Bubble Period Research Articles

Research on multiple bubbles in China's multi-level stock market.

Financial bubbles have always been a topic of long-term concern for economists. Understanding bubble phenomenon and dating the period of bubbles in real time can provide an early warning diagnosis for financial bubbles and help regulatory authorities to control it and maintain market order. The generalized sup ADF (GSADF) and backward sup ADF (BSADF) tests with flexible window width can effectively detect and date periodically collapsing bubbles in real time. Based on the financial present value model, this paper applies right-tail recursive ADF test to test multiple bubbles in China's multi-level stock market. Unlike the other researches in China, the ratios of the real stock prices' natural logarithm to the real dividends' natural logarithm are used for our testing instead of stock price index. Empirical results show that there are 8 bubbles in the Main-Board Market, 6 bubbles in the Small and Medium Enterprises Board (SMEs), and 4 bubbles in the Growth Enterprise Market (GEM). These bubbles are liquidity-driven and presuppose a loose credit cycle, with the exception of bubbles in 2014-2015. The frequent emergence of bubbles in a short time indicates that China's stock market is still emerging market. In addition, frequent fluctuations imply there is a serious "herd effect" and a lack of monitoring mechanism for bubble risk. This study not only enrich the real-time dynamic research on periodical bubbles of China's stock market, but also provide an empirical reference for investors' investment choices, financial decisions of listed companies and warning mechanism of regulatory authorities.

Portfolio Correlations in the Bank-Firm Credit Market of Japan

The recent global financial crisis has shown portfolio correlations between agents as one of the major channels of risk contagion and amplification. In this work, we analyse the structure and dynamics of the cross-correlation matrix of banks’ loan portfolios in the yearly bank-firm credit network of Japan during the period from 1980 to 2012. Using the methods of Random Matrix Theory (RMT), Principal Component Analysis and complex networks, we aim to detect non-random patterns in the empirical cross-correlations as well as to identify different states of such correlations over time. Our findings suggest that although a majority of portfolio correlations between banks in lending relations to firms are contributed by noise, the top largest eigenvalues always deviate from the random bulk explained by RMT, indicating the presence of non-random patterns governing the correlation dynamics. In particular, we show that this dynamics is mainly driven by a global common factor and a couple of “groups” factors. Furthermore, different states in the credit market can be identified based on the evolution of eigenvalues and associated eigenvectors. For example, during the asset price bubble period in Japan from 1986 to 1991, we find that banks’ loan portfolios tend to be more correlated, showing a significant increase in the level of systemic risk in the credit market. In addition, building Planar Maximally Filtered Graphs from the correlations of different eigenmodes, notably, we observe that the local interaction structure between banks changes in different periods. Typically, when the dominance of a group of banks in one period gradually vanishes, the credit market starts to build-up a different structure in the next period in which another group of banks will become the main actors in the backbone of the cross-correlations.

COVID-19, cryptocurrencies bubbles and digital market efficiency: sensitivity and similarity analysis

This paper compares the degree of cryptocurrency market efficiency during the pre- and post COVID-19 pandemic with the bubble and non-bubble periods of cryptocurrency markets. Furthermore, it examines and clusters eighteen cryptocurrencies by exploring their market efficiency similarity. Comparing the cryptocurrency bubble periods with the COVID-19 pandemic, the results indicate that this pandemic has the highest impact on cryptocurrency market efficiency. Interestingly, using the dynamic time warping clustering approach, we found evidence on the presence of three clusters that essentially represent mining coins, non-mining coins and token categorizations .

CRYPTOCURRENCIES, COVID-19 PANDEMIC AND THE FINANCIAL BUBBLES: THE CASE OF TOP FIVE DIGITAL ASSETS

This study explores the bubble behavior in the prices of top five cryptocurrencies (i.e., Bitcoin, Ethereum, Ripple, Stellar, and Tether) using daily data of the closing level at the COVID-19 pandemic, covering the period from January 2, 2020 to January 2, 2021. The testing procedure of the bubble behavior in selected cryptocurrencies prices is investigated by two methodologies. Those covers the test statistics originated by the Supremum Augmented Dickey-Fuller (SADF) (Phillips et al., 2011) and Generalized Supremum Augmented Dickey-Fuller (GSADF) (Phillips et al., 2015) to define several bubble periods. The empirical results emphasize that bubble behavior is not a diverse and stable feature of Bitcoin, Ethereum, Ripple, and Stellar prices, except the Tether prices, which point out the emergence of a potential crisis in the digital assets market through an increasing degree of financial instability.

Shock wave and bubble characteristics of underwater array explosion of charges

In this study, we focused on the effect of the underwater explosion parameters of multi-point array explosion. The shock wave and bubble parameters of aggregate charge, two charges, and four charges were measured through an underwater explosion test, and their influence on the explosion power field of charge quantity and array distance was analyzed. Results show that the multi-shock wave collision of array explosion can be approximated to a linear superposition, and the interaction of delayed shock wave can be deemed as the increase of the shock wave baseline. Shock wave focusing and delayed superposition increase the shock wave peak pressure. Compared with the aggregate charge, the greater the number of array explosion points is, the higher the impulse and the gain of the bubble peak pressure are. At the same array distance, the smaller the charge quantity is, the higher the bubble impulse will be. At the same charge quantity, the smaller the array distance is, the higher the bubble impulse will be. The bubble period decreases gradually with the increase of the charge quantity, but the test orientation has little effect on the bubble period.

Interaction of two approximately equal-size bubbles produced by sparks in a free field

A series of experiments are performed to study the interaction of two bubbles of approximately equal size in free-field water for different parameter combinations (i.e., the phase difference θ and the initial distance d*). First, a high-voltage discharge device that can generate multiple bubbles of different sizes in water and accurately control the time of bubble generation is introduced. For different discharge voltages, the maximum radius and the first oscillation period of a single bubble and the shock wave energy and bubble energy conversion rate are studied through high-speed photography, current monitoring, voltage probes, and an underwater free-field pressure sensor. Then the distance of the center of mass and average radius of two bubbles generated at different distances at the same time are compared with a theoretical model and good consistency is obtained when the initial distance is greater than the bubble diameter. Finally, the interaction phenomena of two bubbles generated with different initial distances and phase differences are divided into five categories, namely, coalescence, failed catapult, piercing jet, jet toward, and jet away, and the boundary conditions used to distinguish different phenomena are given. For the piercing jet, a high-speed fine jet will be generated in the bubble generated later. The jet will penetrate the wall of the bubble and propagate steadily in the water at high speed (∼79 m/s). The velocity of the jet in the bubble and in water generated with different parameter combinations is statistically analyzed, and the velocity distribution cloud diagrams are given.

Effect of time delay in a bistable synthetic gene network.

The essence of logical stochastic resonance is the dynamic manipulation of potential wells. The effect of time delay on the depth of potential wells and the width of a bistable region can be inferred by logic operations in the bistable system with time delay. In a time-delayed synthetic gene network, time delay in the synthesis process can increase the depth of the potential wells, while that in the degradation process, it can reduce the depth of the potential wells, which will result in a decrease in the width of the bistable region (the reason for time delay to induce logic operations without external driving force) and the instability of the system (oscillation). These two opposite effects imply stretching and folding, leading to complex dynamical behaviors of the system, including period, chaos, bubble, chaotic bubble, forward and reverse period doubling bifurcation, intermittency, and coexisting attractors.

The effect of the housing crisis on the finances of central cities

In 2015, eight years after the start of the Great Recession, average per capita revenue in the nation's largest central cities was 7% below pre-recession levels, a decline that in both depth and duration is the most severe in the post-war period. In this paper, we address the role of the housing market in this decline. We analyze the impact of the boom and subsequent collapse in housing prices and the unprecedented surge in mortgage foreclosures on the finances of central cities. To link city finances to housing conditions, we draw on a specially created data base that takes account of the revenues and spending of all the local governments that provide services to city residents. Our regression analysis, which employs data from 2000 through 2014 for 90 large central cities, finds statistically and economically significant effects of both housing price changes and foreclosure rate changes on property tax revenues. We also find that property tax levy limits dampened the fiscal response to the housing bubble and bust. During the housing bubble period, property tax revenues and capital expenditures rose significantly faster in non-levy limit cities than in cities subject to levy limits, but then fell more sharply during the housing bust period. We estimate that the direct effect of the housing bust was responsible for 21% of the decline in the general revenue of large central cities from 2009 to 2011.

Do factor models explain stock returns when prices behave explosively? Evidence from China

We test the Fama-French five-factor model when stock prices exhibit explosive (or bubble) behavior. Using the Backward Sup Augmented Dickey-Fuller (BSADF) statistic, we identify the bubble period for China's A-share stock market from September 2014 to June 2015. The model explains cross-sectional stock returns during the bubble period, but the explanatory power of the five-factor model declines as prices change from the random walk period to the bubble period. Furthermore, the marginal pricing ability of the five factors also decreases substantially in the bubble period. The speculative investor behavior may explain the declined explanatory power of the model during the bubble.

The impact of the rise and collapse of Japan's housing price bubble on households’ lifetime utility

This study estimates the impact of the dramatic changes in housing prices during Japan's bubble from the late 1980s to the 1990s on households’ asset accumulation and utility over their life cycle. We construct a life-cycle model explaining households’ consumption/saving and housing decisions under collateral and borrowing constraints. We estimate this model using data from the Family Income and Expenditure Survey (FIES), which includes data on households’ housing wealth estimated from objective information. Using the estimated model, we then conduct a counterfactual simulation in which we assume that housing prices remained constant during the bubble period. Doing so allows us to quantify the gains/losses of lifetime utility due to the housing price boom and bust. We find that 72.2% of the households experienced an average decrease in lifetime utility equivalent to 5.7% of lifetime income. On average, Japan's housing price boom and bust caused a loss in lifetime utility equivalent to 4.7% of lifetime income. Moreover, we compare the impact of the housing price bubble across cohorts and find that the impact was greatest for those who experienced the bubble at ages 35–45.

When and why do stock and bond markets predict US economic growth?

We consider whether major financial variables predict key macroeconomic growth series. Full sample results suggest that aggregate stock returns and the 10-year minus 3-month term structure exhibit a positive and significant predictive effect on subsequent output, consumption and investment growth. Additionally, the change in the 3-month Treasury bill has predictive power for output and investment growth. Sub-sample analysis reveals that while the term structure exhibits relatively constant predictive power, that arising from stock returns largely occurs only during the great moderation period, whereas predictability from the change in the short-term rate largely arises in the period following the financial crisis. Results also reveal similarity in the predictive relations for output growth and investment growth but less so for consumption growth. Extending the analysis to include commodity, housing and the corporate bond markets, full sample results reveal limited additional predictive ability, with the REIT returns providing positive predictive power for output and investment growth over a one-quarter horizon and the default return doing likewise at the four-quarter horizon. Sub-sample results, however, reveal a change in the sign of the predictive coefficient around the dotcom bubble and crash period. As leading indicator measures include financial variables, these results, suggesting that the predictive relation is time-varying, are key for policy-makers.

Network-centric Indicators for Fragility in Global Financial Indices

Over the last 2 decades, financial systems have been studied and analyzed from the perspective of complex networks, where the nodes and edges in the network represent the various financial components and the strengths of correlations between them. Here, we adopt a similar network-based approach to analyze the daily closing prices of 69 global financial market indices across 65 countries over a period of 2000–2014. We study the correlations among the indices by constructing threshold networks superimposed over minimum spanning trees at different time frames. We investigate the effect of critical events in financial markets (crashes and bubbles) on the interactions among the indices by performing both static and dynamic analyses of the correlations. We compare and contrast the structures of these networks during periods of crashes and bubbles, with respect to the normal periods in the market. In addition, we study the temporal evolution of traditional market indicators, various global network measures, and the recently developed edge-based curvature measures. We show that network-centric measures can be extremely useful in monitoring the fragility in the global financial market indices.

Identifying price bubble periods in the Bitcoin market-based on GSADF model

The advert of cryptocurrency era is signified by the luanch of Bitcoin, which has been considered as a milestone event. Ever since its emergence, Bitcoin has experienced rapid price increase along with great price fluctuations. This paper aims to explore the beginning and the culmination of possible speculative bubbles the Bitcoin market. Based on the daily closing price of Bitstamp, a major Bitcoin exchange platform, from September 13, 2011 to October 12, 2020, this paper adopts GSADF (generalized sup augmented Dickey–Fuller) to explore the existence of the bubble in the Bitcoin market, estimate the time of emergence and collapse of the bubble, investigate the causes of the bubbles based on its time order, and attempts to put forward some policy suggestions. Through this study, we have found that: (1) There are a lot of speculative bubbles. During the research period, there were a total of four long bubbles (i.e. 2013.01.25–2013.04.05; 2013.11.05–2013.12.10; 2017.04.27–2017.07.05; 2017.07.15 –2018.01.09) and four short bubbles (2016.06.08–2016.06.18; 2016.12.30–2017.01.15; 2017.02.22 –2017.03.07; 2019.06.19 –2019.06.25). (2) The emergence and burst of bubbles were mostly related to the occurrence of relevant events and policies. (3) Bitcoin market is far from mature. A key policy risk triggering the speculative behavior is policy announcement. The prominent innovation of this paper is that the latest developed bubble detection method GSADF has been employed in the Bitcoin market. This method can detect the existence of multiple Bitcoin bubbles and their durations.

Study on Unsteady Cavitation Flow and Pressure Pulsation Characteristics in the Regulating Valve

A combined numerical‐experiment investigation on the unsteady cavitation flow and pressure fluctuation characteristics in the regulating valves is conducted in this paper. The cavitation flow in the regulating valve is an unsteady and periodic flow which could be divided into fixed and travelling cavitation bubbles. The fixed cavitation bubbles are formed in the gap in the initial stage and then fell off and formed the travelling cavitation bubbles because of the re‐entrant jet. The travelling cavitation bubbles move downstream, oscillate, and break up into several smaller bubbles. Changes in the length/radius ratio (L/R0) of the valve spool is an important factor affecting unsteady cavitation flow and pressure pulsation characteristics in the regulating valve. The length of travelling cavitation bubbles increases firstly and then decreases with increasing time. With the increase of the length/radius ratio (L/R0), the oscillation period of cavitation bubbles also increases. In the initial stage of cavitation bubbles, the velocity distribution inside the regulating valve is relatively stable, and no re‐entrant jet could be found although L/R0 is different. In the collapse stage of cavitation bubbles, the velocity distribution becomes extremely unstable because the collapsing cavitation bubbles affect the pressure drop and velocity field in the flow channel. Furthermore, the amplitude of pressure pulsation increases gradually, and the peak time of the pressure pulsation is gradually delayed while increasing the length/diameter ratio.

A review paper on bubbling nature of crypto currency

The scholarly research on the development of price bubbles in digital currency marketplaces is reviewed in this article. According to studies, Bitcoin values went through numerous bubble stages, the most recent of which occurred. Other major digital currencies, such as Ethereum and Lit coin, have gone through numerous bubble periods as well. The most often used methods for bubble identification and measurement are the Augmented Dickey Fuller (ADF) and Log-Periodic Power Law (LPPL) methodologies. According to scholarly research, Bitcoin has been in a capsule stage from June 2015, while Blockchain, NEM, Stellar, Ripple, Lit currency, and Dash have been labelled as possessing bubble-like characteristics since November 2015. However, that the latter grouping has been lacking academic evidence to prove the presence of bubbles since early 2018. A thorough reference list is provided based on considerable differences between market citation marks and foundational beliefs, which may be used as a reference for policymakers, scholars, and investors.

Bank herding in loan markets: Evidence from geographical data in Japan

AbstractThis paper investigates whether Japanese banks followed herd behavior in loan markets during 1980–2000. Using data categorized by bank type and geographical area, we examine leader–follower relationships between the behavior of different bank types. We find evidence of their herding that is not explained by macroeconomic conditions. In particular, regional types of banks always followed banks that had large loan shares in individual areas. Such herding was observed more frequently in regional areas. Unusual herding by major banks was observed from immediately before the Japanese asset‐price bubble in the late 1980s to its bursting in the early 1990s. During the bubble period, the estimated amount of loans raised by major banks' herding in urban areas was greater than 2% of the average annual nominal GDP in the period, overwhelming that of herding by other types.

Bitcoin price manipulation: evidence from intraday orders and trades

ABSTRACT We analyse 519.4 million Bitcoin orders placed on Gemini Exchange during January 2016-August 2019 and find limit orders dominate at 99.92%. We document order-based evidence of price manipulation during the Bitcoin bubble in late 2017, when the daily number of market orders during the bubble period more than triples the overall daily average. The changes in both prices and liquidity satisfy two criteria specified in Kyle and Viswanathan (2008) for the price manipulation definition. Moreover, we find a significant increase in market order imbalance associated with price manipulations modelled in Jarrow, Protter and Roch (2012).

Bubbles in Crude Oil and Commodity Energy Index: New Evidence

This paper considers a long dataset of both Brent and West Texas Intermediate (WTI) crude oil prices and the Commodity (fuel) energy index (CEI) to identify possible bubbles. Using the Supremum Augmented Dickey–Fuller (SADF) test, we compare results from WTI and Brent with CEI. We prove that the CEI follows Brent crude oil (they provide similar bubble periods) and that Brent is recognized as a crude oil benchmark. Financial managers should incorporate it into their analysis and forecasts. The findings are strongly recommended to energy policymakers and investors.

Numerical simulation on the whole process of an underwater explosion between a deformable seabed and a free surface

When a charge explodes in shallow water, the combined effects of free surface and seabed on shockwave propagation and bubble motion are significant. In this paper, an underwater explosion between a deformable seabed and a free surface is numerically investigated. An axisymmetric numerical model is established using the Eulerian Finite Element Method (EFEM) and the Volume of Fluid (VOF) method is used in dealing with the interface. The truncated computational domain boundary adopts the non-reflecting boundary condition. The seabed is regarded as a heavier fluid and density ratio between the seabed and water is used to describe seabed feature in this paper. The present model is validated by comparing with the experiment and shows great results. Then the underwater explosion with different initial conditions are simulated, it is found that deformable seabed has a great impact on bubble when the bubble is near the deformable seabed. And the bubble period and pressure peak of shockwave have a positive relation with the density ratio and initial charge depth. In addition, the annular jet might appear and penetrate the upper surface of the bubble in certain condition, leading to the bubble split during the contraction phase.

Do Bubble Behaviors Exist in Chinese Film Stocks?

This article investigates bubbles in the Chinese film industry to reveal the industry’s boom and bust process that influences employment, citizen’s livelihoods, and even economic growth. We adopt the film stock index to reflect the industry’s trajectory and employ the generalized and backward sup augmented Dickey–Fuller tests to detect bubble periods. Empirical results indicate that there are three positive bubbles in 2007, 2013, and 2015, indicating that the film market continues to expand after temporary frustrations. Meanwhile, one negative bubble is found in 2019, which demonstrates that the bubble’s negative impacts persist and the film industry is still having problems such as declining industrial output. Economic growth, film quality, and industrial policies are common factors for all bubbles. The global financial crisis, capital in- and outflows, internet giants’ entry and sky-high remuneration are reasons for certain bubble behaviors. Hence, market practitioners should actively recognize bubbles and observe their evolution, which will favor industrial stabilization. A perfect legal system, moderate industrial policies, a competitive market environment, and other measures are needed to confront the opportunities and challenges.