资产价格波动对金融稳定的影响——基于中国数据的实证研究北大核心CSSCI

资产价格波动是影响金融稳定的重要因素。金融稳定不仅仅指银行信贷或汇率波动的稳定性,而是一个多维度的、能够全面衡量银行、证券、外汇以及宏观经济状况等金融相关变量稳定性的指标体系。本文在构建金融稳定指标体系的基础上,实证研究了我国资产价格波动对金融稳定的影响,结果表明,中国房地产销售价格和股票价格等资产价格显著影响金融稳定,且房地产、股票等资产价格的剧烈波动是引发金融不稳定的重要原因。为此,政策当局要充分意识到这一点,通过加大股票市场监管力度、建立股票市场和房地产市场的预警体系等手段来观测资产价格波动情况;同时,在制定货币政策时应高度关注资产价格,从而在一定程度上降低由资产价格剧烈波动引发金融危机的可能性。     

资产价格波动与金融稳定

研究资产价格波动与金融稳定之间的联系有很大意义,文章拟从资产价格波动对金融稳定的影响、资产价格波动对金融稳定影响的传导机制以及我国货币政策的反应几个方面进行论述。     

资产价格波动成因、测度以及对金融不平衡的影响

<正>一、资产价格对金融不平衡的影响无论是费雪的债务-通货紧缩理论还是Minsky的金融脆弱性假说,对金融不稳定的研究都涉及到了资产价格波动这一方面,对于债务—通缩理论,费雪认为通货紧缩是由信用不足引发信用危机,人们通过负债获得信用的扩张,信用扩张又引发资产价格波动,当信用危机发生时,经济衰退,物价下跌,资产价格也会下跌。而金融脆弱性理论则是从心里预期方面对金融不稳定进行分析,前面对于资产价格波动的分析     

论资产价格波动对银行业稳定性的影响

本文以金融稳定为研究目标,以资产价格波动为研究着眼点,分析了资产价格过度波动引发金融不稳定的特征。本文在进行相关理论和数理分析的基础上,通过大量实证数据和实证分析来反应实际问题。为了检验资产价格波动与银行体系稳定性,本文收集和选取大量的中国的时间序列数据,并利用Eviews、SPSS等研究工具检验了相关变量之间的影响效果,并结合实证分析的结果,提出相关的结论和对策建议。     

资产价格与货币政策目标选择研究

随着资产价格与货币政策的关系日益紧密,传统的货币政策目标与操作体系面临愈来愈多的挑战。资产价格往往有可能对实体经济产生巨大的影响,资产价格由膨胀到崩溃的急剧变化很可能引发长时间的经济衰退和通货紧缩,这就给宏观经济政策当局为了保证经济较为平稳健康发展而制定相关政策,尤其是货币政策,提出了新的问题和挑战。重点关注资产价格波动究竟对货币政策的传导以及效果有什么影响;传统的以保证物价稳定、国内外收支平衡等为目标的基础上,是否应该增加稳定资产价格或者防止资产价格泡沫等对于资产价格波动的关注,又该如何关注,可能存在哪些问题,这些问题越来越受到关注。在这样的背景下,就资产价格波动与货币政策的一些相关问题做了简单的阐述,并对金融资产价格对货币政策作用进行简单的理论分析。     

资产价格波动与银行系统稳定

本文主要研究资产价格波动与银行系统稳定之间的关系.有关金融危机的理论研究表明,资产价格波动与银行脆弱性之间存在很强的相关性.资产价格波动主要通过信贷风险渠道、市场风险渠道、经纪业务收入渠道、为附属机构注资的风险渠道及"第二回合"渠道等传导渠道,影响到银行系统的稳定.发生在斯堪的纳维亚和日本的银行危机证明,资产价格剧烈波动确实会造成严重的银行问题,因此为维持银行系统的稳定,监管当局应该密切关注资产价格可能出现的剧烈下跌对银行部门可能产生的风险,并以相应的方法应对.     

资产价格波动视角下的资产证券化影响金融稳定机制研究

资产证券化通过增加市场的流动性影响资产价格波动,进而从不同方面对金融体系产生冲击影响金融稳定。文章在分析这一逻辑关系的基础上,指出供给侧结构性改革为资产证券化这一金融创新提供新的发展机遇。提出利用资产证券化技术推进供给侧结构性改革,促进经济转型升级,同时维护金融稳定的政策建议。     

资产价格波动、金融稳定与货币政策选择

从内生角度来看,资产价格波动可能通过金融创新、银行信贷与流动性、微观主体行为等途径,引起金融不稳定和宏观经济波动。货币政策应适当关注资产价格及其波动,并选择合适的刺破资产价格泡沫的工具。目前,我国正处于经济持续发展、人民币不断升值和城市化不断推进的特殊时期,这意味着我国资产价格波动愈发频繁,应建立资产价格泡沫预警指标体系,为货币政策的制定和实施提供参考。尤其是为了防止房地产价格泡沫产生带来的危害,应考虑将房地产价格纳入CPI体系,为货币政策的制定和实施提供参考。     

资产价格波动与银行信贷的相互关系研究

本文研究了我国资产价格波动和银行信贷之间的关系,发现信贷对房地产市场的冲击要比对股市的冲击大,未来我国的金融风险集中在房地产市场。信贷政策需要保持平稳的信贷投放,才能减少资产价格波动的幅度以实现金融稳定。     

中国金融周期与工业产品价格波动的耦合效应研究

国际金融危机之后的近十多年来,全球资产价格经历了剧烈的波动,特别是工业领域普遍出现的产能过剩成为制约经济可持续发展的重要因素。在此背景下,金融周期与经济周期关系成为研究的焦点。随着中国资本市场的逐步成熟,商品期货市场已基本涵盖所有重要的工业产品,工业产品价格波动与金融周期之间的耦合效应愈加显著。通过分析金融周期与工业产品价格之间的影响机理,并采取模型和脉冲响应分析的实证方法,考察中国金融周期与工业产品价格的耦合效应。结果表明,在短期内金融供给与工业产品价格之间存在显著的正相关关系,且正向的冲击影响呈现逐步递减的特征。     

流动性视角下的非流通股定价策略分析

金融市场上的流动性对金融资产定价有重要作用。在Longstaff模型的基础上对“卖掉持有股票的权利”进行定价,可得出股票的流动性价格,进而得到非流通股的价格。通过分析可知非流通股的价格是禁售期的减函数,是流通股的增函数;股票的价格波动率越大,贷款利率与无风险利率的差越大,非流通股的价格是就越低;反之,非流通股的价格就越高。以我国股票市场的相关指数进行验证,上述结论依然成立。     

A generalized theoretical modelling approach for the assessment of economic-capital under asset market liquidity risk constraints

This paper proposes a concrete theoretical foundation and a new modelling framework that attempts to tackle the issue of market/liquidity risk and economic-capital estimation at a portfolio level by combining two mutual asset market/liquidity risk models. In essence, this study extends research literature related to the assessment of the asset market/liquidity risk by providing a generalized theoretical modelling underpinning that handle, from the same perspective, market and liquidity risks jointly and integrate both risks into a portfolio setting without a commensurate increase of statistical postulations. As such, we argue that market and liquidity risk components are correlated in most cases and can be integrated into one single market/liquidity framework that consists of two interrelated sub-components. The first component is attributed to the impact of adverse price movements and is modelled based on the concept of liquidity-adjusted value-at-risk framework, while the second component focuses on the risk of variation in transactions costs due to the bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. As such, the model comprises a new approach to contemplating the impact of time-varying volatility of the bid-ask spread and its upshot on the overall asset market/liquidity risk. The modelling framework can be constructive for financial service industries in emerging-economies and particularly in reinforcing rational economic-capital allocation in light of the aftermaths of the sub-prime financial crisis.     

Market Volatility and Feedback Effects from Dynamic Hedging

In this paper we analyze the manner in which the demand generated by dynamic hedging strategies affects the equilibrium price of the underlying asset. We derive an explicit expression for the transformation of market volatility under the impact of such strategies. It turns out that volatility increases and becomes time and price dependent. The strength of these effects however depends not only on the share of total demand that is due to hedging, but also significantly on the heterogeneity of the distribution of hedged payoffs. We finally discuss in what sense hedging strategies derived from the assumption of constant volatility may still be appropriate even though their implementation obviously violates this assumption.     

Global excess liquidity and asset prices in emerging countries: A PVAR approach

The overly accommodating monetary policy is often accused of creating surplus liquidity and bubbles on the asset markets. In particular, it could have contributed to strong capital inflows in emerging countries, which may have had a significant impact on financial stability in these countries, affecting domestic financing conditions and creating a risk of upward pressures on asset prices. We focus in this paper on the impact of global excess liquidity on goods and asset prices for a set of emerging market countries by estimating a panel VAR model. We define first global liquidity and highlight situations of excess liquidity. We then find that excess liquidity at global level has spillover effects on output and price levels in emerging countries. The impact on real estate, commodity and share prices in emerging countries is less clear.     

Rational speculative bubbles in the gold futures market: An application of dynamic factor analysis

The existence of speculative bubbles in financial markets has been a longstanding issue under debate. Many financial economists believe that, given the assumption of rational expectations and rational behavior of economic agents, an asset should be priced according to its “market fundamentals.” Others argue that self‐fulfilling rumors of market participants can influence asset prices as well. These self‐fulfilling rumors are initiated by events extraneous to markets and are often called bubbles. The rationality of both expectations and behavior often does not imply that the price of an asset be equal to its fundamental value. In other words, there can be rational deviations of the price from this value—rational bubbles. A rational bubble can arise when the actual market price depends positively on its own expected rate of change, as normally occurs in asset markets. Since agents forming rational expectations do not make systematic prediction errors, the positive relationship between price and its expected rate of change implies a similar relationship between price and its actual rate of change. Under such conditions, the arbitrary, self‐fulfilling expectation of price changes may drive actual price changes independently of market fundamentals; we refer to such a situation as a rational price bubble.¹ © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:79–108, 2001     

Option Pricing in Stochastic Volatility Models of the Ornstein-Uhlenbeck type

Stochastic volatility models of the Ornstein-Uhlenbeck type possess authentic capability of capturing some stylized features of financial time series. In this work we investigate this class of models from the viewpoint of derivative asset analysis. We discuss topics related to the incompleteness of this type of markets. In particular, for structure preserving martingale measures, we derive the price of simple European-style contracts in closed form. Furthermore, the range of viable prices is determined and an empirical application is presented.     

银行信贷和资产价格泡沫的联动性——基于动态贷款价值比的分析

投资者借贷投资是现代金融市场的常态。信息不对称及其带来的风险收益不对称和风险转移问题,会造成资产价格泡沫。文章引入贷款价值比进一步扩展了Allen-Gale模型,并用贷款价值比的动态变化来说明资产价格泡沫生成的内在机理及其所产生的影响;通过对贷款价值比动态调整的模拟得出:贷款价值比越大,资产价格泡沫越大。因此,降低贷款价值比是遏制资产价格泡沫膨胀的关键。     

EQUILIBRIUM STATE PRICES IN A STOCHASTIC VOLATILITY MODEL1

In a stochastic volatility model, the no-free-lunch assumption does not induce a unique arbitrage price because of market incompleteness. In this paper, we consider a contingent claim on the primitive asset, traded in zero net supply. Given a system of Arrow-Debreu state prices, we provide necessary and sufficient conditions for consistency with an intertemporal additive equilibrium model that we fully characterize. We show that the risk premia corresponding to the minimal martingale of Föllmer and Schweizer (1991) are consistent with logarithmic preferences, while the Hull and White model (1987) (volatility risk premium independent of the asset price) is consistent with a class of utility functions including constant relative risk aversion (CRRA) ones.     

INDIFFERENCE PRICES AND IMPLIED VOLATILITIES

We consider a general local‐stochastic volatility model and an investor with exponential utility. For a European‐style contingent claim, whose payoff may depend on either a traded or nontraded asset, we derive an explicit approximation for both the buyer's and seller's indifference prices. For European calls on a traded asset, we translate indifference prices into an explicit approximation of the buyer's and seller's implied volatility surfaces. For European claims on a nontraded asset, we establish rigorous error bounds for the indifference price approximation. Finally, we implement our indifference price and implied volatility approximations in two examples.     

Managed futures,positive feedback trading,and futures price volatility

A major issue in recent years is the role that large, managed futures funds and pools play in futures markets. Many market participants argue that managed futures trading increases price volatility due to the size of managed futures trading and reliance on positive feedback trading systems. The purpose of this study is to provide new evidence on the impact of managed futures trading on futures price volatility. A unique data set on managed futures trading is analyzed for the period 1 December 1988 through 31 March 1989. The data set includes the daily trading volume of large commodity pools for 36 different futures markets. Regression results are unequivocal with respect to the impact of commodity pool trading on futures price volatility. For the 72 estimated regressions (two for each market), the coefficient on commodity pool trading volume is significantly different from zero in only four cases. These results constitute strong evidence that, at least for this sample period, commodity pool trading is not associated with increases in futures price volatility. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 759–776, 1999