Price Bubbles Research Articles

BEHAVIOUR BIAS IN INVESTMENT DECISIONS: EMPIRICAL STUDY OF INVESTOR PSYCHOLOGY IN INDONESIA

Investing involves putting money into a variety of asset classes for a predetermined amount of time in the hopes of increasing total value and producing more income. The goals of investments and economics, such as value creation, profit generation, and other related goals, are strongly correlated. It is critical to recognize that investments may include additional financial, social, and spiritual goals. This research aims to assess investor behavior from internal and external perspectives concerning investing decisions. This study employs the Structural Equation Model (SEM) methodology utilizing the Smart-PLS software. This study's findings demonstrate that qualities including anger, anxiety, overconfidence, and self-monitoring positively influence investment decisions. Herding mitigates the adverse impacts of anger, anxiety, overconfidence, and self-monitoring on investment decisions. This research's consequences can assist investors in circumventing irrational risks and yield more objective findings grounded in thorough study. This tendency can result in inefficient market transactions, asset bubbles, and significant volatility. This study arose as a counter to the conventional understanding of exchange markets predicated on the premise of trader rationality. This research identifies that emotional emotions, risk perception, and cognitive biases frequently affect investment decisions by comprehending human nature.

Local powers of least‐squares‐based test for panel fractional Ornstein–Uhlenbeck process

In recent years, significant advancements have been made in the field of identifying financial asset price bubbles, particularly through the development of time‐series unit‐root tests featuring fractionally integrated errors and panel unit‐root tests. This study introduces an innovative approach for assessing the sign of the persistence parameter () within a panel fractional Ornstein‐Uhlenbeck process, based on the least squares estimator of . This method incorporates three distinct test statistics based on the Hurst parameter (), which can take values in the range of , be equal to , or fall within the interval of . The null hypothesis corresponds to . Based on a panel of continuous records of observations, the null asymptotic distributions are obtained when the time span () is fixed and the number of cross sections () goes to infinity. The power function of the tests is obtained under the local alternative where is close to zero in the order of . This alternative covers the departure from the unit root hypothesis from the explosive side, enabling the calculation of lower power in bubble tests. The hypothesis testing problem and the local power function are also considered when a panel of discrete‐sampled observations is available under a sequential limit, that is, the sampling interval shrinks to zero followed by the goes to infinity.

INFERENCE IN MILDLY EXPLOSIVE AUTOREGRESSIONS UNDER UNCONDITIONAL HETEROSKEDASTICITY

Mildly explosive autoregressions have been extensively employed in recent theoretical and applied econometric work to model the phenomenon of asset market bubbles. An important issue in this context concerns the construction of confidence intervals for the autoregressive parameter that represents the degree of explosiveness. Existing studies rely on intervals that are justified only under conditional homoskedasticity/heteroskedasticity. This paper studies the problem of constructing asymptotically valid confidence intervals in a mildly explosive autoregression where the innovations are allowed to be unconditionally heteroskedastic. The assumed variance process is general and can accommodate both deterministic and stochastic volatility specifications commonly adopted in the literature. Within this framework, we show that the standard heteroskedasticity- and autocorrelation-consistent estimate of the long-run variance converges in distribution to a nonstandard random variable that depends on nuisance parameters. Notwithstanding this result, the corresponding t-statistic is shown to still possess a standard normal limit distribution. To improve the quality of inference in small samples, we propose a dependent wild bootstrap-t procedure and establish its asymptotic validity under relatively weak conditions. Monte Carlo simulations demonstrate that our recommended approach performs favorably in finite samples relative to existing methods across a wide range of volatility specifications. Applications to international stock price indices and U.S. house prices illustrate the relevance of the advocated method in practice.

ANALYSIS OF BUBBLES ASSETS FOR WEIGHTED AVERAGE INTEREST RATES APPLIED TO BANK LOANS

This study examines the existence of the "bubble effect" in the average interest rates of loans applied by banks to various types of loans for consumers. The purpose of this article is the research of the bubble formations in the average interest rates applied by the banks to consumer, housing (home), vehicle, and commercial loan types. This article examines the existence of bubbles in the average loan interest rates of banks in Turkey using the GSADF unit root test developed by Phillips et al. (2015). Bubble assets are analyzed with weekly data for the period June 2019–March 2023. Monte Carlo simulations performed obtained critical values for the GSADF unit root test. The results show that the bubble effect on housing loan interest rates is statistically significant at the 0.05 level. Against this, although the existence of a bubble effect in consumer, vehicle, and commercial loan interest rates has been determined, these bubbles are statistically insignificant.

Detecting house price bubbles in G7 countries: New evidence and heterogeneous determinants

In recent years, the high growth of house prices in G7 countries has attracted some attention from all sectors due to the role of the real estate bubble in the global financial crisis of 2008. In this research, we analyzed the house price bubbles and their determinants in G7 countries. Firstly, we detected multiple house price bubbles in G7 countries between 1970 and 2022 and located when the house price bubbles emerged and burst. Second, we investigated the determinants of house price bubbles in each country and in the G7 countries as a whole. The results show that the level of house price bubbles and their determinants is significantly diversified over countries. However, total population, size of private debt, GDP per capita, and urbanization are among the common drivers of the whole G7 countries. Based on these results, we provide some suggestions on the critical points for a stable real estate market development.

Artificial intelligence as a core of the new industrial revolution: prospects and limitations

The purpose of the article is to define prospects and limitations of artificial intelligence as a core of in the new industrial revolution. The definition of the concept of AI in the scientific community remains the subject of heated debate. At the same time, in the regulatory and legal plane, a trend is being formed towards unification of the concept of AI. Based on the analysis conducted and literary sources, the following prospects for AI can be identified on theoretical and practical levels. On theoretical level: (1) alienation of tacit knowledge from the individual (employee and entrepreneur); (2) optimization of the planning system; (3) revision of the socialist-calculation debate; (4) decreasing information asymmetry. On practical level: (1) formation of new products and markets; (2) increasing labor and capital productivity; (3) massive creation of new jobs; (4) optimization of business processes; (5) opportunity for rapid growth for small businesses and startups. Limitations: (1) long-term structural unemployment; (2) inflated expectations from AI and, as a consequence, the possible formation of a speculative bubble in the global stock market; (3) energy consumption of AI; (4) outdated pre-AI corporate culture and regulatory environment. Further improvement of AI (including the transition from AI to AGI) and the expansion of its use can make a significant contribution to solving problems related to economic calculation and minimizing information asymmetry, and therefore optimizing transaction costs in the economy. AI, certainly acting as a locally useful tool at the level of individual enterprises and organizations, causes the acceleration of attracting funds to the stock market, which can lead to the formation of a bubble on global level. If this bubble bursts, expectations about the economic efficiency of AI will be revised, and some AI-related companies will experience significant margin reductions (perhaps losses and bankruptcies). But this, in turn, will initiate the next stage of AI development, will accelerate its transition from the current narrow specialization to the creation of full-fledged general artificial intelligence (artificial general intelligence), which has a greater potential to change the economy at all levels. As a result, AI will become established as the core of the new industrial revolution.

Comparative Analysis Between Japan's Real Estate Economy and China's Real Estate Status

Japan's real estate bubble economy in the 1990s caused a major blow to the Japanese economy, Japan entered the "disappearing 30 years". The causes of Japan's real estate bubble economy and the reasons why the bubble burst are worthy of the world's countries to learn from. 21st century since the rapid development of China's real estate economy, housing prices are growing rapidly. The real estate economy has been overheated in some areas, although the Chinese government has taken relevant measures to cool down, still can't relax the vigilance, people should always pay attention to the overheated areas of real estate prices, land prices. Through the comparison between China and Japan, although the economic structure and development trend are similar when the property overheating phenomenon occurs, the economic development background and international background between the two countries are different, and the governments of the two countries have adopted different strategies to deal with the property overheating phenomenon. So in conclusion, although there are some areas in China where real estate is overheating, China's real estate market will not burst the bubble. In order to prevent China's real estate bubble from bursting and its impact on economic development, China should pay attention to the reasons behind it and make targeted policy adjustments, while also drawing on the lessons learned from other countries to promote the healthy and stable development of the real estate economy.

Impacts of CEO-employee pay disparity on investor behavior and market dynamics: Evidence from laboratory asset markets

This study explores the impacts of CEO-to-employee pay disparity on investor behavior and market dynamics using an experimental methodology. We employed two laboratory asset markets with identical company valuations but differing CEO-employee pay ratios. Our findings reveal that a higher pay ratio leads investors to quote higher prices for the company's stock. This effect is driven by two conflicting mechanisms of social preference: inequality aversion, which motivates investors who value fairness to quote lower prices for stocks of companies with high pay ratios, and social comparison, where the high pay ratio prompts investors to compare their wealth with that of CEOs, thus becoming more risk-seeking and quoting higher prices. Moreover, higher pay ratios contribute to increased stock prices, fostering larger market bubbles, enhancing the dispersion of investor opinions, boosting trading volumes, and escalating market volatility. This study enriches our understanding of how asset markets react to CEO-to-employee pay disparities, providing valuable insights for policymakers and market participants.

Like a moth to a flame: Do stock market bubbles exacerbate credit risks of peer‐to‐peer lending?

AbstractWe establish a causal link between stock market bubbles and credit risks from peer‐to‐peer lending. Employing a fuzzy regression discontinuity design based on retail investors' disproportional increase in stock market participation when the Shanghai Stock Exchange composite index exceeds 3500, we find that both the default rate and the degree of delinquency rise disproportionately for loans borrowed above the 3500 threshold. This effect is more pronounced among loans of lower quality and when borrowers are more overconfident and less risk averse. Overall, our results suggest that FinTech developments could amplify financial risks and induce contagion across markets.

Effect of financial contagion between real and financial sectors on asset bubbles: A two‐layer network game approach

AbstractUnderstanding the mechanism of asset bubble formation is important for maintaining financial stability and healthy functioning of the economic system. With gradual emphasis on the complex characteristics of financial markets, a new perspective for analyzing the emergence of asset bubbles is emerging: how to integrate the real economy with financial markets composed of heterogeneous individuals. In this study, we propose a two‐layer network game to investigate the impact of financial contagion between the real and financial sectors on asset bubbles. Among their interactions, shadow banking activities in both sectors increase the contagion risk across financial markets and construct a broader financial system. Both credit interactions and peer learning effects are captured in the network framework. Simulating relevant regulation policies, our experiments indicate that regulators should closely monitor returns on assets by setting an upper threshold. Financialization in the real sector significantly exacerbates the formation of asset bubbles, with medium‐level borrowing constraints minimizing bubble dynamics most effectively. The financialization practices of mature industries should be strictly regulated, while innovative industries should be allowed moderately flexible financing practices. The degree of friction within the financial market should be flexibly calibrated for financial institutions and genuine enterprises, aiming to mitigate systemic risks in the financial market while fostering robust growth in the real economy.

Introducing a novel fragility index for assessing financial stability amid asset bubble episodes

This paper is devoted to the development of an innovative fragility index designed to capture comprehensively the dynamics of financial stability during periods characterized by asset bubbles. Utilizing a multifaceted methodological framework, the study begins by identifying bubble occurrences and calculating the delta CoVaR systemic risk metric. Building on established macroeconomic methodologies, we then propose an indicator to quantify the impact of financial bubbles on the stability of an emerging market. Specifically, we construct two coincident indicators based on daily observations of financial stability for the twenty most liquid Romanian companies. The first indicator is derived from the delta CoVaR values of these companies, while the second is computed using the residuals of a model that employs the same financial stability metric as the dependent variable, with a binary variable representing the presence of asset bubbles as the explanatory factor. This second coincident indicator tracks financial stability in the absence of bubble effects. The disparity between these two indicators forms the basis for the creation of an index, termed the “bubble fragility index,” which measures the overall susceptibility of financial stability to asset bubbles. In the context of the Romanian market, this study demonstrates that periods marked by asset bubbles are associated with elevated systemic risks. Our findings indicate that the presence of bubbles significantly intensifies financial risk factors, creating conditions conducive to severe market corrections and economic downturns. We identify specific intervals during which fragility reaches peak levels, including June to September 2018, December 2018 to March 2019, March 2020, and March 2022.

Análisis económico del derecho de las medidas no-convencionales del Banco Central Europeo

This study delves into the significance and effectiveness of unconventional monetary policy measures adopted by central banks within the current economic policy framework. These measures are employed when conventional tools prove inefficient in stimulating or stabilizing the economy, influencing interest rates, inflation, and economic activity. The hypothesis will be tested through quantitative analysis, encompassing macroeconomic data and time series analysis, and examining various economic schools and theories. Additionally, potential long-term problems associated with these measures will be explored. The expected conclusions of this analysis aim to demonstrate that unconventional measures implemented by central banks have the potential to significantly impact the economy, particularly during economic crises. It is anticipated that “Quantitative Easing” will provide increased liquidity to the financial system and lower long-term interest rates. Furthermore, the study will assess potential side effects, such as income inequality, financial risks, price distortions, or the formation of asset bubbles. This research underscores the critical importance of unconventional monetary policies in contemporary economic discourse while scrutinizing their long-term implications.

Detecting speculative bubbles in the Chinese energy market: evidence from a GSADF test

ABSTRACT Analysing bubbles in China’s energy futures market facilitates the identification of the unique driving factors of bubbles in emerging markets. We apply the Generalized Supremum Augmented Dickey-Fuller (GSADF) and Supremum Augmented Dickey-Fuller (SADF) to verify the bubbles of crude oil (SC), power coal (ZC) and liquefied petroleum gas (LPG). Furthermore, we use the GSADF method to identify the definite generation and bursting times of these futures. The empirical results show that three bubbles occurred in the SC and LPG markets between 22 June 2020 and 26 September 2022 while four occurred in ZC during the same period. As an international commodity, SC bubbles are highly influenced by global factors, such as the global economy and geopolitical situation. In China, ZC bubbles are mainly influenced by domestic factors, such as price guidance, environmental protection policies and power demand. LPG bubbles are influenced by global oil prices and domestic policy regulations. Therefore, based on the timely bubble detection method, policymakers may take ex ante measures, such as regularly assessing the risk of bubbles and augmenting supply in the spot market, rather than simply adopting ex post strict price control. Additionally, investors and entrepreneurs can take early risk-hedging steps to reduce potential losses.

The Research of Real Estate Price Bubble in Case of Hengda Real Estate Company

Real state bubble refers to a continuous process of abrupt increase of selling price which excesses value. Therefore the economy is so full of bubbles that cannot reflect material wealth. When the price is too high to afford by consumers, the whole industry have risk to collapse. In order to research reasons lead to real estate bubble, this paper uses liner regression method to explore factors that influence real state selling price. As a result, the real state selling price is positive relative to land price and resident disposable income and negatively relative to interest rate. Additionally, this research also takes a example of Hengda to prove the result.

Local land regulatory governance and land transaction prices: Micro evidence from land audits

It is of great significance to explore the role of land supervision in the standardization of local land transactions. We document the DID strategy to systematically evaluate how land audits affect the transactions in the land market. The results show that: (1) land audits have restrained the transactions of low price of industrial lands and the high price of commercial and residential lands, raised the unit price of industrial lands transactions, and reduced the price of commercial and residential lands, and these effects would not exist in the public sectors land transactions; (2) the impacts of land audits are more pronounced in State-Owned Enterprises (SOEs) and enterprises with large-scale operations and high capital intensity; (3) audits have overall positive significance, which has increased the total investment of local industrial enterprises and reduced the investment bubble. However, there are no deterrent effects. The conclusions have important implications for our understanding of the loss of lands and resources, supervision, and the standardized construction of the trading market.

Implications of China’s Innovative Drug Investment Bubble

Implications of China’s Innovative Drug Investment Bubble

Investigating Financial Bubbles and Bursts: A Psychological Perspective

Investigating Financial Bubbles and Bursts: A Psychological Perspective

The influence of psychological factors on investment decision-making: Psychological features of economic relations formation

The article aimed to analyse the influence of psychological factors on the investment decision-making process, which shapes the economic behaviour of investors in Ukraine. The research involved surveys and experimental tasks conducted among investors, with the data analysed using statistical methods to identify the impact of psychological factors on investment decisions. Fear and greed have been found to be most significant emotions affecting investment decisions, whereas fear leads to excessive caution and risk avoidance. In contrast, greed drives investors to take on excessive risks. Overconfidence in one’s knowledge and skills results in an overestimation of opportunities and an increased risk of losses, while confirmation bias leads investors to seek information that supports their previous decisions, ignoring conflicting data. Expert opinions and group behaviour significantly influence investment decisions, particularly under conditions of uncertainty, often resulting in herd behaviour and the formation of economic bubbles. The experimental tasks demonstrated that investors frequently make irrational decisions under the influence of emotions and cognitive biases, even when they can access complete information about risks and opportunities. The survey results also indicated that investors with higher levels of financial literacy are less susceptible to the influence of emotions and cognitive biases, highlighting the importance of financial education in improving the quality of investment decisions. These findings illustrate how psychological factors can distort the investment decision-making process and underscore the necessity of considering these factors when developing investment strategies

Caring for uncommon bodies: Commoning yoseba through indifferent care and working together

ABSTRACT This study examines the emergence of care as a commoning practice within grassroots movements by focusing on Sōgidan, an activist group supporting rough sleepers in San’ya, Tokyo. San’ya is yoseba (day labor auction market), a historical urban margin turning into a service hub. Produced as cheap, disposable labor in the process of Japanese modernization, Japan’s day laborers were enclaved in yoseba and left without social protection after the economic bubble burst. However, they were not merely victims; they embodied a rebellious subjectivity, actively breaking away from the oppressive society. Despite welfare provisions after the 2000s, many day laborers refused aid and continued to sleep on the streets. Through extensive archival research, ethnographic observation, and in-depth interviews, this paper illuminates how Sōgidan has developed strategies of care to relate to the underclass, the historical others who refuse aid. Sōgidan embodies and carries forward the underclass movement, which uniquely echoed feminist ethics of care. It also initiates the creation of the radical commons, reconfiguring the distance between individuals and collectives, and sharing precariousness differently from capitalist norms. By linking Sōgidan’s practices to feminist ethics of care, this research contributes to opening up new perspectives of care and in(ter)dependence toward the commons.

Scars of the job market “ice-age”

Abstract Existing studies found that entering the labor market during a recession has persistent negative effects—the scarring effects—on employment and earnings for Japanese men. The cohorts who entered the labor market during the prolonged recession between 1993 and 2004 are called “the ice-age cohorts,” and the persistent gap between them and older cohorts who entered the labor market during the bubble economy is often interpreted as the scarring effect of business cycle conditions at entry. However, the existing studies in Japan use data covering cohorts who enter the labor market in the 1990s or earlier. Motivated by the lack of empirical evidence with updated data, this article revisits the scarring effects of a recession at labor market entry on employment and earnings using data covering graduation cohorts 1984–2013. Younger cohorts who enter the labor market during the recovery do not earn more or enjoy more stable employment than the cohorts who enter the bottom of the ice-age, and that the effects of unemployment rate at entry on employment and earnings are no longer statistically significant for cohorts who enter the labor market after the job market ice-age. I also discuss potential factors that may have weakened scarring effects.