Simple Finite Horizon Bubbles Robust to Higher Order Knowledge

An asymmetric information model of a finite horizon “nth order” rational asset price bubble is presented, where (all agents know that)ⁿ the asset is worthless. Also, the model has only two agents, so the first order version of the bubble is simpler than other first order bubbles in the literature.     

资产价格泡沫何时发生崩溃？——基于LPPL模型的在中国金融市场上的有效性检验

本研究基于对数周期幂律模型LPPL（Log Periodic Power Law Model），针对金融时间序列将一维价格波动翻译成反映市场泡沫微观结构的多维变量。通过对多维变量的动态监测，把握市场中泡沫的演变并预测泡沫破裂的临界点，从而有效降低或防范金融资产泡沫破裂所导致的风险。为检验LPPL模型在中国金融市场中的适用性，本文分别使用上证综指、四个期货连续合约以及两支个股检验模型效果。实证结果表明当金融资产价格序列呈现超指数加速震荡上升或下降时，该模型能获得稳定的估计效果，有效预测泡沫破裂临界时点。     

金融泡沫与企业投资

研究了金融泡沫对企业投资策略影响的微观机理.在投资项目市场价值中引入金融泡沫因子,建立起企业的投资决策模型,研究了泡沫对投资概率的影响,并对泡沫持续期、决策者视窗和融资规模和方式与金融泡沫对投资的共同影响进行了分析.结果表明:正泡沫对投资具有推动作用,负泡沫具有抑制作用;正泡沫期间进行的投资长期具有折价趋势,负泡沫期间进行的投资价值有上升趋势;正泡沫持续期越长,投资的可能性越小;负泡沫的持续期越长,投资可能性越大;在正泡沫期,若决策者越短视,立即投资的动机越强,企业偏向于出售股权进行投资;在负泡沫期,若决策者越短视,投资将会推迟,企业偏向于以其他融资方式进行投资.     

金融泡沫与企业投资

研究了金融泡沫对企业投资策略影响的微观机理.在投资项目市场价值中引入金融泡沫因子,建立起企业的投资决策模型,研究了泡沫对投资概率的影响,并对泡沫持续期、决策者视窗和融资规模和方式与金融泡沫对投资的共同影响进行了分析.结果表明:正泡沫对投资具有推动作用,负泡沫具有抑制作用;正泡沫期间进行的投资长期具有折价趋势,负泡沫期间进行的投资价值有上升趋势;正泡沫持续期越长,投资的可能性越小;负泡沫的持续期越长,投资可能性越大;在正泡沫期,若决策者越短视,立即投资的动机越强,企业偏向于出售股权进行投资;在负泡沫期,若决策者越短视,投资将会推迟,企业偏向于以其他融资方式进行投资.     

中国股市泡沫破裂临界时点动态置信区间研究

本文在对数周期幂率(LPPL)模型基础上,分别构建了“滚动窗口”以及“固定起点并移动终点”两种泡沫临界点动态置信区间构建方法,并以中国股市沪深300指数在2007年和2015年发生的两次大牛市股市崩盘为研究对象,采用两种新的方法进行样本外预测,计算出泡沫破裂的临界时点以及动态置信区间。研究结果表明,随着时间的不断推移,泡沫破裂临界时点的置信区间基本上能稳定覆盖实际发生泡沫破裂的时点。相比单纯利用LPPL模型预测临界时点方法,置信区间法能更好地克服预测临界时点随机性的情况,并能很好显示股市泡沫临界区间的变化轨迹,为投资者风险管理提供参考。     

A Robust Model of Bubbles With Multidimensional Uncertainty

Observers often interpret boom–bust episodes in asset markets as speculative frenzies where asymmetrically informed investors buy overvalued assets hoping to sell to a greater fool before the crash. Despite its intuitive appeal, however, this notion of speculative bubbles has proven difficult to reconcile with economic theory. Existing models have been criticized on the basis that they assume irrationality, that prices are somewhat unresponsive to sales, or that they depend on fragile, knife‐edge restrictions. To address these issues, I construct a rational version of Abreu and Brunnermeier (2003), where agents invest growing endowments into an asset, fueling appreciation and eventual overvaluation. Riding bubbles is optimal as long as the growth rate of the bubble and the probability of selling before the crash are high enough. This probability increases with the amount of noise in the economy, as random short‐term fluctuations make it difficult for agents to infer information from prices.     

Quantitative Risk Estimation for a Legionella pneumophila Infection Due to Whirlpool Use

Quantitative microbiological risk assessment was used to quantify the risk associated with the exposure to Legionella pneumophila in a whirlpool. Conceptually, air bubbles ascend to the surface, intercepting Legionella from the traversed water. At the surface the bubble bursts into dominantly noninhalable jet drops and inhalable film drops. Assuming that film drops carry half of the intercepted Legionella, a total of four (95% interval: 1–9) and 4.5×10⁴ (4.4×10⁴ – 4.7×10⁴) cfu/min were estimated to be aerosolized for concentrations of 1 and 1,000 legionellas per liter, respectively. Using a dose‐response model for guinea pigs to represent humans, infection risks for active whirlpool use with 100 cfu/L water for 15 minutes were 0.29 (～0.11–0.48) for susceptible males and 0.22 (～0.06–0.42) for susceptible females. A L. pneumophila concentration of ≥1,000 cfu/L water was estimated to nearly always cause an infection (mean: 0.95; 95% interval: 0.9–～1). Estimated infection risks were time‐dependent, ranging from 0.02 (0–0.11) for 1‐minute exposures to 0.93 (0.86–0.97) for 2‐hour exposures when the L. pneumophila concentration was 100 cfu/L water. Pool water in Dutch bathing establishments should contain <100 cfu Legionella/L water. This study suggests that stricter provisions might be required to assure adequate public health protection.     

资产泡沫、技术创新与经济增长

本文从理论和实证两个角度研究了资产泡沫发生、技术创新与经济增长之间的相关性。理论方面,本文构建了符合我国经济典型事实的熊彼特经济增长模型。模型中,企业家在为研发筹集资金时面临融资约束。由于融资约束的存在导致资本市场的资金供过于求,发生资产泡沫可促进企业平均的研发投入增加,研发成功的概率相应上升。实证方面,本文采用FF-TVP-SV-VAR和TVAR模型以及我国2000-2016年的月度数据分别对理论分析得出的结论进行检验。实证结果表明,资产泡沫发生可以促进技术创新,但该效应依赖于融资约束。此外,本文识别了融资约束的两个门限值。低于下限值时,资产泡沫可通过技术创新效应促进经济增长;高于下限值时,资产泡沫的技术创新效应较弱,因而对经济增长产生负向作用。     

Measuring resetting of brain dynamics at epileptic seizures: application of global optimization and spatial synchronization techniques

Epileptic seizures are manifestations of intermittent spatiotemporal transitions of the human brain from chaos to order. Measures of chaos, namely maximum Lyapunov exponents (STL _max ), from dynamical analysis of the electroencephalograms (EEGs) at critical sites of the epileptic brain, progressively converge (diverge) before (after) epileptic seizures, a phenomenon that has been called dynamical synchronization (desynchronization). This dynamical synchronization/desynchronization has already constituted the basis for the design and development of systems for long-term (tens of minutes), on-line, prospective prediction of epileptic seizures. Also, the criterion for the changes in the time constants of the observed synchronization/desynchronization at seizure points has been used to show resetting of the epileptic brain in patients with temporal lobe epilepsy (TLE), a phenomenon that implicates a possible homeostatic role for the seizures themselves to restore normal brain activity. In this paper, we introduce a new criterion to measure this resetting that utilizes changes in the level of observed synchronization/desynchronization. We compare this criterion’s sensitivity of resetting with the old one based on the time constants of the observed synchronization/desynchronization. Next, we test the robustness of the resetting phenomena in terms of the utilized measures of EEG dynamics by a comparative study involving STL _max , a measure of phase (φ _max ) and a measure of energy (E) using both criteria (i.e. the level and time constants of the observed synchronization/desynchronization). The measures are estimated from intracranial electroencephalographic (iEEG) recordings with subdural and depth electrodes from two patients with focal temporal lobe epilepsy and a total of 43 seizures. Techniques from optimization theory, in particular quadratic bivalent programming, are applied to optimize the performance of the three measures in detecting preictal entrainment. It is shown that using either of the two resetting criteria, and for all three dynamical measures, dynamical resetting at seizures occurs with a significantly higher probability (α=0.05) than resetting at randomly selected non-seizure points in days of EEG recordings per patient. It is also shown that dynamical resetting at seizures using time constants of STL _max synchronization/desynchronization occurs with a higher probability than using the other synchronization measures, whereas dynamical resetting at seizures using the level of synchronization/desynchronization criterion is detected with similar probability using any of the three measures of synchronization. These findings show the robustness of seizure resetting with respect to measures of EEG dynamics and criteria of resetting utilized, and the critical role it might play in further elucidation of ictogenesis, as well as in the development of novel treatments for epilepsy.     

中国房地产市场投机泡沫实证分析

由于对国民经济具有明显的乘数带动效应,因此房地产业既可以拉动经济增长,也可能导致经济过热,进而常常成为政府宏观调控的首选对象和是否成功的主要标志之一。本文对中国房地产市场发展概况进行了简要分析,介绍了有关泡沫的经济学基本理论和研究,以及中国房地产市场是否存在泡沫的争论。在此基础上,本文重新定义了房地产基本价值、投机泡沫和泡沫度,并利用中国房地产的相关数据,对中国房地产基本价值、投机泡沫和泡沫度进行了实际计算,得出了中国房地产泡沫已经产生、而且比较严重的结论,并解释了中国房地产投机泡沫产生的主要原因。最后,提出了挤出房地产泡沫的若干政策,并特别指出,地方政府对中央政府的有关政策能否“上令下达,不打埋伏”是挤出房地产市场泡沫的关键所在。     

Statistical Approach to Identify Threshold and Point of Departure in Dose–Response Data

The study presents an integrated, rigorous statistical approach to define the likelihood of a threshold and point of departure (POD) based on dose–response data using nested family of bent‐hyperbola models. The family includes four models: the full bent‐hyperbola model, which allows for transition between two linear regiments with various levels of smoothness; a bent‐hyperbola model reduced to a spline model, where the transition is fixed to a knot; a bent‐hyperbola model with a restricted negative asymptote slope of zero, named hockey‐stick with arc (HS‐Arc); and spline model reduced further to a hockey‐stick type model (HS), where the first linear segment has a slope of zero. A likelihood‐ratio test is used to discriminate between the models and determine if the more flexible versions of the model provide better or significantly better fit than a hockey‐stick type model. The full bent‐hyperbola model can accommodate both threshold and nonthreshold behavior, can take on concave up and concave down shapes with various levels of curvature, can approximate the biochemically relevant Michaelis–Menten model, and even be reduced to a straight line. Therefore, with the use of this model, the presence or absence of a threshold may even become irrelevant and the best fit of the full bent‐hyperbola model be used to characterize the dose–response behavior and risk levels, with no need for mode of action (MOA) information. Point of departure (POD), characterized by exposure level at which some predetermined response is reached, can be defined using the full model or one of the better fitting reduced models.     

When bubbles burst: Mimetic insights into minimising confidentiality breaches

This paper presents a theoretical model to help managers visualise and manage confidential situations more effectively. The model metaphorically likens a confidential setting to the properties of a soap bubble, e.g. elastic expansion or contraction, minimal surface area to contain a given volume, fragility, surface tension, pressure, stress, strain and the potential for bursting thereby releasing the contents to the external environment. We explore the conceptual developments in two phases. Firstly, looking at how a bubble and confidential scenario form and grow. Secondly, we consider how a bubble may burst and map these forces to ways in which confidentiality may be breached. Many attributes are mapped, the key ones being: the embedded value within the system, the criticality of maintaining confidentiality, increasing pressure, the corresponding stress/strain dynamics and the levels of trust between stakeholders. Key research propositions are derived from the model which aims to minimise the risk of a confidentiality breach.     

MANAGING CREDIT BUBBLES

We study a dynamic economy where credit is limited by insufficient collateral and, as a result, investment and output are too low. In this environment, changes in investor sentiment or market expectations can give rise to credit bubbles, that is, expansions in credit that are backed not by expectations of future profits (i.e., fundamental collateral), but instead by expectations of future credit (i.e., bubbly collateral). Credit bubbles raise the availability of credit for entrepreneurs: this is the crowding‐in effect. However, entrepreneurs must also use some of this credit to cancel past credit: this is the crowding‐out effect. There is an “optimal” bubble size that trades off these two effects and maximizes long‐run output and consumption. The equilibrium bubble size depends on investor sentiment, however, and it typically does not coincide with the “optimal” bubble size. This provides a new rationale for macroprudential policy. A credit management agency (CMA) can replicate the “optimal” bubble by taxing credit when the equilibrium bubble is too high and subsidizing credit when the equilibrium bubble is too low. This leaning‐against‐the‐wind policy maximizes output and consumption. Moreover, the same conditions that make this policy desirable guarantee that a CMA has the resources to implement it.     

基于因素嵌入的非理性资产价格泡沫生成及膨胀演化研究

近几年,随着资产价格泡沫现象的频繁发生,实业家和学者开始重点关注泡沫生成、膨胀的演化过程。本文通过引入导致预期发生变化的三个影响因素(过度自信、资产缺乏弹性、流动性过剩),扩展了现有的噪声交易者(DSSW)模型,揭示由噪声交易者对资产价格预期发生变化而造成的非理性资产价格泡沫的生成及膨胀机理,分析得出:三个影响因素促使资产价格预期发生变化,进而导致非理性资产价格泡沫生成及膨胀;并利用MATLAB软件对非理性资产价格泡沫膨胀过程进行模拟,分析得出:噪声交易者占比、非知情噪声交易者占比、过度自信影响因子、资产缺乏弹性影响因子、流动性过剩影响因子越大,非理性资产价格泡沫的膨胀速度越快、波动幅度越大,这对防止泡沫膨胀速度过快、过大有一定的参考价值。     

Discrete–Time Approximations of the Holmström–Milgrom Brownian–Motion Model of Intertemporal Incentive Provision

This paper studies the relation between discrete–time and continuous–time principal–agent models. We derive the continuous–time model as a limit of discrete–time models with ever shorter periods and show that optimal incentive schemes in the discrete–time models approximate the optimal incentive scheme in the continuous model, which is linear in accounts. Under the additional assumption that the principal observes only cumulative total profits at the end and the agent can destroy profits unnoticed, an incentive scheme that is linear in total profits is shown to be approximately optimal in the discrete–time model when the length of the period is small.     

基于理性预期均衡框架下的价格泡沫与过度反应研究

基于理性预期均衡框架,分别在私人信息外生和内生获取的条件下研究知情交易者对新信息过度反应与价格泡沫之间的联系。研究发现：在私人信息外生获取的情况下,知情交易者对新信息过度反应会提高价格信息量。在私人信息内生获取的情况下,过度反应挤出了私人信息的生产,导致价格信息量降低,价格泡沫由此形成,此时流动性可能呈先降低后提高的U型变化。这为管理层加强私人信息披露和弱化投资者的过度反应程度提供了依据。     

Nonspeculative Bubbles in Experimental Asset Markets: Lack of Common Knowledge of Rationality vs. Actual Irrationality

We report the results of an experiment designed to study the role of speculation in the formation of bubbles and crashes in laboratory asset markets. In a setting in which speculation is not possible, bubbles and crashes are observed. The results suggest that the departures from fundamental values are not caused by the lack of common knowledge of rationality leading to speculation, but rather by behavior that itself exhibits elements of irrationality. Much of the trading activity that accompanies bubble formation, in markets where speculation is possible, is due to the fact that there is no other activity available for participants in the experiment.     

Inferential Theory for Factor Models of Large Dimensions

This paper develops an inferential theory for factor models of large dimensions. The principal components estimator is considered because it is easy to compute and is asymptotically equivalent to the maximum likelihood estimator (if normality is assumed). We derive the rate of convergence and the limiting distributions of the estimated factors, factor loadings, and common components. The theory is developed within the framework of large cross sections (N) and a large time dimension (T), to which classical factor analysis does not apply. We show that the estimated common components are asymptotically normal with a convergence rate equal to the minimum of the square roots of N and T. The estimated factors and their loadings are generally normal, although not always so. The convergence rate of the estimated factors and factor loadings can be faster than that of the estimated common components. These results are obtained under general conditions that allow for correlations and heteroskedasticities in both dimensions. Stronger results are obtained when the idiosyncratic errors are serially uncorrelated and homoskedastic. A necessary and sufficient condition for consistency is derived for large N but fixed T.     

Anchoring Economic Predictions in Common Knowledge

The paper examines within a unified methodology expectational coordination in a series of economic models. The methodology views the predictions associated with the Rational Expectations Hypothesis as reasonable whenever they can be derived from the more basic Common Knowledge Hypothesis. The paper successively considers a simple non‐noisy N‐dimensional model, standard models with “intrinsic” uncertainty, and reference intertemporal models with infinite horizon. It reviews existing results and suggests new ones. It translates the formal results into looser but economically intuitive statements, whose robustness, in the present state of knowledge, is tentatively ascertained.     

过度自信心理影响期货价格的数理模型分析

过度自信心理是金融市场中投资者的一种非理性心理,对金融产品价格有重要影响。本文结合期货市场的特征,建立了过度自信心理影响期货价格的数理模型。通过模型分析表明,过度自信心理会造成过度自信投机者和套利者合约交易量的增加,投机者和套利者的过度自信程度会影响期货均衡价格的走向,同时,过度自信会平抑由噪声交易造成的价格波动。最后,本文利用模拟的方法验证了上述结论。