Mikhail Anufriev's page

Recent Publications

Working Papers

(Re-)Inventing the traffic light: Designing recommendation devices for play of strategic games

Time pressure reduces financial bubbles: Evidence from a forecasting experiment

Leaning against the wind in the New Keynesian model with heterogeneous expectations

Social Distancing Policies and Intersectoral Spillovers: Australia vs Sweden

A model of network formation for the overnight interbank market

Work in Progress

Selected Publications

Recent Publications

"IEL-CDA model: A more accurate theory of behavior in continuous double auctions", 2025, with Jasmina Arifovic, Anil Donmez, John Ledyard and Valentyn Panchenko, Journal of Economic Dynamics & Control, 104840. [ Journal Article | Working Paper ]

Keywords: Continuous double auction, Experiments, Individual evolutionary learning, Marshallian selection.

"Individual Evolutionary Learning in Repeated Beauty Contest Games", 2024, with John Duffy and Valentyn Panchenko, Journal of Economic Behavior & Organization, Volume 218, Pages 550-567. [ Journal Article | SSRN Working paper ]

Keywords: Beauty Contest Game, Learning, Evolutionary Dynamics, Testbed, Agent-based model.

"Dissonance minimization and conversation in social networks," 2023, with Kirill Borissov and Mikhail Pakhnin, Journal of Economic Behavior & Organization, Volume 215, Pages 167-191. [ Journal Article | SSRN Working paper ]

Keywords: DeGroot learning, Social influence, Audience tuning, Dissonance minimization, Conversations.

"An asset pricing model with accuracy-driven evolution of heterogeneous expectations", 2023, with Tomáš Tichý, Fabio Lamantia and Davide Radi, Communications in Nonlinear Science and Numerical Simulation. [ Journal Article ]

Keywords: Heterogeneous beliefs, Asset-pricing model, Prediction accuracy, Nonlinear dynamics

"Learning in two-dimensional beauty contest games: Theory and experimental evidence", 2022, with John Duffy and Valentyn Panchenko, Journal of Economic Theory, Volume 201, 105417. [ Journal Article | Online Appendix | Slides ]

Keywords: Learning, Stability, Multivariate systems, Beauty contest, Complexity, Level-k.

"Asset price volatility and investment horizons: An experimental investigation", 2022, with Aleksei Chernulich and Jan Tuinstra, Journal of Economic Behavior & Organization, Volume 193, Pages 19-48. [ Journal Article | SSRN Working paper | Online Appendix ]

Keywords: Experimental economics, Expectations, Asset pricing, Investment horizons, Behavioral finance.

Working Papers

(Re-)Inventing the traffic light: Designing recommendation devices for play of strategic games

Mikhail Anufriev, John Duffy, Valentyn Panchenko and Benjamin Young

We present the results of a novel experiment investigating individuals' ability to offer incentive-compatible recommendations for strategic games. Subjects designed recommendation devices for five canonical 2x2 games played by Bayesian, expected-utility maximizing robots to achieve Pareto efficiency and fairness. Most subjects succeeded in achieving this objective in Matching Pennies and Battle of the Sexes, but only a minority found the desirable device in Prisoner's Dilemma and the two Chicken games. However, the vast majority of subjects designed an incentive-compatible recommendation device for the Chicken games. Subjects failed to recognize that strategic incentives meant the socially efficient outcome could never be recommended in Prisoner's Dilemma. Our approach requires participants to use a holistic approach to equilibrium reasoning. Our findings suggest that equilibrium reasoning is most challenging for individuals when strategic incentives conflict with cooperative outcomes.

[ Download: SSRN Working Paper | Slides ]

Time pressure reduces financial bubbles: Evidence from a forecasting experiment

Mikhail Anufriev, Frieder Neunhoeffer and Jan Tuinstra

From previous laboratory experiments, we know that price bubbles may emerge in asset markets due to participants' tendency to coordinate on extrapolative expectations. In this paper we investigate whether time pressure, which is relevant for many decisions on financial markets, exacerbates or mitigates these bubbles. With increasing time pressure, we find that price volatility decreases and prices tend to converge faster to their fundamental value. This is due to participants using simpler, adaptive forecasting strategies under high time pressure. In addition, substantially increasing the number of decision periods in our experiment allows us to study whether the bubbles and crashes emerging under low time pressure are persistent. We find that, in the long run, prices typically converge to their fundamental value. This can be explained by participants eventually switching from extrapolative to adaptive forecasting strategies.

[ Download: Working Paper| Slides ]

Leaning against the wind in the New Keynesian model with heterogeneous expectations

Mikhail Anufriev, Fabio Lamantia, Davide Radi and Tomas Tichy

In this paper, we explore the efficiency of the Leaning Against the Wind (LAW) policy within the New Keynesian framework with heterogeneous expectations. To do so, we introduce the financial sector into the benchmark model using the financial accelerator channel. We show that the LAW policy can be counterproductive because it creates an equilibrium that can coexist with the desirable equilibrium. A more stringent LAW policy reduces the stability region of the desirable equilibrium. However, in cases where the desirable equilibrium is unstable, the LAW policy can help reduce the amplitude of economic fluctuations.

[ Download: Working Paper ]

Social Distancing Policies and Intersectoral Spillovers: Australia vs Sweden

Mikhail Anufriev, Andrea Giovannetti and Valentyn Panchenko

Social distancing measures, adopted around the world to contain the spread of the COVID-19 pandemic, affect employment unevenly across sectors with non-trivial aggregate implications. We apply a CES multi-sector model to explore social distancing in economies characterized by sectoral spillovers. We calibrate our model on Australia and Sweden, the two countries that pursued very different social distancing strategies, and measure the impact of the COVID-19 shock. We found, for Australia but not for Sweden, that the up-stream sectors are subject to larger losses in value added than implied by the observed change in employment. This indicates a compounded network effect of the COVID-19 shock.

[ Download: Working Paper ]

A model of network formation for the overnight interbank market

Mikhail Anufriev, Andrea Deghi, Paolo Pin and Valentyn Panchenko

We introduce an endogenous network model of the interbank overnight lending market. Banks are motivated to meet the minimum reserve requirements set by the Central Bank, but their reserves are subject to random shocks. To adjust their expected end-of-the-day reserves, banks enter the interbank market, where borrowers decrease their expected cost of borrowing with the Central Bank, and lenders decrease their deposits with the Central bank in attempt to gain a higher interest rate from the interbank market, but face a counter-party default risk. In this setting, we show that a financial network arises endogenously, exhibiting a unique giant component which is at the same time connected but bipartite in lenders and borrowers. The model reproduces features of trading decisions observed empirically in the Italian e-MID market for overnight interbank deposits. Also, we show that aggregating market realization across time, we are able to reproduce the empirically observed spoke hub structure of interbank lending markets.

[ Download: SSRN Working paper | Working Paper | Slides | Presentation]

Work in Progress

"Local interactions in a market with heterogeneous expectations", with Andrea Giovannetti, Valentyn Panchenko. [ Slides ]

"Gross return illusion and fee aversion in mutual fund choice", with Jan Tuinstra, Valentyn Panchenko, Benjamin Young. [ Slides ]

"Hypocrisy in a simple social interaction model", with Kirill Borissov, Mikhail Pakhnin. [ Slides ]

"Heterogeneous belief pricing model under replicator dynamics", with Tomáš Tichý, Fabio Lamantia, Davide Radi. [ Slides ]

"Bayesian estimation of the heuristic switching model using experimental data", with Cars Hommes, Valentyn Panchenko.

"Market reflexivity in an asset pricing model with endogenous fundamentals". [ Slides ]

"Asset price dynamics with expectation selection".

"Should financial economic literacy be promoted to boost rational decisions for the housing market?", with Hana Dvořáčková, Aleš Melecký, Martina Novotna.

Selected Publications

Learning in Two-Dimensional Beauty Contest Games: Theory and Experimental Evidence

Mikhail Anufriev, John Duffy and Valentyn Panchenko, Journal of Economic Theory, Volume 201, 105417

We extend the beauty contest game to two dimensions: each player chooses two numbers to be as close as possible to certain target values, which are linear functions of the averages of the two number choices. One of the targets depends on the averages of both numbers, making the choices interrelated. We report on an experiment where we vary the eigenvalues of the associated two-dimensional linear system and find that subjects can learn the Pareto-optimal Nash Equilibrium of the system if both eigenvalues are stable and cannot learn it if both eigenvalues are unstable. Interestingly, subjects can also learn it if the system has the saddlepath property – with one stable and one unstable eigenvalue — but only if the one unstable eigenvalue is negative. We show theoretically that our results cannot be explained by homogeneous level-k models where all agents apply the same level k depth of reasoning to their choices, including the naïve learning model. However, our results can be explained by a mixed cognitive-levels model, including the adaptive learning model. We also run a horserace between many models used in the literature with the winner being a simple mixed model with levels 0, 1, and equilibrium reasoning.

Download: Paper (open access) | Slides

Simple forecasting heuristics that make us smart: Evidence from different market experiments

Mikhail Anufriev, Cars Hommes and Tomasz Makarewicz, Journal of the European Economic Association, Volume 17, Issue 5, Pages 1538–1584, 2019

In this paper we address the question of how individuals form expectations and invent, reinforce, and update their forecasting rules in a complex world. We do so by fitting a novel, parsimonious and empirically validated genetic algorithm learning model with explicit heterogeneity in expectations to a set of laboratory experiments. Agents use simple linear first order price forecasting rules, adapting them to the complex evolving market environment with a Genetic Algorithm optimization procedure. The novelties are: (1) a parsimonious experimental foundation of individual forecasting behavior; (2) explanation of individual and aggregate behavior in three different experimental settings, (3) improved one- and 50-period ahead forecasting of experiments, and (4) characterization of the mean, median and empirical distribution of forecasting heuristics. The median of the distribution of GA forecasting heuristics can be used in designing or validating simple Heuristic Switching Models.

Download: Paper , Online Appendix , Slides

Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments

Mikhail Anufriev and Cars Hommes, American Economic Journal: Microeconomics, Vol. 4 (4), pp. 35-64, 2012.

In recent “learning to forecast” experiments (Hommes et al. 2005), three different patterns in aggregate price behavior have been observed: slow monotonic convergence, permanent oscillations, and dampened fluctuations. We show that a simple model of individual learning can explain these different aggregate outcomes within the same experimental setting. The key idea is evolutionary selection among heterogeneous expectation rules, driven by their relative performance. The out-of-sample predictive power of our switching model is higher compared to the rational or other homogeneous expectations benchmarks. Our results show that heterogeneity in expectations is crucial to describe individual forecasting and aggregate price behavior.

Download: PDF , Online Appendix , Model code and Data