Booms and Busts in Asset Prices

We show how low-frequency boom and bust cycles in asset prices can emerge from Bayesian learning by investors. Investors rationally maximize infinite horizon utility but hold subjective priors about the asset return process that we allow to differ infinitesimally from the rational expectations prior. Bayesian updating of return beliefs then gives rise to selfreinforcing return optimism that results in an asset price boom. The boom endogenously comes to an end because return optimism causes investors to make optimistic plans about future consumption. The latter reduces the demand for assets that allow to intertemporally transfer resources. Once returns fall short of expectations, investors revise return expectations downward and set in motion a self-reinforcing price bust. In line with available survey data, the learning model predicts return optimism to comove positively with market valuation. In addition, the learning model replicates the low frequency behavior of the U.S. price dividend ratio over the period 1926-2006.asset price fluctuations, boom and bust cycles

Booms and Busts in Asset Prices

We show how low-frequency boom and bust cycles in asset prices can emerge from Bayesian learning by investors. Investors rationally maximize infinite horizon utility but hold subjective priors about the asset return process that we allow to differ infinitesimally from the rational expectations prior. Bayesian updating of return beliefs then gives rise to self-reinforcing return optimism that results in an asset price boom. The boom endogenously comes to an end because return optimism causes investors to make optimistic plans about future consumption. The latter reduces the demand for assets that allow to intertemporally transfer resources. Once returns fall short of expectations, investors revise return expectations downward and set in motion a self-reinforcing price bust. In line with available survey data, the learning model predicts return optimism to comove positively with market valuation. In addition, the learning model replicates the low frequency behavior of the U.S. price dividend ratio over the period 1926-2006.

Internal Rationality, Imperfect Market Knowledge and Asset Prices

We present a decision theoretic framework in which agents are learning about market behavior and that provides microfoundations for models of adaptive learning. Agents are 'internally rational', i.e., maximize discounted expected utility under uncertainty given dynamically consistent subjective beliefs about the future, but agents may not be 'externally rational', i.e., may not know the true stochastic process for payoff relevant variables beyond their control. This includes future market outcomes and fundamentals. We apply this approach to a simple asset pricing model and show that the equilibrium stock price is then determined by investors' expectations of the price and dividend in the next period, rather than by expectations of the discounted sum of dividends. As a result, learning about price behavior affects market outcomes, while learning about the discounted sum of dividends is irrelevant for equilibrium prices. Stock prices equal the discounted sum of dividends only after making very strong assumptions about agents' market knowledge.learning, internal rationality, consumption based asset pricing

The Immunity of Polymer-Microemulsion Networks

The concept of network immunity, i.e., the robustness of the network connectivity after a random deletion of edges or vertices, has been investigated in biological or communication networks. We apply this concept to a self-assembling, physical network of microemulsion droplets connected by telechelic polymers, where more than one polymer can connect a pair of droplets. The gel phase of this system has higher immunity if it is more likely to survive (i.e., maintain a macroscopic, connected component) when some of the polymers are randomly degraded. We consider the distribution $p(\sigma)$ of the number of polymers between a pair of droplets, and show that gel immunity decreases as the variance of $p(\sigma)$ increases. Repulsive interactions between the polymers decrease the variance, while attractive interactions increase the variance, and may result in a bimodal $p(\sigma)$.Comment: Corrected typo

Patent Citations and International Knowledge Flow: The Cases of Korea and Taiwan

This paper examines patterns of knowledge diffusion from US and Japan to Korea and Taiwan using patent citations as an indicator of knowledge flow. We estimate a knowledge diffusion model using a data set of all patents granted in the U.S. to inventors residing in these four countries. Explicitly modeling the roles of technology proximity and knowledge decay and knowledge diffusion over time, we have found that knowledge diffusion from US and Japan to Korea and Taiwan exhibits quite different patterns. It is much more likely for Korean patents to cite Japanese patents than US patents, whereas Taiwanese inventors tend to learn evenly from both US and Japanese inventors. The frequency of a Korean patent citing a Japanese patent is almost twice that of the frequency of a Taiwanese patent citing a Japanese patent. We also find that a patent is much more likely to cite a patent from its own technological field than from another field.

House Price Booms and the Current Account

A simple open economy asset pricing model can account for the house price and current account dynamics in the G7 over the years 2001-2008. The model features rational households, but assumes that households entertain subjective beliefs about price behavior and update these using Bayes' rule. The resulting beliefs dynamics considerably propagate economic shocks and crucially contribute to replicating the empirical evidence. Belief dynamics can temporarily delink house prices from fundamentals, so that low interest rates can fuel a house price boom. House price booms, however, are not necessarily synchronized across countries and the model correctly predicts the heterogeneous response of house prices across the G7, following the fall in real interest rates at the beginning of the millennium. The response to interest rates depends sensitively on agents' beliefs at the time of the interest rate reduction, which are a function of the prior history of disturbances hitting the economy. According to the model, the US house price boom could have been largely avoided, if real interest rates had decreased by less after the year 2000.interest rates, house prices, short-term capital movements

Individual Professional Practice in the Company

Cílem této bakalářské praxe je popis absolvování odborné praxe ve firmě Digital Wizards Group s.r.o., ve které jsem působil jako frontend vývojář webových stránek. Náplní této praxe byl vývoj webových stránek v základních jazycích HTML a CSS a poté vývoj pomocí moderních nástrojů jako October CMS nebo frontend framework Materialize. Nejdříve jsem se zaměřil na firmu samotnou a na pozici, kterou jsem zastával, dále jsem popsal jednotlivé projekty, na jejichž vývoji jsem se podílel. V závěru práce jsem praxi zhodnotil a shrnul znalosti a dovednosti, které jsem získal, a které mi scházely.The object of this bachelor thesis is a description of professional practice I performed in company Digital Wizards Group s.r.o., where I worked as a frontend website developer. Main content of my practice was website development in basic languages HTML and CSS and later development with help of modern tool such as October CMS or Materialize frontend framework. First, I focused on the company itself and the position that I held then I described individual projects, whose development I participated in. In conclusion, I reviewed the practice summed up the skills and knowledge that I gained and skills and knowledge that I missed.460 - Katedra informatikyvýborn

Monoclonal antibodies and immunotherapy : theory and applications

Revision and update 2024This document is an update of a previous one published on the Papyrus site of the University of Montreal in 2023. It takes into account new therapeutic targets as well as monoclonal antibodies approved last year by the FDA. This update consists of two parts. Firstly. the theoretical bases underlying the antigen-antibody reaction and therefore the effectiveness of active and passive immunotherapy. On the other hand, a description and classification of the 70 antigenic targets as well as their 150 corresponding monoclonal antibodies currently used for passive immunotherapy

Stock market volatility and learning

Introducing bounded rationality into a standard consumption based asset pricing model with a representative agent and time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though we restrict consideration to learning schemes that imply only small deviations from full rationality. The findings are robust to the particular learning rule used and the value chosen for the single free parameter introduced by learning, provided agents forecast future stock prices using past information on prices. JEL Classification: G12, D84asset pricing, Learning, near-rational price forecasts

Stock Market Volatility and Learning

We study a standard consumption based asset pricing model with rationally investing agents but allow agents' prior beliefs about price and dividend behavior to deviate slightly from rational expectations priors. Learning about stock price behavior then causes the model to become quantitatively consistent with a range of basic asset prizing 'puzzles': stock returns display momentum and mean reversion, asset prices become volatile, the price-dividend ratio displays persistence, long-horizon returns become predictable and a risk premium emerges. Comparing the moments of the model with those in the data using confidence bands from the method of simulated moments, we show that our findings are robust to different assumptions on the system of beliefs and other model features. We depart from previous studies of asset prices under learning in that agents form expectations about future stock prices using past price observations.asset pricing, learning, near-rational price forecasts