Heterogeneous trading and complex price dynamics

We review the book “Behavioural Rationality and Heterogeneous Expectations in Complex Economic Systems” written by Cars Hommes and discuss the research trends on the dynamic interaction between heterogeneous investment and complex asset price movements.     

House price dynamics: Fundamentals and expectations

We investigate whether expectations that are not fully rational have the potential to explain the evolution of house prices and the price-to-rent ratio in the United States. First, a stylized asset-pricing model solved under rational expectations is used to derive a fundamental value for house prices and the price–rent ratio. Although the model can explain the sample average of the price–rent ratio, it does not generate the large and persistent fluctuations observed in the data. Then, we consider a rational bubble solution, an extrapolative expectations solution and a near rational bubble solution. In this last solution agents extrapolate the future from the latest realizations and the degree of extrapolation is stronger in good times than in bad times, generating waves of over-optimism. We show that under this solution the model not only is able to match key moments of the data but can also replicate the run up in the U.S. house prices observed over the 2000–2006 period and the subsequent sharp downturn.     

Complexity traits and synchrony of cryptocurrencies price dynamics

Decisions in Economics and Finance - In this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three...     

Entry and price dynamics in a perfect foresight model

This paper studies firms' entry and price dynamics in a model that combines the assumptions of free entry and perfect foresight with the hypothesis of consumer's loyalty postulated by Phelps and Winter. The analysis of the transition to long-run equilibrium reveals that, in such a model, the entry of firms is related to the difference between current prices and costs. In relation to the growth of the firms' output, it is shown that the model is consistent with Gibrat's Law. Finally, it is shown that the size distribution of firms approaches asymptotically a Pareto distribution.     

Cobweb dynamics and price dispersion in illicit drug markets

Extreme price dispersion is a hallmark of illegal drug markets, and this apparent contradiction to the law of one price has long puzzled drug market economists. We propose a novel explanation for this dispersion: the coupling of dealers’ unwillingness to hold inventory with dealers’ imperfect foresight concerning future prices and/or random lead times when “ordering” drugs from higher-level suppliers. Unwillingness to hold inventory means drug markets might operate consistent with a cobweb model. The classic cobweb model was inspired by the observation of cyclic (typically annual) fluctuations in commodity prices. However, with minor changes that make the model more realistic the resulting price trajectories can be highly variable or even chaotic, not just periodic. Cobweb dynamics can also amplify the variability created by supply chain disruptions.     

Agents interaction and price dynamics: evidence from the laboratory

Journal of Economic Interaction and Coordination - Using data collected from an experimental double auction market, we study the dynamics of interaction among traders. Our focus is on the effect...     

The nonlinear price dynamics of U.S. equity ETFs

We investigate the price dynamics of large market-capitalization U.S. equity exchange-traded funds (ETFs) in order to uncover trader motivations and strategy. We show that prices of highly liquid ETFs can deviate significantly from their daily net asset values. By adjusting for changes in valuations, we report the impact of non-classical variables including price trend and volatility using data from 2008 to 2011. We find a cubic nonlinearity in the trend suggesting that traders are not only aware of the underreaction of others, but also self-optimize by anticipating others’ reactions, and sell when the uptrend is stronger than usual.     

Equilibrium price dynamics in an overlapping-generations exchange economy

An extension to the Yaari (1965)–Blanchard (1985) continuous time overlapping generations model for an endowment Arrow–Debreu economy with an age-structured population is presented. It is proved that Arrow–Debreu equilibrium prices are represented by a double linear integral equation, and depend on the age-distributions of population and endowments. For an economy with a balanced growth, and logarithmic utility, we prove that bubbles may exist if endowments are distributed earlier than some critical age.     

Income distribution and income dynamics in the United Kingdom

In this paper, we propose a model of income dynamics which takes account of mobility both within and between jobs. The model is a hybrid of the mover‐stayer model of income dynamics and a geometric random walk. In any period, individuals face a discrete probability of ‘moving’, in which case their income is a random drawn from a stationary recurrent distribution. Otherwise, they ‘stay’ and incomes follow a geometric random walk. The model is estimated on income transition data for the United Kingdom from the British Household Panel Survey (BHPS) and provides a good explanation of observed non‐linearities in income dynamics. The steady‐state distribution of the model provides a good fit for the observed, cross‐sectional distribution of earnings. We also evaluate the impact of tertiary education on income transitions and on the long‐run distribution of incomes. Copyright © 2001 John Wiley & Sons, Ltd.     

Monetary policy,global liquidity and commodity price dynamics

This paper examines the interactions between money, interest rates, goods and commodity prices at a global level. Aggregated data for major OECD countries are therefore analysed in a cointegrated VAR framework. Our empirical results for the period ranging from the 1970s to 2008 support the view that, when controlling for interest rate changes and thus different monetary policy stances, money (defined as a global liquidity aggregate) is still a key factor to determine the long-run homogeneity of commodity and goods prices movements.     

Asset price dynamics with heterogeneous beliefs and local network interactions

In this paper we investigate the effects of network topologies on asset price dynamics. We introduce network communications into a simple asset pricing model with heterogeneous beliefs. The agents may switch between several belief types according to their performance. The performance information is available to the agents only locally through their own experience and the experience of other agents directly connected to them. We model the communications with four commonly considered network topologies: a fully connected network, a regular lattice, a small world, and a random graph. The results show that the network topologies influence asset price dynamics in terms of the regions of stability, amplitudes of fluctuations and statistical properties.     

Asset price and wealth dynamics in a financial market with heterogeneous agents

This paper considers a discrete-time model of a financial market with one risky asset and one risk-free asset, where the asset price and wealth dynamics are determined by the interaction of two groups of agents, fundamentalists and chartists. In each period each group allocates its wealth between the risky asset and the safe asset according to myopic expected utility maximization, but the two groups have heterogeneous beliefs about the price change over the next period: the chartists are trend extrapolators, while the fundamentalists expect that the price will return to the fundamental. We assume that investors’ optimal demand for the risky asset depends on wealth, as a result of CRRA utility. A market maker is assumed to adjust the market price at the end of each trading period, based on excess demand and on changes of the underlying reference price. The model results in a nonlinear discrete-time dynamical system, with growing price and wealth processes, but it is reduced to a stationary system in terms of asset returns and wealth shares of the two groups. It is shown that the long-run market dynamics are highly dependent on the parameters which characterize agents’ behaviour as well as on the initial condition. Moreover, for wide ranges of the parameters a (locally) stable fundamental steady state coexists with a stable ‘non-fundamental’ steady state, or with a stable closed orbit, where only chartists survive in the long run: such cases require the numerical and graphical investigation of the basins of attraction. Other dynamic scenarios include periodic orbits and more complex attractors, where in general both types of agents survive in the long run, with time-varying wealth fractions.     

The dynamics of changes in the female wage distribution in the USA: a quantile regression approach

This paper examines the female wage structure focusing on changes at different points in the wage distribution. Newly developed quantile regression methods are used in analysing data from the March Current Population Survey. The results show that while the most significant changes for the less skilled women took place at the bottom of the wage distribution, for the more skilled groups changes occurred at both ends of the distribution. Consequently, wage inequality decreased for the high-school graduates and increased for the younger college graduates. Furthermore, the more highly skilled women experienced the steepest gain in wages regardless of their position in the distribution. © 1998 John Wiley & Sons, Ltd.     

城市旅游景区的游客构成及空间分流

大众旅游的逐步普及和城市游憩的迅猛发展,使城市旅游空间超载问题日益加剧。在分析游客构成和比较不同类型游客空间行为特点的基础上,认为高级别旅游景区应主要承担旅游功能、弱化游憩功能,并提出了城市区域内不同等级的旅游空间合理分工模式。     

A calibration procedure for analyzing stock price dynamics in an agent-based framework

In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of (Brock and Hommes, 1998), we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a nonlinear constrained optimization that can be solved numerically via a gradient-based method. The calibration results show that the simplest version of the Brock and Hommes model, with two trader types, fundamentalists and trend-followers, replicates nicely the price series of four different markets indices: the S&P 500, the Euro Stoxx 50, the Nikkei 225 and the CSI 300. We show how the parameter values of the calibrated model are important in interpreting the trader behavior in the different markets investigated. These parameters are then used for price forecasting. To further improve the forecasting, we modify our calibration approach by increasing the trader information set. Finally, we show how this new approach improves the model׳s ability to predict market prices.     

Permanent and transitory shocks in owner-occupied housing: A common trend model of price dynamics

Significant fluctuations in house prices have received considerable attention in recent years. An understanding of the forces underlying the departure from fundamental values is important in explaining the mechanisms underlying housing market performance and predicting potential house price changes in the future. This study constitutes the first use of a common trend (CT) model to analyze private house prices in the Swedish market. We employ a cointegration system to analyze the macro variables of consumption expenditure per capita, user costs and house prices. We decompose shocks into those resulting from fundamental variables, specified in this research as income and the interest rate, and those resulting from cyclical variables. The results indicate that interest rates play a dominant role in explaining house price swings, and are also significant in determining user costs for households in Sweden. Transitory shocks are found to have little explanatory power for house prices and user costs in the long run. A number of tests have been performed to verify the robustness of the specification and results.     

Oil price shocks,geopolitical risks,and green bond market dynamics

This research explores the causal relation among oil price, geopolitical risks, and green bond index in the United States from December 2013 to January 2019. Unlike the conventional linear model specification used in earlier works, we evaluate causal relations based on Granger-causality in quantile analysis. Our empirical results reveal unidirectional Granger-causality from geopolitical risk to oil price at the extreme quantiles. We also observe a significant bi-directional causality from oil price to green bond index for the lower quantiles. Findings also reveal causality from geopolitical risk to green bond index in the lower quantiles of the distribution. Therefore, knowledge of these causal relationships can help policy makers to evaluate and implement effective policies to prevent sudden and substantial oil price shocks and geopolitical risk.     

House price convergence: Evidence from US state and metropolitan area panels

We study house price convergence in panels of US states and metropolitan areas. Our analysis is centered on three issues. First, we test whether the US house prices are converging over time using log t convergence test by Phillips and Sul (2007). The test results suggest that there is little evidence of overall convergence. The second issue is to investigate the possibility of a convergence club where the cross-sectional dispersion of house prices of the club members decreases over time. We utilize a clustering algorithm and the results support that there is strong evidence of multiple convergence clubs. Finally, we examine the general characteristics of the various convergence and divergence subgroups as well as some important driving forces of convergence clubs. We find that housing supply regulation together with climate are important determinants of convergence club membership.     

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.