A liquidity-based model for asset price bubbles

We provide a new liquidity-based model for financial asset price bubbles that explains bubble formation and bubble bursting. The martingale approach to modeling price bubbles assumes that the asset's market price process is exogenous and the fundamental price, the expected future cash flows under a martingale measure, is endogenous. In contrast, we define the asset's fundamental price process exogenously and asset price bubbles are endogenously determined by market trading activity. This enables us to generate a model that explains both bubble formation and bubble bursting. In our model, the quantity impact of trading activity on the fundamental price process—liquidity risk—is what generates price bubbles. We study the conditions under which asset price bubbles are consistent with no arbitrage opportunities and we relate our definition of the fundamental price process to the classical definition.     

中国房地产市场价格泡沫的检验与成因机理研究

本文使用Pesaran(2007)提出的CIPS面板单位根检验和Pedroni面板协整检验,对我国房地产价格是否存在泡沫等问题进行了研究。检验结果表明,房屋销售价格指数和租赁价格指数序列的单整阶数不相等,并且二者不存在协整关系,因此在样本期间内我国房地产价格存在泡沫。在此基础上,本文对我国房地产价格泡沫产生的原因进行了简要分析,并给出相应的政策建议。     

短期国际资本流动新趋势、对我国的影响及其防范

当前,全球资本流动总量小幅但不均衡回升,未来有可能缓慢增长;发展中国家资本市场的发展正在逐渐改变国际资本流动的结构;国际金融市场参与者的角色发生很大的变化;国际资本向新兴经济体特别是亚洲新兴经济体大量流动.在短期国际资本的持续冲击下,新兴经济体已有形成资产泡沫的风险,并且在未来仍有继续扩大的趋势.对于中国而言,热钱在中国的投机空间有限,短期内大规模持续流入的条件还不具备,温和流入并时有反复可能将成长期趋势.要摆脱国际热钱大规模流动带来的包括人民币升值压力在内的一系列困扰,必须采取疏堵结合的方式:一方面,采取有效的防御性措施,监控各类热钱,加强流入管制;另一方面,应重视疏导的作用,抑制泡沫膨胀,吸引中长期国际资本,防范和限制短期资本泛滥.     

中国会重蹈日本八十年代的覆辙吗

当前中国的经济形势与20世纪80年代后期的日本非常相似,本国货币持续地升值,资金大量涌入股市和房市,使股价房价大幅上涨。那么中国是否会重蹈日本的覆辙呢?比较分析表明中日有诸多不同的地方,中国处于高速增长期而日本经济处于平稳增长期,中国宏观政策稳健而日本宏观政策失当,日元大幅升值而人民币小幅缓慢升值,因此,日本泡沫破灭之后的长达十年之久的萧条不太可能在中国重演。     

Testing for differences in the tails of stock-market returns

In this paper, we use a database consisting of daily stock-market returns for 20 countries to test for similarities between the left and right tails of returns, as well as across countries. We estimate and test using the distribution of extreme returns over subsamples approach. Via Monte-Carlo simulations, we show that maximum-likelihood estimators are essentially unbiased, provided the size of subsamples is correctly chosen, and that the likelihood-ratio tests on parameters characterizing the behavior of extremes are correctly sized. For actual returns, we find that left and right tails behave very similarly. Across countries, we find that extremes are located at different levels and that their dispersion varies. The tail index, characterizing large extreme realizations, is found to be constant within each geographical group. We verify that the perception that left tails are heavier than right ones is not due to clustering of extremes. The failure to detect statistical significant differences is likely to be due to the relative infrequency of large extremes.     

基于持续期依赖马尔可夫转换模型的我国股市泡沫研究

使用持续期依赖马尔可夫转换模型,通过Gibbs抽样估计方法,对上海股票市场是否存在泡沫进行研究。结果表明,我国股票市场具有明显的持续期依赖特征。给出上海股票市场在样本期间内各时刻处于有泡沫状态的概率,发现在样本期间内有三个时段存在泡沫的概率超过了50%。     

资产价格泡沫与货币政策响应--基于Taylor规则的分析

本文从Taylor规则的分析角度出发,讨论资产价格泡沫与货币政策的关系.本文通过加入资本市场因素对Taylor规则进行了动态扩展,以研究1994年第1季度到2001年第4季度中国的货币政策是否对股市泡沫做出响应.本文的研究结论表明,在这一时期内中国的货币政策表现为一种不稳定的规则,中央银行并未运用利率政策抑制股市泡沫增长,在不经意间容忍了明显的股市泡沫.     

房地产基础价值及泡沫类型解析——以上海市为例

本文应用时变现值模型对上海商品房的基础价值进行了测算,在此基础上计算各时期商品房价格与价值的偏离值,通过对偏离值的统计检验证实存在房地产泡沫。结果表明:爆炸性泡沫并不存在;内生性泡沫和趋势性泡沫是构成实际泡沫的主要成分;内生性泡沫的影响要高于趋势性泡沫的影响。     

虚拟资本运行与经济泡沫形成

虚拟资本有其不同于实物资本的运行特点和运动轨迹 ,随着虚拟程度增加 ,其自身价格变动已越来越脱离了它所代表的实际资本的内在价值 ,更多取决于证券市场上的交易状况 ,取决于证券市场上投资者的预期与信心。而这种对虚拟资本的预期和信心远比对实际投资的预期和信心来得脆弱 ,不确定性更强。虚拟资本比实物资本大得多、多得多 ,因而 ,虚拟资本本来就是以泡沫形式存在的。货币供求机制和信用制度在较大程度上决定了虚拟资本向经济泡沫的传导过程。经济泡沫本质是虚拟价值增殖的过度膨胀 ,经济泡沫对经济的影响是多方面和多渠道的     

Asset price bubbles and crashes with near-zero-intelligence traders

Summary. We examine whether a simple agent-based model can generate asset price bubbles and crashes of the type observed in a series of laboratory asset market experiments beginning with the work of Smith, Suchanek and Williams (1988). We follow the methodology of Gode and Sunder (1993, 1997) and examine the outcomes that obtain when populations of zero-intelligence (ZI) budget constrained, artificial agents are placed in the various laboratory market environments that have given rise to price bubbles. We have to put more structure on the behavior of the ZI-agents in order to address features of the laboratory asset bubble environment. We show that our model of near-zero-intelligence traders, operating in the same double auction environments used in several different laboratory studies, generates asset price bubbles and crashes comparable to those observed in laboratory experiments and can also match other, more subtle features of the experimental data.Received: 15 July 2003, Revised: 28 September 2004, JEL Classification Numbers: D83, D84, G12. Correspondence to: John DuffyWe would like to thank an Anonymous referee, Guillaume Frechette, David Laibson, Al Roth and participants in Harvard Experimental and Behavioral Economics Workshop for their comments, and Charles Noussair for providing his data set.