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.     

Foreign currency bubbles

This paper develops a new model for studying foreign currency exchange rate bubbles. The model constructed is a modification of the martingale based bubble approach of Jarrow et al. (Adv Math Finance 105–130, 2006; Math Finance 20(2):145–185, 2008). This model generates some new insights into our understanding of exchange rate bubbles and it can be utilized empirically to test for their existence. The new insights are: (1) exchange rate bubbles can be negative, in contrast to asset price bubbles, (2) exchange rate bubbles are caused by price level bubbles in either or both of the relevant countries’ currencies, and (3) price level bubbles decrease the expected inflation rate in the domestic economy.     

Relative asset price bubbles

In models of financial bubbles, the price of a stock is typically unbounded, and this plays a fundamental role in the analysis of finite horizon local martingale bubbles. It would seem that price bubbles do not apply to a priori bounded risky asset prices, such as bond prices. To avoid this limitation, to characterize, and to identify bond price mispricings consistent with an absence of arbitrage, we develop the concept of a relative asset price bubble. This notion uses a risky asset’s price as the numéraire instead of the money market account’s value. This change of numéraire generates some interesting mathematical complexities because many important numéraires, including risky bonds, can vanish with positive probability over the model’s horizon.     

Inferring fundamental value and crash nonlinearity from bubble calibration

Identifying unambiguously the presence of a bubble in an asset price remains an unsolved problem in standard econometric and financial economic approaches. A large part of the problem is that the fundamental value of an asset is, in general, not directly observable and it is poorly constrained to calculate. Further, it is not possible to distinguish between an exponentially growing fundamental price and an exponentially growing bubble price. In this paper, we present a series of new models based on the Johansen–Ledoit–Sornette (JLS) model, which is a flexible tool to detect bubbles and predict changes of regime in financial markets. Our new models identify the fundamental value of an asset price and a crash nonlinearity from a bubble calibration. In addition to forecasting the time of the end of a bubble, the new models can also estimate the fundamental value and the crash nonlinearity, meaning that identifying the presence of a bubble is enabled by these models. In addition, the crash nonlinearity obtained in the new models presents a new approach to possibly identify the dynamics of a crash after a bubble. We test the models using data from three historical bubbles ending in crashes from different markets. They are the Hong Kong Hang Seng index 1997 crash, the S&P 500 index 1987 crash (Black Monday) and the Shanghai Composite index 2009 crash. All results suggest that the new models perform very well in describing bubbles, forecasting their ending times and estimating fundamental value and the crash nonlinearity. The performance of the new models is tested under both the Gaussian residual assumption and non-Gaussian residual assumption. Under the Gaussian residual assumption, nested hypotheses with the Wilks' statistics are used and the p-values suggest that models with more parameters are necessary. Under the non-Gaussian residual assumption, we use a bootstrap method to obtain type I and II errors of the hypotheses. All tests confirm that the generalized JLS models provide useful improvements over the standard JLS model.     

中国房地产市场价格泡沫与空间传染效应

本文使用对数周期性幂律(Log Period Power Law, LPPL)模型对房地产市场价格泡沫进行测度,运用空间计量模型对我国房地产市场价格泡沫和空间传染效应进行研究。LPPL模型认为由价格泡沫产生并最终破裂的金融市场与地震系统具有很多相似之处,即金融资产的价格呈周期性变化规律,价格持续上涨到临界状态直至反转。本文采用2010年6月至2017年11月间我国100个城市的房地产市场数据对各城市房地产价格泡沫进行测度和物理/经济空间传染效应研究。研究发现,LPPL模型能够对我国100个城市房地产价格泡沫进行甄别且主要存在两种泡沫状态:正向泡沫(房价持续上升)和反转泡沫(房价整体下降却存在反转点)。各个城市(地区)房地产价格具有较强的空间传染性;存在正向泡沫区域的空间传染性相较反转泡沫区域更为明显,在考虑经济空间测度而不是物理空间测度的情况下,各城市间的空间传染性更强。与现有文献不同,我们发现反转泡沫区域的新房价格指数特别是二手房价格指数的上升对周边城市的房地产价格指数存在强烈的正向推高影响。最后,本文发现城市的房地产调控政策在一定程度上抑制了房价传统影响(比如信贷、新房、二手房价等)因素的推高影响,但各城市房地产价格之间的联动变化特征应该引起监管部门的注意。     

Risk premia,asset price bubbles,and monetary policy

We develop a dynamic general equilibrium asset pricing model with heterogeneous beliefs to study the effects of monetary policy on prices, risk premia, asset price bubbles, and financial stability. We propose a new framework for monetary policy with respect to bubbles. Because bubble risk premia arise from an interaction between disagreements among investors and dynamic trading constraints, under a non-accommodative monetary policy, liquidity adjusted risk and bubble risk premia increase. What matters for policy is the trading constrained fraction/mass of agents that disagree about fundamentals (i.e. optimists/pessimists). Accommodative policy can lead to a larger fraction of trading constrained agents that disagree, larger bubbles, and increased systemic risk. An implication of our results is that accommodative monetary policy in response to the Covid-19 crisis does not increase systemic risk due to asset price bubbles, as long as the policy keeps inflation under control.     

Speculative bubbles and the cross-sectional variation in stock returns

Evidence suggests that rational, periodically collapsing speculative bubbles may be pervasive in stock markets globally, but there is no research that considers them at the individual stock level. In this study we develop and test an empirical asset pricing model that allows for speculative bubbles to affect stock returns. We show that stocks incorporating larger bubbles yield higher returns. The bubble deviation, at the stock level as opposed to the industry or market level, is a priced source of risk that is separate from the standard market risk, size and value factors. We demonstrate that much of the common variation in stock returns that can be attributable to market risk is due to the co-movement of bubbles rather than being driven by fundamentals.     

Asset price bubbles: a survey

Why do asset price bubbles continue to appear in various markets? What types of events give rise to bubbles and why do arbitrage forces fail to quickly burst them? Do bubbles have real economic consequences and should policy makers do more to prevent them? This paper provides an overview of recent literature on bubbles, with significant attention given to behavioral models and rational models with frictions. The latest U.S. real estate bubble is described in the context of this literature.     

Fundamentals and bubbles in asset prices: Evidence from U.S. and Japanese asset prices

This paper investigates the existence and extent of non-fundamental bubbles in both U.S. and Japanese asset prices by employing a flexible empirical method which allows us to decompose asset prices into fundamental and non-fundamental bubble components. This study finds that a substantial fraction of U.S. and Japanese asset prices is accounted for by non-fundamental bubble components and that these asset prices overreact to non-fundamental bubble shocks. In addition, allowing for time-varying interest rates as another fundamental factor does not change any qualitative results about the role of non-fundamental bubble components. This suggests that the present value model fails to explain volatile asset price behavior even with time-varying interest rates. This paper was initially written when I was visiting Keio University in Japan. I benefited from several discussions with Mike Dothan, Pat Hess, and Steve LeRoy in my department, Takashi Kaneko, Yukitami Tsuji and Naoyuki Yoshino at Keio University, and Yong-Seok Park at the International University of Japan. Special thanks are due to the anonymous referee and the editor of this journal, who provided many useful and insightful comments that helped to improve the paper. This research was in part supported by a grant from the International Program Development.     

Speculation and price bubbles in the Korean and Japanese real estate markets

This article investigates the possibility of speculation having caused the prices of land and housing to deviate from their given long-run equilibrium levels in Korea and Japan. We modeled speculation by incorporating the expected future price into the demand equation. The existence of growing rational bubbles was tested on Korean and Japanese data using the standard econometric technique for estimating linear rational expectations models. Our analysis of the Korean annual data suggests that a growing rationale bubble existed during the 1974–1989 period, nominal or real. Estimation results of the same model using Japanese annual data also confirmed the existence of a bubble in land price. Contrary to our analysis of land price data, the evidence of the bubble was much less obvious in Korean annual housing price data. We therefore estimated the model using quarterly data and found that the existence of a bubble could not be established in housing prices. This finding was also consistent with the trend of the rent-to-value ratio series in apartment units. Our results need to be taken with caution because our approach suffers from the common econometric problem of possible mis-specification of the model and because of the small size of the sample.     

Are liquidity and corporate control priced by shareholders? Empirical evidence from Swiss dual class shares

Stadard asset pricing models generally exclude corporate control and liquidity considerations as joint explanatory factors of the stock price formation process. This empirical study investigates their influence on Swiss Bearer and Registered share prices issued by the same firm. It is shown that the statistical properties of both shares' returns differ without implying profitable arbitrage opportunities. A multifactor model of the ‘premium’ between Bearer and Registered stock prices is then proposed and tested. The results show that the freely negotiable equity book value, the existence of dominant shareholder positions and ownership transfer regime changes are significant variables in explaining the dual class share price differential.     

Conditional risk premia in currency markets and other asset classes

The downside risk capital asset pricing model (DR-CAPM) can price the cross section of currency returns. The market-beta differential between high and low interest rate currencies is higher conditional on bad market returns, when the market price of risk is also high, than it is conditional on good market returns. Correctly accounting for this variation is crucial for the empirical performance of the model. The DR-CAPM can jointly rationalize the cross section of equity, equity index options, commodity, sovereign bond and currency returns, thus offering a unified risk view of these asset classes. In contrast, popular models that have been developed for a specific asset class fail to jointly price other asset classes.     

Super-Exponential RE bubble model with efficient crashes

We propose a dynamic Rational Expectations (RE) bubble model of prices, combining a geometric random walk with separate crash (and rally) discrete jump distributions associated with positive (and negative) bubbles. Crashes tend to efficiently bring back excess bubble prices close to a “normal” process. Then, the RE condition implies that the excess risk premium of the risky asset exposed to crashes is an increasing function of the amplitude of the expected crash, which itself grows with the bubble mispricing: hence, the larger the bubble price, the larger its subsequent growth rate. This positive feedback of price on return is the archetype of super-exponential price dynamics. We use the RE condition to estimate the real-time crash probability dynamically through an accelerating probability function depending on the increasing expected return. After showing how to estimate the model parameters, we obtain a closed-form approximation for the optimal investment that maximizes the expected log of wealth (Kelly criterion) for the risky bubbly asset and a risk-free asset. We demonstrate, on seven historical crashes, the promising outperformance of the method compared to a 60/40 portfolio, the classic Kelly allocation, and the risky asset, and how it mitigates jumps, both positive and negative.     

Future labor income growth and the cross-section of equity returns

This paper examines the equilibrium relation between future labor income growth and expected asset returns; it proposes revisions in the expectation of future labor income growth as a macroeconomic state variable and suggests a three-factor model, including a factor related to this variable, along with the consumption growth factor and the market factor. The proposed future labor income growth factor is positively associated with the Fama-French factors and subsumes their explanatory power in explaining the cross-section of stock returns. These results provide a possible economic explanation for the roles of the Fama-French factors: they are compensation for higher exposure to the risk related to changes in the value of human capital. This paper also compares the performance of the proposed three-factor model with other competing models and finds that the proposed model specification better captures cross-sectional variation in average returns than any of the competing asset pricing models considered.     

Bubbles,Fads and Stock Price Volatility Tests: A Partial Evaluation

This is a summary and interpretation of some of the literature on stock price volatility that was stimulated by Leroy and Porter 28 and Shiller 40 . It appears that neither small-sample bias, rational bubbles nor some standard models for expected returns adequately explain stock price volatility. This suggests a role for some nonstandard models for expected returns. One possibility is a “fads” model in which noise trading by naive investors is important. At present, however, there is little direct evidence that such fads play a significant role in stock price determination.     

Are There Rational Bubbles in REITs? New Evidence from a Complex Systems Approach

This study applies a complex systems approach to test for the presence of rational bubbles in the Equity REITs market. The applied model is based on theoretical implications of the evolution of prices under rational bubble regimes. The advantage of the approach is twofold. The model is able to detect rational bubbles while they rise and to predict the most likely time of their collapse. We apply the model to daily price data on U.S. Equity REITs from 1989 to 2011. Our findings suggest the existence of a bubble for the period of 2003 to 2007. Tests for sub-markets reveal that the bubble developed in the Residential REITs market, but not in the Office REITs market.     

Inexperienced investors and bubbles

We use mutual fund manager data from the technology bubble to examine the hypothesis that inexperienced investors play a role in the formation of asset price bubbles. Using age as a proxy for managers’ investment experience, we find that around the peak of the technology bubble, mutual funds run by younger managers are more heavily invested in technology stocks, relative to their style benchmarks, than their older colleagues. Furthermore, young managers, but not old managers, exhibit trend-chasing behavior in their technology stock investments. As a result, young managers increase their technology holdings during the run-up, and decrease them during the downturn. Both results are in line with the behavior of inexperienced investors in experimental asset markets. The economic significance of young managers’ actions is amplified by large inflows into their funds prior to the peak in technology stock prices.     

Asset price bubbles and economic welfare

In this paper, we provide the first empirical evidence on whether or not asset price bubbles predict economic welfare. Using a time-series model, we show that asset price bubbles both positively and negatively predict economic welfare, although the evidence that asset price bubbles are welfare-enhancing is much stronger. These results are also robust to out-of-sample forecasting as well as to a predictive regression model augmented by structural break dates.     

Housing Price Bubbles in Hong Kong, Beijing and Shanghai: A Comparative Study

This study investigates whether there was a housing price bubble in Beijing and Shanghai in 2003. The existence of a bubble can be interpreted from (abnormal) interactions between housing prices and market fundamentals. This paper introduces an enhanced framework, with the combination of standard econometric methodologies: i.e., Granger causality tests and generalized impulse response analysis, and the reduced form of housing price determinants. A test case in Hong Kong, between 1990 and 2003, is included to test the reliability of our methods because Hong Kong has experienced the formation and bursting of a huge housing bubble around the year 1997. It is found that the pattern and magnitude of the estimated bubbles conform quite well to the discrepancies between the actual and predicted prices. Also, the findings suggest that there appeared a bubble in Shanghai in 2003, accounting for 22% of the housing price. By contrast, Beijing had no sign of a bubble in the same year. The bubble phenomenon, of course, should be taken with cautions. Nonetheless this study has laid the groundwork for further investigations in abnormal housing price phenomena in Mainland China.     

信贷扩张、资产价格上涨与调控政策选择

本文首先从理论上考察信贷与资产价格之间的关系,利用Allen和Gale的资产价格泡沫模型,并根据我国实际情况,通过放松假设条件说明信贷扩张是资产价格上涨的重要原因,资产供给、信贷政策、银行信贷管理能力会影响资产价格的上涨。通过对我国经济的实证研究发现,我国的信贷与资产价格之间存在相关关系,最后指出从资产供给、信贷政策、银行信贷管理等方面入手制定政策抑制资产价格的进一步上涨。