scholarly journals An endogenous mechanism of business cycles

2021 ◽  
Vol 8 (3-4) ◽  
pp. 127-148
Author(s):  
Dimitri Kroujiline ◽  
Maxim Gusev ◽  
Dmitry Ushanov ◽  
Sergey V. Sharov ◽  
Boris Govorkov
Keyword(s):  
Stock Market ◽  
Business Cycles ◽  
Coupled System ◽  
Resonance Phenomenon ◽  
Market Model ◽  
Market Dynamics ◽  
Real Economy ◽  
Coherence Resonance ◽  
Market Interaction ◽  
Stable Equilibria

This paper suggests that business cycles may be a manifestation of coupled real economy and stock market dynamics and describes a mechanism that can generate economic fluctuations consistent with observed business cycles. To this end, we seek to incorporate into the macroeconomic framework a dynamic stock market model based on opinion interactions (Gusev et al., 2015). We derive this model from microfoundations, provide its empirical verification, demonstrate that it contains the efficient market as a particular regime and establish a link through which macroeconomic models can be attached for the study of real economy and stock market interaction. To examine key effects, we link it with a simple macroeconomic model (Blanchard, 1981). The coupled system generates nontrivial endogenous dynamics, which exhibit deterministic and stochastic features, producing quasiperiodic fluctuations (business cycles). We also inspect this system’s behavior in the phase space. The real economy and the stock market coevolve dynamically along the path governed by a stochastically-forced dynamical system with two stable equilibria, one where the economy expands and the other where it contracts, resulting in business cycles identified as the coherence resonance phenomenon. Thus, the incorporation of stock market dynamics into the macroeconomic framework, as presented here, allows the derivation of realistic behaviors in a tractable setting.

scholarly journals Stock market dynamics created by interacting agents

2006 ◽  
Vol 2006 ◽  
pp. 1-11
Author(s):  
Mohamed Riad Remita ◽  
Karl-Theodor Eisele
Keyword(s):  
Phase Transitions ◽  
Stock Market ◽  
Stock Price ◽  
Market Model ◽  
Market Dynamics ◽  
Market Crashes ◽  
Interacting Agents

We study a stock market model, consisting in a large number of agents, going eventually to infinity, and evaluate the stock price under the influence of opinions of different agents. Next we study the behavior of prices when the market is very nervous; there appear discontinuities (phase transitions) which can be interpreted as stock market crashes.

New Stock Market Model

1997 ◽  
Author(s):  
Brian NMI Thomas
Keyword(s):  
Stock Market ◽  
Market Model

scholarly journals Stochastic sensitivity of bull and bear states

2021 ◽  
Author(s):  
Jochen Jungeilges ◽  
Elena Maklakova ◽  
Tatyana Perevalova
Keyword(s):  
Additive Noise ◽  
Asset Price ◽  
Market Model ◽  
Asset Market ◽  
Stochastic Version ◽  
Market Participants ◽  
Price Process ◽  
Stochastic Sensitivity ◽  
Stable Equilibria ◽  
Parametric Noise

AbstractWe study the price dynamics generated by a stochastic version of a Day–Huang type asset market model with heterogenous, interacting market participants. To facilitate the analysis, we introduce a methodology that allows us to assess the consequences of changes in uncertainty on the dynamics of an asset price process close to stable equilibria. In particular, we focus on noise-induced transitions between bull and bear states of the market under additive as well as parametric noise. Our results are obtained by combining the stochastic sensitivity function (SSF) approach, a mixture of analytical and numerical techniques, due to Mil’shtein and Ryashko (1995) with concepts and techniques from the study of non-smooth 1D maps. We find that the stochastic sensitivity of the respective bull and bear equilibria in the presence of additive noise is higher than under parametric noise. Thus, recurrent transitions are likely to be observed already for relatively low intensities of additive noise.

scholarly journals Speculative housing markets and rent control: insights from nonlinear economic dynamics

2021 ◽  
Author(s):  
Noemi Schmitt ◽  
Frank Westerhoff
Keyword(s):  
Housing Market ◽  
Housing Stock ◽  
House Price ◽  
Housing Markets ◽  
Market Model ◽  
Market Dynamics ◽  
Rent Control ◽  
Forecasting Accuracy ◽  
Expectation Formation ◽  
Rent Level

AbstractWe propose a novel housing market model to explore the effectiveness of rent control. Our model reveals that the expectation formation and learning behavior of boundedly rational homebuyers, switching between extrapolative and regressive expectation rules subject to their past forecasting accuracy, may create endogenous housing market dynamics. We show that policymakers may use rent control to reduce the rent level, although such policies may have undesirable effects on the house price and the housing stock. However, we are also able to prove that well-designed rent control may help policymakers to stabilize housing market dynamics, even without creating housing market distortions.

A simple finite-difference stock market model involving intrinsic value

2008 ◽  
Vol 38 (3) ◽  
pp. 769-777
Author(s):  
Jan Melecký ◽  
Artur Sergyeyev
Keyword(s):  
Finite Difference ◽  
Stock Market ◽  
Intrinsic Value ◽  
Market Model

Linkages between cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles

2016 ◽  
Vol 9 (2) ◽  
pp. 123-146 ◽  
Author(s):  
Kim Hiang Liow
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Business Cycles ◽  
Spillover Effects ◽  
Real Estate Market ◽  
Stock Market Index ◽  
Content Type ◽  
Market Index ◽  
Cross Country ◽  
The Cross

Purpose This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014. Design/methodology/approach The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology. Findings There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered. Research limitations/implications The research is subject to the usual limitations concerning empirical research. Practical implications This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors. Originality/value In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.

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