33 research outputs found

    Bubble economics

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    This article provides a self-contained overview of the theory of rational asset price bubbles. We cover topics from basic definitions, properties, and classical results to frontier research, with an emphasis on bubbles attached to real assets such as stocks, housing, and land. The main message is that bubbles attached to real assets are fundamentally nonstationary phenomena related to unbalanced growth. We present a bare-bones model and draw three new insights: (i) the emergence of asset price bubbles is a necessity, instead of a possibility; (ii) asset pricing implications are markedly different between balanced growth of stationary nature and unbalanced growth of nonstationary nature; and (iii) asset price bubbles occur within larger historical trends involving shifts in industrial structure driven by technological innovation, including the transition from the Malthusian economy to the modern economy

    Bubbles, Banks, and Financial Stability

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    This paper asks two main questions: (1) What makes some asset price bubbles more costly for the real economy than others? and (2) When do costly bubbles occur? We construct a model of rational bubbles under credit frictions and show that when bubbles held by banks burst this is followed by a costly financial crisis. In contrast, bubbles held by ordinary savers have relatively muted effects. Banks tend to invest in bubbles when financial liberalisation decreases their profitability.

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Bubbles, Banks, and Financial Stability

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    This paper asks two main questions: (1) What makes some asset price bubbles more costly for the real economy than others? and (2)When do costly bubbles occur? We construct a model of rational bubbles under credit frictions and show that when bubbles held by banks burst this is followed by a costly financial crisis. In contrast, bubbles held by ordinary savers have relatively muted effects. Banks tend to invest in bubbles when financial liberalisation decreases their profitability.Rational bubbles, Financial Frictions, Financial Stability

    Essays in asset price bubbles

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    This thesis studies the field of asset price bubbles. It is comprised of three independent chapters. Each of these chapters either directly or indirectly analyse the existence or implications of asset price bubbles. The type of bubbles assumed in each of these chapters is consistent with rational expectations. Thus, the kind of price bubbles investigated here are known as rational bubbles in the literature. The following describes the three chapters. Chapter 1: This chapter attempts to explain the recent US housing price bubble by developing a heterogeneous agent endowment economy asset pricing model with risky housing, endogenous collateral and defaults. Investment in housing is subject to an idiosyncratic risk and some mortgages are defaulted in equilibrium. We analytically derive the leverage or the endogenous loan to value ratio. This variable comes from a limited participation constraint in a one period mortgage contract with monitoring costs. Our results show that low values of housing investment risk produces a credit easing effect encouraging excess leverage and generates credit driven rational price bubbles in the housing good. Conversely, high values of housing investment risk produces a credit crunch characterized by tight borrowing constraints, low leverage and low house prices. Furthermore, the leverage ratio was found to be procyclical and the rate of defaults countercyclical consistent with empirical evidence. Chapter 2: It is widely believed that financial assets have considerable persistence and are susceptible to bubbles. However, identification of this persistence and potential bubbles is not straightforward. This chapter tests for price bubbles in the United States housing market accounting for long memory and structural breaks. The intuition is that the presence of long memory negates price bubbles while the presence of breaks could artificially induce bubble behaviour. Hence, we use procedures namely semi-parametric Whittle and parametric ARFIMA procedures that are consistent for a variety of residual biases to estimate the value of the long memory parameter, d, of the log rent-price ratio. We find that the semi-parametric estimation procedures robust to non-normality and heteroskedasticity errors found far more bubble regions than parametric ones. A structural break was identified in the mean and trend of all the series which when accounted for removed bubble behaviour in a number of regions. Importantly, the United States housing market showed evidence for rational bubbles at both the aggregate and regional levels. In the third and final chapter, we attempt to answer the following question: To what extend should individuals participate in the stock market and hold risky assets over their lifecycle? We answer this question by employing a lifecycle consumption-portfolio choice model with housing, labour income and time varying predictable returns where the agents are constrained in the level of their borrowing. We first analytically characterize and then numerically solve for the optimal asset allocation on the risky asset comparing the return predictability case with that of IID returns. We successfully resolve the puzzles and find equity holding and participation rates close to the data. We also find that return predictability substantially alter both the level of risky portfolio allocation and the rate of stock market participation. High factor (dividend-price ratio) realization and high persistence of factor process indicative of stock market bubbles raise the amount of wealth invested in risky assets and the level of stock market participation, respectively. Conversely, rare disasters were found to bring down these rates, the change being severe for investors in the later years of the life-cycle. Furthermore, investors following time varying returns (return predictability) hedged background risks significantly better than the IID ones

    Furman Magazine. Volume 50 Issue 2 - Full Issue

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    How to identify UK housing bubbles? A decision support model

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    The purpose of this thesis is to provide a decision support model for the early diagnosis of housing bubbles in the UK during the phenomenon’s maturity process. The development process of the model is divided into four stages. These stages are driven by the normal distribution theorem coupled with the case study approach. The application of normal distribution theory is allowed through the usage of several parametric tools. An empirical application of the model is conducted using UK housing market data for the period of 1983-2011; and by placing particular emphasis on the last two UK housing bubble case studies, 1986 to 1989 and 2001/2 to 2007. The central hypothesis of the model is that during housing bubbles, all speculative activities of market participants follow an approximate synchronisation. The new algorithmic approach successfully identifies the well-known historical UK bubble episodes over the period of 1983-2011. The proposed algorithm acts like an index or a thermometer to gauge the ‘‘fever’’ of a housing bubble in the UK at any point in time. In this approach, the housing bubble is no longer invisible until the crash, and as such can be monitored over time. The study further determines that for uncovering housing bubbles in the UK, house price changes have the same weight as the debt-burden ratio when their velocity is positive. The application of this model-algorithm has led us to conclude that the model’s outputs fluctuate approximately in line with phases of the UK real estate cycle. Finally, the research has provided a new and more technical definition of housing bubbles. The phenomenon is defined as a situation in which all speculative activities of market participants achieve an approximate synchronisation. Consequently, under such regime, the model expects that (during housing bubbles) an irrational, synchronised and periodic increase in a wide range of relevant variables must occur to anticipate a bubble component. In this definition, the relevant variables are those that exhibit a periodic and irrational acceleration in the rate of change, which, in turn, is synchronised with other relevant variables. Therefore, the model views such variables as symptoms for identifying housing bubbles. This thesis proposes a new measure for studying the presence of irrational housing bubbles. This measure is not simply an ex post detection technique but employs dating algorithms that use data only up to the point of analysis for an on-going bubble assessment, giving an early warning diagnostic that can assist market participants and regulators in market monitoring

    BIOFILM DEFOULING USING MICROBUBBLES GENERATED BY FLUIDIC OSCILLATIONS

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    The physical separation offered by membrane filters such as Reverse Osmosis (RO), Microfiltration (UF), Ultrafiltration (UF), and Nanofiltration (NF) has reduced the operating cost of such processes compared to distillation and chemical extraction. The advantages of the membrane such as high selectivity, high capacity, feasibility and cost effectiveness make them very good alternatives in separation industries especially cleaning technologies. Membranes, however, are easily fouled. Since the methods developed to defoul a membrane such as ultrasonic and chemical backflushing are always damaging to the membrane, this study is to explore the potential of microbubbles to restore the membrane to its operational condition. Microbubble clouds generated using fluidic oscillation produce non-coalescent bubbles, smaller and more uniform in size. Fluidic oscillation generated microbubbles are influenced by adjusting flow rate and oscillation frequency in conjunction with the diffuser pore size. The size of the microbubble produced is ranging from 30μm to 500μm at the lowest flow rate of air. The effect for cleaning purposes of microbubble injection with and without fluidic oscillation is explored by examination using Scanning Electron Microscopy (SEM), Total Suspended Solid (TSS) and system operational pressure drop (TMP). The smaller microbubble means higher surface contact area to remove the biofilm on the membrane filter. To further validate the effect of microbubbles on detaching and cleaning, FO generated microbubbles were sparged on biofilm (Chlamydomonas algae and HeLa cells) cultured on microscope slide surface. The detachment rates were compared by observing the density of algae and cells removed from the surface using lux meter and cell counting method. It is found that microbubbles generated using Higher Oscillation frequency of Fluidic Oscillator (HOFO) has a higher detachment and defouling rate. The highest defouling rate recorded for MF filter was 9.53mbar/min using HOFO, followed by 6.22mbar/min of microbubbles generated using Lower Oscillation frequency of Fluidic Oscillator (LOFO). Similar trends were observed in algae and cell detachment, the highest oscillation frequency of 335Hz has the highest detachment rate of 1.775lx/min and 1.7 ́104 cell/ml respectively. For MF systems, microbubbles generated using Higher Oscillation Frequency Oscillator (HOFO), increased the defouling rate by 64%. Similar observation recorded where HOFO increased detachment rate of Chlamydomonas algae and HeLa cells by 42% and 95% respectively
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