Spyros Galanis

Department of Economics · Durham University Business School · spyros.galanis'at'durham.ac.uk

I am a Professor in Economics at the Durham University Business School and Director of the Durham Research in Economic Analysis and Mechanisms (DREAM Research Centre). Previously, I was Associate Professor (Reader) and Head of the Department of Economics of City, University of London. Between 2007-2018, I was first a Lecturer and then an Associate Professor at the Department of Economics of the University of Southampton. I received my PhD from the University of Rochester, my MSc from the University of Warwick and my BSc from the Athens University of Economics and Business, all in Economics. My research interests include decision theory, game theory, experiments and finance.

My main research focuses on the role that uncertainty, information and bounded perception have on single- and multi-agent decision making. I examine under which conditions speculative trade occurs, in three different settings: when traders have a bounded perception of their uncertainty due to their unawareness, when they are dynamically and time inconsistent, and when they are not financially sophisticated enough to formulate complex trading strategies. I also study when information is valuable and whether markets (including the prediction markets) aggregate and reveal information through their price mechanism.

ESRC Grant on Prediction Markets

I am PI for the ESRC standard grant, titled The Forecasting Efficiency Of Prediction Markets, which runs between 2021-2024. The CI is Christos A. Ioannou and the postdoctoral Research Fellow is Sergei Mikhalishchev. I am also CI in the AAPG2021 Research Grant "Bounded Rationality in Prediction Markets".

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Conferences and Workshops

I co-organize the Virtual Seminars in Economic Theory (VSET) and the Makris Symposium in Economic Theory (MSET), together with Francesco Giovannoni (Bristol), Angel Hernando-Veciana (Carlos III), Max Kwiek (Southampton) and Julia Wirtz (Bristol). DREAM organises the Durham Economic Theory Conference and the Durham York workshop.

CMA Durham partnership

The Competition and Markets Authority (CMA) has established a partnership with Durham University. The main partners are the CMA Microeconomics Unit, the Department of Economics and DREAM. You can find more about our joint actions and events by clicking below.

CMA Durham Partnership


Crypto and Blockchain

I have organised panel discussions and short courses on the economics of blockchain and cryptocurrencies, such as Investing in Crypto Assets and Decentralised Finance, that took place on March 31 2021. You can find more information here. I advise Aaro Capital and I regularly write reports, such as An Introduction to Distributed Ledger Technology and blog posts on various topics, such as stablecoins, DLT and the hold-up problem, digital securities and on-chain governance.


After teaching International Trade Theory for more than 10 years, I wrote a book, "Six Easy Models of International Trade Theory". It provides a short and concise introduction to the main theories of international trade, addressing the following questions. Are there gains for a country that engages in free trade? Which goods does it export and import? What happens to its income distribution? What are the implications for consumers and producers when it restricts trade, for example by imposing import tariffs?


Part of my first sabbatical was (regrettably) devoted in learning to program iOS apps, such as Group Debts, about recording and sharing expenses among groups, and Ticket Holder, about storing and organizing ticket codes. Since 2011, they have been downloaded around 43000 times.


Information Aggregation Under Ambiguity: Theory and Experimental Evidence

Review of Economic Studies, 2024.

We study information aggregation in a dynamic trading model with partially informed and ambiguity averse traders. We show theoretically that separable securities, introduced by Ostrovsky (2012) in the context of Subjective Expected Utility, no longer aggregate information if some traders have imprecise beliefs and are ambiguity averse. Moreover, these securities are prone to manipulation, as the degree of information aggregation can be influenced by the initial price, set by the uninformed market maker. These observations are also confirmed in our experiment, using prediction markets. We define a new class of strongly separable securities which are robust to the above considerations, and show that they characterize information aggregation in both strategic and non-strategic environments. We derive several theoretical predictions, which we are able to confirm in the lab.

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Group Testing and Social Distancing

National Institute Economic Review, 2021.

An often overlooked strategy for fighting the COVID-19 pandemic is group testing. Its main advantage is that it can scale, enabling the regular testing of the whole population. We argue that another advantage is that it can induce social distancing. Using a simple model, we show that if a group tests positive and its members are in close social proximity, then they will rationally choose not to meet. The driving force is the uncertainty about who has the virus and the fact that the group cares about its collective welfare. We therefore propose identifying socially connected groups, such as colleagues, friends and neighbours, and testing them regularly.

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Dynamic Consistency, Valuable Information and Subjective Beliefs

Economic Theory, 2021

Ambiguity sensitive preferences must fail either Consequentialism or Dynamic Consistency (DC), two properties that are compatible with subjective expected utility and Bayesian updating, while forming the basis of backward induction and dynamic programming. We examine the connection between these properties in a general environment of convex preferences over monetary acts and find that, far from being incompatible, they are connected in an economically meaningful way. In single-agent decision problems, positive value of information characterises one direction of DC. We propose a weakening of DC and show that one direction is equivalent to weakly valuable information, whereas the other characterises the Bayesian updating of the subjective beliefs which are revealed by trading behavior.

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Updating Awareness and Information Aggregation

B.E. Journal of Theoretical Economics, 2021.

The ability of markets to aggregate information through prices is examined in a dynamic environment with unawareness. We find that if all traders are able to minimally update their awareness when they observe a price that is counterfactual to their private information, they will eventually reach an agreement, thus generalising the result of Geanakoplos and Polemarchakis [1982]. Moreover, if the traded security is separable, then agreement is on the correct price and there is information aggregation, thus generalizing the result of Ostrovsky [2012] for non-strategic traders. We find that a trader increases her awareness if and only if she is able to become aware of something that other traders are already aware of and, under a mild condition, never becomes aware of anything more. In other words, agreement is more the result of understanding each other, rather than being unboundedly sophisticated.

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Speculative Trade and the Value of Public Information

Journal of Public Economic Theory, 2021

In environments with expected utility, it has long been established that speculative trade cannot occur (Milgrom and Stokey [1982]), and that the value of public information is negative in economies with risk-sharing and no aggregate uncertainty (Hirshleifer [1971], Schlee [2001]). We show that these results are still true even if we relax expected utility, so that either Dynamic Consistency (DC) or Consequentialism is violated. We characterise no speculative trade in terms of a weakening of DC and find that Consequentialism is not required. Moreover, we show that a weakening of both DC and Consequentialism is sufficient for the value of public information to be negative. We therefore generalise these important results for convex preferences which contain several classes of ambiguity averse preferences.

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Financial Complexity and Trade

Games and Economic Behavior, 2018

What are the implications on trading activity if investors are not sophisticated enough to understand and evaluate trades that have a complex payoff structure? Can frictions generated by this type of financial complexity be so severe that they lead to a complete market freeze, like that of the recent financial crisis? Starting from an allocation that is not Pareto optimal, we find that whether complexity impedes trade depends on how investors perceive risk and uncertainty. For smooth convex preferences, such as subjective expected utility, complexity cannot halt trade, even in the extreme case where each investor is so unsophisticated that he can only trade up to one Arrow-Debreu security, without being able to combine two or more in order to construct a complex trade. However, for non-smooth preferences, which allow for kinked indifference curves, such as maxmin expected utility, complexity can completely shut down trade.

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Speculation Under Unawareness

Games and Economic Behavior, 2018

“No trade” theorems establish that, in various trading environments, investors who share a common prior will not engage in speculation, as long as expected utility, Bayesian updating and full awareness are imposed. We relax the last assumption by allowing for asymmetric unawareness and examine under which conditions speculative behavior emerges. We find that if common knowledge is assumed (as in the settings of Aumann [1976] and Milgrom and Stokey [1982]), unawareness cannot generate speculation. This is not true, however, in settings where no common knowledge is assumed, such as speculation in equilibrium (Geanakoplos [1989]) and betting that is always beneficial (Morris [1994]), unless stronger conditions on awareness are imposed.

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The Value of Information in Risk-Sharing Environments with Unawareness

Games and Economic Behavior, 2016

The value of information is examined in a risk-sharing environment with unawareness and complete markets. Information and awareness are symmetric among agents, who have a clear understanding of their actions and deterministic payoffs. We show with examples that public information can make some agents strictly better off at the expense of others, contrasting the standard results of Hirshleifer [1971] and Schlee [2001] that the value of public information is negative for all when risk averse agents are fully insured. We identify the source of this problem to be that, as awareness varies across states, it creates an awareness signal that the agents misunderstand and treat asymmetrically. As a result, risk-sharing opportunities that are available when this signal is not used, vanish when it is used. We identify a property, Conditional Independence, which we show is sufficient for the value of public information to be negative for all.

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The Value of Information Under Unawareness

Journal of Economic Theory, 2015

The value of information is examined in a single-agent environment with unawareness. Although the agent has a correct prior about events he is aware of and has a clear understanding of his available actions and payoffs, his unawareness may lead him to commit information processing errors and to behave suboptimally. As a result, the value of information can be negative, contrasting what is true in the standard model with partitional information and no unawareness. We show that the source of the agent’s suboptimal behavior is that he misunderstands the information revealed by his varying awareness, treating it asymmetrically.

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Admissibility and Event-Rationality

Games and Economic Behavior, 2013

We develop an approach to providing epistemic conditions for admissible behavior in games. Instead of using lexicographic beliefs to capture infinitely less likely conjectures, we postulate that players use tie-breaking sets to help decide among strategies that are outcome-equivalent given their conjectures. A player is event-rational if she best responds to a conjecture and uses a list of subsets of the other players’ strategies to break ties among outcome-equivalent strategies. Using type spaces to capture interactive beliefs, we show that event-rationality and common belief of event-rationality (RCBER) imply S∞W, the set of admissible strategies that survive iterated elimination of dominated strategies. By strengthening standard belief to validated belief, we show that event-rationality and common validated belief of event-rationality (RCvBER) imply IA, the iterated admissible strategies. We show that in complete, continuous and compact type structures, RCBER and RCvBER are nonempty, hence providing epistemic criteria for S∞W and IA.

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Unawareness of Theorems

Economic Theory, 2013

This paper provides a set-theoretic model of knowledge and unawareness. A new property called Awareness Leads to Knowledge shows that unawareness of theorems not only constrains an agent’s knowledge, but also can impair his reasoning about what other agents know. For example, in contrast to Li (J Econ Theory 144:977– 993, 2009), Heifetz et al. (J Econ Theory 130:78–94, 2006) and the standard model of knowledge, it is possible that two agents disagree on whether another agent knows a particular event. The model follows Aumann (Ann Stat 4:1236–1239, 1976) in defining common knowledge and characterizing it in terms of a self-evident event, but departs in showing that no-trade theorems do not hold.

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Syntactic Foundations for Unawareness of Theorems

Theory and Decision, 2011

We provide a syntactic model of unawareness. By introducing multiple knowledge modalities, one for each sub-language, we specifically model agents whose only mistake in reasoning (other than their unawareness) is to underestimate the knowledge of more aware agents. We show that the model is a complete and sound axiomatization of the set-theoretic model of Galanis (University of Southampton Discussion paper 709, 2007) and compare it with other unawareness models in the literature.

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Working Papers

Information Aggregation with Costly Information Acquisition

Extended abstract to appear in the 25th ACM Conference on Economics and Computation (ACM EC 2024)
June 2024

We study information aggregation in a dynamic trading model with partially informed traders. Ostrovsky [2012] showed that ‘separable’ securities aggregate information in all equilibria, however, separability is not robust to small changes in the traders’ private information. To remedy this problem, we enhance the model by allowing traders to acquire signals with cost κ, in every period. We show that ‘κ separable securities’ aggregate information and, as the cost decreases, nearly all securities become κ separable, irrespective of the traders’ initial private information. Moreover, the switch to κ separability happens not gradually but discontinuously, hence even a small decrease in costs can result in a security aggregating information. Finally, even with myopic traders, cheaper information may accelerate or decelerate information aggregation for all but Arrow-Debreu securities.

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No Trade in a Blockchain

June 2024

We show that there cannot be common knowledge trade in a truly decentralised environment, such as in a blockchain. A trade is an agreement to buy and sell a security that pays according to some state of nature; it is settled when the security’s value is verified by an oracle, an intermediary who knows the state of nature. However, since the identity of traders in a blockchain is hidden, an oracle can impersonate a trader, by participating in a trade only when he knows that the outcome will be favourable. If other traders know that this is possible, they might be unwilling to participate in any trade that is offered. In other words, anonymity of traders is incompatible with verifiability of trades. We find that the requirement on verifiability is relatively mild. In particular, it is enough that, among all values of the security that it is common knowledge that some trader thinks are possible, there exists an oracle that can verify either the maximum or the minimum.

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Tax Evasion and Laffer Curves

March 2018

We provide a theory of the Laffer curve (LC) using a simple model of tax evasion with strategic complementarities, which arise from the assumption that the cost of being caught while evading is decreasing as more people evade their taxes. We find that with either sufficiently low or sufficiently high tax rates, there is a unique equilibrium, therefore a unique level of tax evasion and tax revenues. If taxes are in between, there can be multiple equilibria which imply two LCs, one with high and one with low tax evasion. The policy implication of this result is that if taxes are sufficiently high, it is possible to increase tax revenues by reducing taxes, even though locally the LC was upward sloping. Using data on VAT evasion, we find empirical evidence that supports our assumption of strategic complementarities and the presence of multiple LCs. Finally, we provide a numerical example by calibrating the LCs for Greece and show that an increase in the VAT rate would reduce tax revenues.

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Positive Common Priors and Speculative Trade

March 2016

The speculative trade theorem specifies that a positive common prior, which assigns positive probability to all elements of the join of the agents’ partitions, implies that there can be no mutually beneficial trade that is common knowledge at some state. We show that the reverse is also true for full support type structures, where at each state a type assigns positive probability to the element of the join that contains this state. By providing this behavioral characterization of positive common priors, we complement the existing result of the literature, that for arbitrary type structures there is a (not necessarily positive) common prior if and only if there is no mutually beneficial trade that is common knowledge at all states.

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Concern for Relative Standing and Deception

IZA Discussion Paper No.8442, August 2014

We report results from a sender-receiver deception game, which tests whether an individual’s decision to deceive is influenced by a concern for relative standing in a reference group. The sender ranks six possible outcomes, each specifying a payoff for him and the receiver. A message is then transmitted to the receiver, announcing that the sender has ranked the outcomes according to the receiver’s payoff, from highest to lowest. The receiver, without knowing that there is conflict of interest, chooses an action that determines the payoff of both players. The sender has an incentive to deceive the receiver, in order to obtain a higher payoff. A sender is positively biased if he thinks that he is higher in the deception distribution than in reality. We show theoretically that a positively biased sender will increase cheating when presented with information about the deception of his peers. The experimental data confirm this. We conclude that concern for relative standing does play a role in the decision to deceive.

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The Forecasting Efficiency of Prediction Markets

The ESRC grant started in December 2021 and will last for three years. The CI is Christos A. Ioannou and the postdoctoral Research Fellow is Sergei Mikhalishchev.

Learn more about the project


We are always looking for new companies to help them run prediction markets. Email me if you are interested to know more!

What we want to do

Prediction markets leverage the wisdom of the crowd, by aggregating information that is dispersed among individuals. The mechanism is intuitive. Traders buy and sell securities, which pay £1 only if a specific event occurs (e.g. Trump wins the next US presidential election) and £0 otherwise. On the one hand, if the security price is low and some traders have private information that the event is highly likely, they will buy the security; consequently, its price will go up. On the other hand, if the security price is high and some traders have private information that the event is highly unlikely, they will sell the security, hence its price will go down. Such price movements could reveal to a trader information that others might have, prompting her to update her beliefs and either buy or sell the security, thus, further revealing to other traders some of her own private information. The final price, normalized to be between 0 and 1, is interpreted as the public's probability of the event occurring. Information gets aggregated if the final price (or probability) is close to the true outcome (0 or 1).

Our proposed research aims to understand under which conditions the prediction markets (and financial markets more generally) are an effective tool in aggregating information. This is important because making predictions about future events is an inescapable part of decision making. Revenues for the forecasting industry are estimated at around $300 billion (Atanasov et al. (2017)), hence, even slightly better predictions are economically beneficial for individuals, governments, firms and organizations.

Prediction markets have been analysed both theoretically and experimentally. Our proposed research aims to improve on both these dimensions and add a third one, by studying prediction markets in the field. In particular, we want to collaborate with the industry in order to deploy prediction markets in a field setting with firms and test their effectiveness. This has not been done before and it is interesting because it relates to predictions about real-world events, with participants that are experienced in making predictions about their firm and their industry.

Although the ability of prediction markets to forecast events has been examined theoretically in the past, this has always been under the assumption of economies populated with fully rational agents, who, in addition, have precise beliefs about all conceivable future events. In other words, they are aware of all relevant contingencies, they can implement any complicated trading strategy and they can assign a precise probabilistic estimate on every event. For example, they are extremely confident and assign probability 40% on the event that Trump will win the next election, instead of being unsure and assigning a range of 20%-40%. As these are non-realistic and highly stylized assumptions, we will relax them by constructing alternative theoretical models of dynamic trading in prediction markets, which accommodate boundedly rational agents, who either have precise or imprecise beliefs about future events. These theoretical models will enable us to study in more detail the design of prediction markets and understand under which conditions they are effective in information aggregation. For example, in our working paper we show theoretically and experimentally that the most common design for prediction markets, which is used in practice as well, fails to aggregate information when agents are unboundedly rational but have imprecise beliefs. We want to extend this examination, both theoretically and experimentally, using models with boundedly rational agents with either precise or imprecise beliefs. Together with our examination in the field, we want to obtain a holistic understanding of when prediction markets are effective in aggregating information and what goes wrong when they are not.


  • Financial Economics, 2020
  • Asset Pricing, 2020
  • Introduction to Microeconomics 2019 - present
  • Advanced Microeconomics 2019 - present
  • International Trade Theory and Policy, Spring 2008-2018
  • Topics in Economic Theory, Spring 2009-2018
  • PhD Micro, Spring 2012-2015
  • Microeconomic Theory II, Fall 2007, Fall 2011
  • Intermediate Microeconomics, Summer 2006
  • International Trade, Summer 2005