Bubble Period Research Articles

House price dispersion in boom–bust cycles: evidence from Tokyo

We investigate the cross-sectional distribution of house prices in the Greater Tokyo Area for the period 1986–2009. We find that size-adjusted house prices follow a lognormal distribution except for the period of the housing bubble and its collapse in Tokyo, for which the price distribution has a substantially heavier upper tail than that of a lognormal distribution. We also find that, during the bubble era, sharp price movements were concentrated in particular areas, and this spatial heterogeneity is the source of the fat upper tail. These findings suggest that, during a bubble, prices increase markedly for certain properties but to a much lesser extent for other properties, leading to an increase in price inequality across properties. In other words, the defining property of real estate bubbles is not the rapid price hike itself but an increase in price dispersion. We argue that the shape of cross-sectional house price distributions may contain information useful for the detection of housing bubbles.

When and Why Do Stock and Bond Markets Predict Economic Growth?

We consider whether key financial variables predict macroeconomic series and if any predictive power for output growth is also seen in consumption or investment growth. Such information will allow the use of financial markets as a leading indicator for macroeconomic performance. 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 only occurs during the great moderation period, whereas for the change in the short-term rate it 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. We extend the analysis to include commodity, housing and the corporate bond markets. Full sample results reveal limited additional predictive ability, while the REIT returns do provide positive predictive power for output and investment growth over a one-quarter horizon, with the default return doing likewise at the four-quarter horizon. Notably, sub-sample results reveal a change in the sign of the predictive coefficient around the dotcom bubble and crash period.

Short-Range Signatures of Explosive Sounds in Shallow Water Used for Seabed Characterization

Small explosions were used as sound sources in the Seabed Characterization Experiment conducted in spring 2017 in the New England Mud Patch, a shallow-water region with a depth of approximately 75 m. The sources were U.S. Navy Signal Underwater Sound (SUS) Mk 64 charges, which contained 31.18 g of the explosive 2,4,6-Trinitrophenylmethylnitramine, commonly referred to as Tetryl. Source recordings were obtained by two hydrophones deployed from the same ship that deployed the SUS. The recordings were analyzed for bubble period, energy spectral density, and the variability of these parameters, and compared to previous results from the literature, including the prediction of a historic spectral model, and a new semiempirical time-domain model assembled using measured data from the literature. The new model describes the source level measurements in the 25–275-Hz band and in the 400-Hz octave band to within 0.5 dB, and agrees with similar measurements from the literature to within 0.6 dB. The standard deviation of the band-limited source levels was found to be about 1 dB, some of which is ascribed to uncertainty and variation in the source-to-receiver distance. The observed source level variation is similar to previously reported values.

Disentangling bubbles in equity REITs

This paper examines the occurrence of price bubbles in equity real estate investment trusts (REITs) classified by property types. We employ the Generalized Supremum Augmented Dickey–Fuller (GSADF) methodology to a sample spanning January 1980–December 2017. The analysis considers the overall equity REIT index and seven major property sectors including Diversified, Healthcare, Industrial/Office, Lodging/Resorts, Residential, Retail, and Self-Storage. Our results reveal significant bubble periods in the overall equity REIT index and all property sectors except for Lodging/Resorts. Interestingly, we observe unique patterns in the price bubbles for all remaining six property sectors. Our results confirm that each property sector represents a distinct line of business.

Online, quasi-real-time analysis of high-resolution, infrared, boiling heat transfer investigations using artificial neural networks

We present a machine learning methodology that can be used online and quasi-real-time (i.e., as fast as we can practically run an experiment) to accelerate the analysis of infrared, boiling heat transfer investigations. Precisely, we use feed-forward artificial neural networks with one layer of hidden neurons to measure bubble growth time, bubble period, and nucleation site density directly from the radiation recorded by the high-speed infrared camera. We test and validate the methodology against saturated pool boiling experiments with water, run on both plain and nanoengineered surfaces. Using such a technique, we have measurements of the quantities above within a few seconds from the moment the camera records the boiling surface radiation, with a regression coefficient of 0.95 or higher compared to reference measurements obtained by conventional, time-consuming, image processing techniques.

Lattice Boltzmann simulation of seawater boiling in the presence of non-condensable gas

In this study, three-dimensional (3D) boiling of seawater containing non-condensable gas (NCG) was simulated using the modified pseudopotential lattice Boltzmann model for multiphase multicomponent flow, and the effects of wettability and the NCG concentration on the heat flux between the heat source and its adjacent fluids, bubble departure period and diameter were analyzed. The simulation results show that, with an increase in the NCG concentration, the heat flux, bubble departure period and diameter decreased, while the effect of NCG on the bubble departure diameter and period plateaued as contact angle proceeded. Additionally, the boiling mechanisms of seawater containing NCG in a horizontal fissure were also analyzed. With an increase in the NCG concentration, the bubble departure diameter decreased while the bubble departure period increased. Furthermore, the influence was weakened with an increase in Re number.

Home prices and fundamentals: solving the mystery for the G-7 by accounting for nonlinearities

PurposeThe purpose of this study is to determine whether house prices and income share a stable, stationary relationship in the G-7 countries. This stable relationship has been clearly implied by theory but has been difficult to uncover empirically in previous studies.Design/methodology/approachThe analysis entails using nonlinear tests for a stationary relationship between home prices and per-capita income for the G-7 countries, whereas most previous papers on the topic have used linear methods.FindingsWhen the standard linear ADF test is used, no stationary relationship for home prices and income is found for any of the G-7 countries. When the more powerful (but still linear) Ng–Perron test is used, the USA, but no other G-7 country, exhibits a stable relationship between the two variables. When the nonlinear Enders–Granger test is used, stationarity between home prices and income is found for five of the remaining six G-7 states.Practical implicationsPrevious research has shown that as house prices have risen far above the income, especially over bubble periods, income has done a poor job in predicting home values. The findings show that income has a clear long-run stationary relationship with home values. This implies income could be helpful in providing home price forecasts.Originality/valueWhere previous studies have failed to find a long-run relationship between home prices and income while using linear methods, results in this paper show this theoretical asset–pricing relationship holds once the adjustment process is allowed to exhibit nonlinearity.

Housing challenges in shrinking and aging Japanese cities

Housing challenges in shrinking and aging Japanese cities

Detecting West Texas Intermediate (WTI) Prices’ Bubble Periods

Oil prices have had considerable surges and bursts since the first oil crisis of 1973. Until then its price was stable, with almost zero volatility. Since then, apart from the two oil crises of 1973 and 1978/9, oil prices had consecutive bubble episodes like the surges up to 2008 and 2014 and their successive bursts, respectively. The trace of these bubble periods is of crucial importance for policymakers, since their drivers and consequences impact global economic developments. Phillips et al. and Phillips et al. methodologies are applied to detect whether West Texas Intermediate prices experienced bubble periods. Both methodologies suggest that WTI prices experienced explosive episodes, which could be fundamentally, speculatively, or politically attributed. Some suggested periods coincide for both methods, but the second methodology seems to be more sensitive than its predecessor is, leading to better bubble detection but also to identification of non-existent bubbles. The identified bubble periods are compared to relevant research in the literature concerning their presence, duration, and explosiveness. The main goal of the research, apart from the detection of bubbles’ presence and duration, is to identify the causal underlying reasons for each explosive episode. Further, we compare the start and endpoints of each bubble episode with time-points when structural changes occurred. The contribution of the paper is that it clearly defines the bubble episodes with their corresponding drivers. The paper identifies the importance of market fundamentals’ swifts in explaining the bubble periods. The findings of the papers can help policymakers and other stakeholders to monitor oil price shifts and their underlying reasons, and then proceed with prompt actions. Since bubble episodes are fundamentally explained, then the practical utility is that by focusing on the market fundamentals, stakeholders can avoid actions that could result in market failures.

What Makes Cryptocurrencies Special? Investor Sentiment and Return Predictability During the Bubble

We propose a crypto-specific lexicon to quantify the investor sentiment and use it to predict the cryptocurrency market returns. The new lexicon achieves better accuracy (32\% higher) than the traditional financial lexicon when applied to an out-of-sample classification setting. The empirical results reveal that investor sentiment positively predicts excess CRIX returns with a daily in(out)-of-sample $R^2$ of 2.74\% (3.15\%) without significant evidence on the return reversal. The results are robust to the inclusion of alternative sentiment indices, technical indicators, market microstructure noise, and across bubble and non-bubble periods. We further exclude the soft information interpretation of our sentiment index by showing that non-fundamental related sentiment shows stronger predictive power than that of the fundamentally related sentiment. Our findings suggest that in a market-driven by noise traders, and when there is only limited information about the fundamental value of the underlying asset, investor sentiment drives the price evolution and its impact may not reverse in a short horizon.

Neuroeconomics of Asset-Price Bubbles: Neuroimaging and Digital Technology for the Prediction and Prevention of Major Bubbles

Asset-price bubbles challenge the explanatory and predictive power of standard economic theory, so neuroeconomic measures should be explored as potential tools for improving the predictive power of standard theory. This exploration is begun by reviewing results from functional magnetic resonance imaging (fMRI) studies of lab asset-price bubbles and herding behavior (i.e., following others' decisions). These results are consistent with a neuroeconomics-based hypothesis of asset-price bubbles. In this view, decision making during bubble or non-bubble periods of financial-market activity is driven by, respectively, evolutionarily ancient or new neurocircuitry. Neuroimaging studies that test this or other neuroeconomics-based hypotheses of asset-price bubbles may yield a bubble-related biomarker (e.g., low trade-related lateral neocortical activity associated with traders’ herding-based decisions). Wearable functional near-infrared spectroscopy (fNIRS) technology could determine the prevalence of such a biomarker among financial-market participants, thereby enabling the real-time detection of an emerging bubble. Mechanisms are described by which this early-warning signal could be exploited in self-regulatory or government-administered policies for financial-system stabilization. Digital technology may offer an even more readily achievable alternative to neuroimaging (e.g., behavioral precursors to price bubbles may be identified in analyses of investors’ interactions with asset-trading platforms). In summary, neuroimaging- or digital technology-based financial-system regulation may be useful for distinguishing bubble from non-bubble periods and preventing major asset-price bubbles. To clarify the role of cognitive distortions in these cyclical periods, price is classified as a heuristic that yields bubble or crash biases.

Are financial analysts eager postmen of bubble psychology? Evidence in the United Kingdom

AbstractThis paper examines the investment value of financial analysts' advice (earnings forecasts and stock recommendations) to shareholders around two recent bubble periods in the United Kingdom: the dot‐com bubble period and the credit bubble period. We find that analysts' advice is valuable at the firm level, as reflected in their recommendations for high‐tech stocks before and after the dot‐com bubble burst. However, at the aggregate level, in neither bubble period do we uncover a stable relation between average stock returns and analysts' advice. The key to the lack of predictive power of analysts' advice does not seem to be their predictable nature, as the responsiveness of returns to such news, predicted or not, varies widely around the bubble periods studied.

Wind Preparation of the Generation of Equatorial Plasma “Bubbles”

According to theoretical conclusions, zonal western thermospheric winds are the key influence on the generation of equatorial plasma “bubbles.” To verify this assumption, a comparative analysis of the longitudinal distribution of equatorial plasma bubbles and the longitudinal profile of deviations of the zonal western thermospheric wind velocity has been carried out. The data on plasma bubbles (from the ISS-b satellite, ~1100 km) averaged over two hemispheres during the spring equinox were analyzed. The wind characteristics used in the study (the CHAMP satellite, ~400 km) were taken as the median values over the equinox period in the interval (15–21 LT) covering the preparation time and the generation period of equatorial plasma bubbles. It was found that these characteristics are very similar with a high degree of correlation (R ≅ 0.76). It has been newly confirmed that the theoretical statement (Kudeki model) on the key influence of zonal western thermospheric winds on the generation of equatorial plasma bubbles.

Do Bubbles Alter Contributions to Price Discovery? Evidence from the Chinese Soybean Futures and Spot Markets

ABSTRACT The purpose of this study is to investigate whether bubbles have significantly influenced the performance of price discovery in Chinese soybean futures markets. To evaluate the performance of price discovery, we employ forecast error variance decomposition based on structural vector autoregression and directed acyclic graphs, using daily data from six price series of futures contracts expiring at different months and one spot soybean price for the past 13 years. Then, the full-period data are divided into bubble and non-bubble periods via the supremum augmented Dickey–Fuller test. The methods utilized on the full sample for price discovery are conducted again on two subperiods. Our empirical results show that price discovery in the Chinese soybean futures market performs much better in bubble periods and worse in non-bubble period compared to the full period, indicating that bubbles have significantly influenced the performance of price discovery in Chinese soybean futures markets.

Does speculation cause high red meat prices? Evidence from Turkey

AbstractThe focus of this letter is the upward trend of red meat prices in Turkey that began to surge in 2009. A typical explanation for such price increases would be an inadequate supply of livestock. Yet, although measures were taken to raise the supply of red meat, they were not sufficient to reverse or stop this upward trend in prices. We specifically search for the dynamics behind the price spikes by exploring whether they were driven by speculation. We investigated the presence of rational speculative bubbles in the red meat market in Turkey by employing a recent methodology developed by Phillips et al. (2015). We found evidence for explosive periods and detected the periods of speculative bubbles in the red meat market in Turkey. [EconLit citations: C4, D4, O13].

Research Note: Low‐frequency pneumatic seismic sources

ABSTRACTPneumatic seismic sources, commonly known as airguns, have been serving us well for decades, but there is an increasing need for sources with improved low‐frequency signal and reduced environmental impact. In this paper, we present a new pneumatic source that is designed to achieve these goals by operating with lower pressures and larger volumes. The new source will release more air creating larger bubbles with longer bubble periods than airguns. The release of the air will be tuned so that the rise time will be longer and the sound pressure level and its slope will be lower. Certain engineering features will eliminate cavitation. Larger bubbles increase low‐frequency content of the signal, longer rise times decrease mid‐frequency content and the elimination of cavitation reduces high‐frequency content. We have not yet built a full‐scale version of the new source. However, we have manufactured a small‐scale low‐pressure source incorporating most of the engineering features, and tested it in a lake. Here, we present the lake data that, as expected, show a significant reduction in the sound pressure level, increase in rise time, decrease in slope and decrease in high‐frequency content while maintaining the same low‐frequency content when the source prototype is operated at low pressure compared with high pressure. Synthetic data produced by numerical modelling of the full‐scale proposed pneumatic source suggest that the new source will improve the low‐frequency content and can produce geophysically useful signal down to 1 Hz.

Trends in Household Debt and Credit

Since the onset of the 2008 financial crisis, consumer financial and borrowing behavior, once considered a relatively quiet little corner of finance, has been of enormously increased interest to policymakers and researchers alike. Prior to the Great Recession, there was a historic run-up in household debt, driven primarily by housing debt, which coincided with a speculative bubble and sharp rises in home prices. Then, as prices began to fall, millions of households began defaulting on their mortgages, unable to keep up with home payments, and greatly contributing to the onset of the deepest recession since the 1930s. Following the steep increase in debt balances during the boom, households began rapidly paying off their loans during and immediately after the Great Recession. Since 2013, debt has begun to increase and eventually rise above its previous levels, albeit at a much slower rate than before, at least partially owing to stricter lending standards. We examine the trends in household debt before, during, and since the 2000s financial crisis and Great Recession. As we will show, this period is unique in American history in several ways. Our analysis will show the sources of the historic run-up in debt during the bubble period of the early 2000s, the change in borrowing behavior that took place as the financial crisis and Great Recession took hold, and the nature of the recovery that began in 2013. We find that while total household debt has recovered to its previous level in nominal terms, its composition and characteristics have changed dramatically along many dimensions.

Sentiment-Induced Bubbles in the Cryptocurrency Market

Cryptocurrencies lack clear measures of fundamental values and are often associated with speculative bubbles. This paper introduces a new way of testing for speculative bubbles based on StockTwits sentiment, which is used as the transition variable in a smooth transition autoregression. The model allows for conditional heteroskedasticity and fat tails of the conditional distribution of the error term, and volatility may depend on the constructed sentiment index. We apply the model to the CRIX index, for which several bubble periods are identified. The detected locally explosive price dynamics, given the specified bubble regime controlled by a smooth transition function, are more akin to the notion of speculative bubble that is driven by exuberant sentiment. Furthermore, we find that volatility increases as the sentiment index decreases, which is analogous to the commonly called leverage effect.

The Impact of Merger and Acquisition Firms on Stock Market Bubble

In this research, we have endeavored to ascertain how the Merger & Acquisition firms effect the Pakistani stock market (PSX) during all stages of bubble periods. The regression results of “transaction multiples” and “inverse transaction multiples” show that the trading of the securities of Merger & Acquisition firms has increased in all stages of bubble periods less crash period where they decreased. The regression results have also revealed that Pakistani investors in the stock market carry a “weak financial knowledge & financial risk distress management” & they prefer market manipulation for discounting & therefore, they are adversely hit market manipulations in the stock exchange while trading securities. Resultantly, managerial incentives, as well as cost of capital of Merger & Acquisition firms, stand increased with the help of relevance of accounting, Earnings manipulation & by exercise Investing Activities.

The missing obese men? Labour force participation and obesity among prime-age men in the United States

The declining labour force participation among men between the ages 25 and 54 in the United State has attracted the attention of policymakers and the public. I document this trend by obesity status during the period 1990–2016 using the Behavioural Risk Factor Surveillance System Survey. I find that the likelihood of being out of the labour force has been increasing by approximately 0.22 percentage points every year on average for non-obese men, while that of obese men has been increasing by approximately 0.28 percentage points. This indicates that the difference in the propensity to be out of the labour force has widened by 1.6 percentage points between the obese and the non-obese during 1990–2016. It seems that the labour force participation gap between obese men and non-obese men started to increase during the housing bubble period, 2001–2007. The difference in the trends seems to be driven by non-Hispanic whites, men without a college degree, and men aged 25–44.