Papers by Dimitri Kroujiline
A Simple Economic Model with Interactions
SSRN Electronic Journal, 2020
Macroeconomic models rarely make explicit how agents actually interact. If however interaction is... more Macroeconomic models rarely make explicit how agents actually interact. If however interaction is explicitly specified, the link between the micro and macro properties of models becomes much richer, leading in certain cases to the onset of macro-level instability. This working paper incorporates interactions among agents at a micro level into the basic Solow model to study disequilibrium behaviors and economic instability on a macro level. In particular, we investigate two limiting cases. First, we recover the classic case where the economy converges to the balanced growth path and then grows along it. In the second case, where the interactions-fueled demand dynamics become the main force driving the economy, we obtain business cycles as quasiperiodic endogenous fluctuations.<br>
SSRN Electronic Journal, 2021
We develop a tractable macroeconomic model that captures dynamic behaviors across multiple timesc... more We develop a tractable macroeconomic model that captures dynamic behaviors across multiple timescales, including business cycles. The model is anchored in a dynamic capital demand framework reflecting an interactions-based process whereby firms determine capital needs and make investment decisions on a micro level. We derive equations for aggregate demand from this micro setting and embed them in the Solow growth economy. As a result, we obtain a closed-form dynamical system with which we study economic fluctuations and their impact on long-term growth. For realistic parameters, the model has two attracting equilibria: one at which the economy contracts and one at which it expands. This bi-stable configuration gives rise to quasiperiodic fluctuations, characterized by the economy's prolonged entrapment in either a contraction or expansion mode punctuated by rapid alternations between them. We identify the underlying endogenous mechanism as a coherence resonance phenomenon. In addition, the model admits a stochastic limit cycle likewise capable of generating quasiperiodic fluctuations; however, we show that these fluctuations cannot be realized as they induce unrealistic growth dynamics. We further find that while the fluctuations powered by coherence resonance can cause substantial excursions from the equilibrium growth path, such deviations vanish in the long run as supply and demand converge.
Algorithmic Finance, 2015
We attempt to explain stock market dynamics in terms of the interaction among three variables: ma... more We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.
Algorithmic Finance, 2019
This paper suggests that business cycles may be a manifestation of coupled real economy and stock... more 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 th...
Chaotic streamlines in steady bounded three-dimensional Stokes flows
Physica D: Nonlinear Phenomena, 1999
ABSTRACT
Effectiveness of kinematic dynamo action in simple geophysical models
ABSTRACT
We attempt to explain stock market dynamics in terms of the interaction among three variables: ma... more We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.
SSRN Electronic Journal, 2015
In this paper we seek to demonstrate the predictability of stock market returns and explain the n... more In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. (2015). This heterogeneous framework enables us to capture dynamics at multiple timescales, expanding the model's applications and improving precision. We study the heterogeneous model theoretically and empirically to highlight essential mechanisms underlying certain market behaviors, such as transitions between bull-and bear markets and the self-similar behavior of price changes. Most importantly, we apply this model to show that the stock market is nearly efficient on intraday timescales, adjusting quickly to incoming news, but becomes inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics, attributable to a feedback mechanism acting over these horizons. Then, using the model, we design algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested results suggest that the return is predictable to the extent that successful trading strategies can be constructed to harness this predictability.
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Papers by Dimitri Kroujiline