引起。相比于下偏已实现半方差,成交量和持仓量对上偏已实现半方差有更强的解释力。正的成交量冲击比负的成交量冲击对价格波动的影响更大,持仓量亦是如此。     

Efficient Competition Through Cheap Talk: The Case of Competing Auctions

We consider a large market where auctioneers with private reservation values compete for bidders by announcing cheap‐talk messages. If auctioneers run efficient first‐price auctions, then there always exists an equilibrium in which each auctioneer truthfully reveals her type. The equilibrium is constrained efficient, assigning more bidders to auctioneers with larger gains from trade. The choice of the trading mechanism is crucial for the result. Most notably, the use of second‐price auctions (equivalently, ex post bidding) leads to the nonexistence of any informative equilibrium. We examine the robustness of our finding in various dimensions, including finite markets and equilibrium selection.     

EXcess Idle Time

We introduce a novel economic indicator, named excess idle time (EXIT), measuring the extent of sluggishness in financial prices. Under a null and an alternative hypothesis grounded in no‐arbitrage (the null) and market microstructure (the alternative) theories of price determination, we derive a limit theory for EXIT leading to formal tests for staleness in the price adjustments. Empirical implementation of the theory indicates that financial prices are often more sluggish than implied by the (ubiquitous, in frictionless continuous‐time asset pricing) semimartingale assumption. EXIT is interpretable as an illiquidity proxy and is easily implementable, for each trading day, using transaction prices only. By using EXIT, we show how to estimate structurally market microstructure models with asymmetric information.     

Uncertainty Shocks in a Model of Effective Demand

Can increased uncertainty about the future cause a contraction in output and its components? An identified uncertainty shock in the data causes significant declines in output, consumption, investment, and hours worked. Standard general‐equilibrium models with flexible prices cannot reproduce this comovement. However, uncertainty shocks can easily generate comovement with countercyclical markups through sticky prices. Monetary policy plays a key role in offsetting the negative impact of uncertainty shocks during normal times. Higher uncertainty has even more negative effects if monetary policy can no longer perform its usual stabilizing function because of the zero lower bound. We calibrate our uncertainty shock process using fluctuations in implied stock market volatility, and show that the model with nominal price rigidity is consistent with empirical evidence from a structural vector autoregression. We argue that increased uncertainty about the future likely played a role in worsening the Great Recession. The economic mechanism we identify applies to a large set of shocks that change expectations of the future without changing current fundamentals.     

Information in Securities Markets: Kyle Meets Glosten and Milgrom

This paper analyzes models of securities markets with a single strategic informed trader and competitive market makers. In one version, uninformed trades arrive as a Brownian motion and market makers see only the order imbalance, as in Kyle (1985). In the other version, uninformed trades arrive as a Poisson process and market makers see individual trades. This is similar to the Glosten–Milgrom (1985) model, except that we allow the informed trader to optimize his times of trading. We show there is an equilibrium in the Glosten–Milgrom‐type model in which the informed trader plays a mixed strategy (a point process with stochastic intensity). In this equilibrium, informed and uninformed trades arrive probabilistically, as Glosten and Milgrom assume. We study a sequence of such markets in which uninformed trades become smaller and arrive more frequently, approximating a Brownian motion. We show that the equilibria of the Glosten–Milgrom model converge to the equilibrium of the Kyle model.     

Marriage,Labor Supply,and Home Production

We develop a search model of marriage where men and women draw utility from private consumption and leisure, and from a non‐market good that is produced in the home using time resources. We condition individual decisions on wages, education, and an index of family attitudes. A match‐specific, stochastic bliss shock induces variation in matching given wages, education, and family values, and triggers renegotiation and divorce. Using BHPS (1991–2008) data, we take as given changes in wages, education, and family values by gender, and study their impact on marriage decisions and intrahousehold resource allocation. The model allows to evaluate how much of the observed gender differences in labor supply results from wages, education, and family attitudes. We find that family attitudes are a strong determinant of comparative advantages in home production of men and women, whereas education complementarities induce assortative mating through preferences.     

Entry and Exit in OTC Derivatives Markets

We develop a parsimonious model to study the equilibrium and socially optimal decisions of banks to enter, trade in, and possibly exit, an OTC market. Although we endow all banks with the same trading technology, banks' optimal entry and trading decisions endogenously lead to a realistic market structure composed of dealers and customers with distinct trading patterns. We decompose banks' entry incentives into incentives to hedge risk and incentives to make intermediation profits. We show that dealer banks enter more than is socially optimal. In the face of large negative shocks, they may also exit more than is socially optimal when markets are not perfectly resilient.     

Consumer Effort in Promotional Incentives

Consumers need to exert effort to use the incentives provided in a promotion campaign. This effort is critical in the consumers’ decision process and for the success of the campaign. We develop a model of consumer redemption effort that is general in nature and is applicable to coupons, rebates, and other price‐discrimination devices. We find that the impact of redemption effort is quite intricate on a firm’s profit and consumers’ surplus. We find that there are cases where a firm would like to operate in a low redemption cost environment while consumers would be better off with higher costs. We identify cases where price can remain the same with or without the promotion. In these cases, it is possible that the surplus for each individual consumer is higher when a firm price discriminates and improves its profit. Our results indicate that a firm would rather have variation in consumer redemption costs than to have variation in consumer valuations. However, in a market with low valuation variability, consumer redemption cost variability is essential for an efficient promotion campaign. Therefore, the markets that naturally have a lot of variability in consumer valuations should be the ones targeted for online promotion programs that reduce consumer effort levels, not the markets with low variability.     

Using Adaptive Sparse Grids to Solve High‐Dimensional Dynamic Models

We present a flexible and scalable method for computing global solutions of high‐dimensional stochastic dynamic models. Within a time iteration or value function iteration setup, we interpolate functions using an adaptive sparse grid algorithm. With increasing dimensions, sparse grids grow much more slowly than standard tensor product grids. Moreover, adaptivity adds a second layer of sparsity, as grid points are added only where they are most needed, for instance, in regions with steep gradients or at nondifferentiabilities. To further speed up the solution process, our implementation is fully hybrid parallel, combining distributed and shared memory parallelization paradigms, and thus permits an efficient use of high‐performance computing architectures. To demonstrate the broad applicability of our method, we solve two very different types of dynamic models: first, high‐dimensional international real business cycle models with capital adjustment costs and irreversible investment; second, multiproduct menu‐cost models with temporary sales and economies of scope in price setting.     

Statistical Properties of Microstructure Noise

We study the estimation of (joint) moments of microstructure noise based on high frequency data. The estimation is conducted under a nonparametric setting, which allows the underlying price process to have jumps, the observation times to be irregularly spaced, and the noise to be dependent on the price process and to have diurnal features. Estimators of arbitrary orders of (joint) moments are provided, for which we establish consistency as well as central limit theorems. In particular, we provide estimators of autocovariances and autocorrelations of the noise. Simulation studies demonstrate excellent performance of our estimators in the presence of jumps, irregular observation times, and even rounding. Empirical studies reveal (moderate) positive autocorrelations of microstructure noise for the stocks tested.     

The Decision of the Supply Chain Executive to Support or Impede Supply Chain Integration: A Multidisciplinary Behavioral Agency Perspective*

Applying the behavioral agency model developed by Wiseman and Gomez‐Mejia (1998) , this article analyzes human resource factors that induce supply chain executives (SCEs) to make decisions that foster or hinder supply chain integration. We examine two internal sources (compensation and employment risk) and one external source (environmental volatility) of risk bearing that can make SCEs more reluctant to make the decision to promote supply chain integration. We argue and empirically confirm the notion that an employment and compensation system that increases SCE risk bearing reduces the SCE's willingness to make risky decisions and thus discourages supply chain integration. We also reveal that this negative relationship becomes stronger under conditions of high environmental volatility. In addressing the “so what?” question, we found empirical support for the hypothesis that supply chain integration positively influences operational performance. Even though this decision has a positive value for the firm, we showed that SCEs discourage supply chain integration when they face higher risk bearing. Hypotheses are tested using a combination of primary survey data and archival measures in a sample of 133 Spanish firms.     

The Role of Contracts on Quality and Returns to Quality in Offshore Software Development Outsourcing

In this study, we examine how the different incentive structures inherent in two primary contract types—time and materials (T&M) and fixed price (FP)—influence the quality provided by the vendor in the software development outsourcing industry. We argue that the incentive structure of FP contracts motivates a vendor to be more efficient in the software development process, which results in higher quality as compared to projects executed under a T&M contract. We thus argue that vendors consistently staff FP projects with better trained personnel because they face the most risk on these contracts, resulting in better outcomes on these projects. We extend our analysis to propose that providing higher quality is associated with higher profit margins for the vendor only for FP contracts. We develop and test these hypotheses on data collected from 100 software projects completed by a leading Indian offshore vendor. The results provide strong support for our fundamental thesis that the drivers of and returns to quality vary by contract type. We discuss the implications of our research for both researchers and practitioners.     

指令驱动市场中非知情交易者的最优交易策略

在非对称信息下,综合非知情交易者对资产价值的预期、私人估值及资产价值波动,构造指令驱动市场价格形成的动态模型,给出非知情交易者指令提交策略的解析解,并依此描述了非知情交易者对资产价值预期的动态更新过程.研究发现:私人估值和资产价值波动通过影响非知情交易者最优策略,使得市场进入不同均衡状态;在每个均衡状态下,非知情交易者根据资产价值的预期变化更新交易策略,进而引起知情交易者策略调整,特别地,使得知情交易者被挤出市场成为可能.进一步分析表明,私人估值、资产价值波动及知情交易者比例对市场流动性的影响依赖于每个均衡中限价指令执行风险的差异.     

一类高新技术企业专利权价值的实物期权评估方法——基于跳扩散过程和随机波动率的美式期权的建模与模拟

由于经典的Black-Scholes期权定价模型的假设忽略了突发事件对资产价格的影响和"波动率微笑"对期权价值的影响而与实际情形往往存在偏差,因此学者们对Black-Scholes模型的改进则主要分别集中在带跳扩散过程的期权定价模型与具随机波动率的期权定价模型等两个方面,然而却少见将这两种模型结合起来的研究。本文首先在带跳扩散过程的期权定价模型与具随机波动率的期权定价模型的研究工作的基础上,建立了一种同时带跳扩散过程和具随机波动率的美式期权定价模型,并通过伊藤引理推导出了资产价格、随机波动率和期权满足的偏微分方程;然后,利用特征函数法和傅里叶变换导出了资产价格的随机分布,进而通过马尔科夫链方法给出了基于跳扩散过程和随机波动率的美式期权的数值解;最后,运用已建立的带跳扩散过程和随机波动率的美式期权定价模型对高新技术企业项目投资的专利权价值进行实物期权定价评估的案例研究,并对跳扩散强度参数和随机波动率参数进行敏感性分析,研究结果表明:将项目收益跳扩散过程和市场环境随机波动率加入到专利权实物期权定价模型中,可以有效避免专利权的期权价值被高估。     

投资者结构、交易失衡与商品期货市场的价格发现效率

基于上海期货交易所铝、铜、橡胶和燃料油期货合约两种投资者结构的分账户数据,分析不同类型投资者交易失衡对我国商品期货市场收益、价格发现与波动的影响。结果表明:(1)个人投资者和投机者的交易失衡暗示其寻找最佳买多或卖空时点的能力不足,存在明显的过度自信、过度投机和羊群行为,加剧商品期货价格波动;(2)机构投资者和套期保值者常常表现出与个人投资者和投机者相反的交易意愿,他们能够较好地把握买入与卖出时机,且更愿意冒险持有头寸,有助于缓解商品期货价格波动;(3)商品期货价格的变动趋势表明机构投资者和套期保值者具有一定的信息优势,能够在一定程度上预测商品期货价格的未来走势,他们极其乐观或悲观的交易失衡可以向商品期货市场传递有效的信息和时间信号。因此,提高机构投资者和套期保值者的成交量(持仓量)比例,优化投资者结构,可以有效促进我国商品期货市场的价格发现,降低期货价波动风险。此外,大型投机者的交易活动也可以在一定程度上缓解商品期货价格波动。     

Idiosyncratic volatility,executive compensation and corporate governance: examination of the direct and moderate effects

Entrenchment of private benefits by the CEO or dominant owners can lead corporations to avoid riskier but more private benefits resulting in greater idiosyncratic volatility and information flow trading. Using a unique database of 806 listed firms, we investigate the impact of CEO compensation and corporate governance on idiosyncratic volatility and information flow trading. We find strong and robust evidence that equity-based (fixed income) CEO compensation is negatively (positively) related to volatility and information trading. Incorporating an agent principal–principal perspective into our models of managerial discretion provides us with an accurate prediction of how the proportion of CEO compensation and the degree of entrenchment will influence risk-taking decisions as well as how equity-based compensation interacts with related-party transaction and ownership dispersion to influence stock volatility. Finally, we find that idiosyncratic volatility and information flow trading are also affected by CEO compensation and corporate governance, which act as instrumental variables, while subject to environmental variants and the jointly determined.     

Supply Chain Conflict Due to Store Brands: The Value of Wholesale Price Commitment in a Retail Supply Chain*

Store brands are of increasing importance in retail supply chains, often causing channel conflict, as the retailer's product directly competes with the manufacturer's national brand. Extant research on the resulting channel interactions either assumes the national brand manufacturer can credibly commit to maintaining a wholesale price or that he lacks such ability. However, these two scenarios imply very different supply chain interactions, as only a national brand manufacturer with commitment ability can strategically adjust a national brand wholesale price to prevent a store brand introduction by the retailer. We specifically analyze the impact of this assumption on the manufacturer, the retailer, and the customers. We determine when long‐term contracts that provide the manufacturer with such commitment ability can improve supply chain profitability.     

Necessity Is the Mother of Invention: Input Supplies and Directed Technical Change

This study provides causal evidence that a shock to the relative supply of inputs to production can (1) affect the direction of technological progress and (2) lead to a rebound in the relative price of the input that became relatively more abundant (the strong induced‐bias hypothesis). I exploit the impact of the U.S. Civil War on the British cotton textile industry, which reduced supplies of cotton from the Southern United States, forcing British producers to shift to lower‐quality Indian cotton. Using detailed new data, I show that this shift induced the development of new technologies that augmented Indian cotton. As these new technologies became available, I show that the relative price of Indian/U.S. cotton rebounded to its pre‐war level, despite the increased relative supply of Indian cotton. This is the first paper to establish both of these patterns empirically, lending support to the two key predictions of leading directed technical change theories.