Igor Makarov

A pervasive feature of financial intermediation is the use of third-party deal-by-deal capital in addition to balance sheet capital to finance investment activity. This paper studies how third-party capital and decentralized fundraising jointly shape competition, screening, and welfare in intermediated credit markets. We show that third-party capital serves a novel economic function: it allows informed intermediaries to separate screening decisions from surplus sharing, thereby intensifying competition and reducing the cost of capital to firms. Yet it also amplifies a dynamic adverse selection externality, resulting in excessively lax screening and overinvestment. Consequently, although entrepreneurs benefit from intermediary third-party leverage, restricting third-party financing can raise social welfare.

We study the impact of peer effects on the adoption of new retail financial products such as cryptocurrencies and online gambling. Using transaction level data from PayPal and Venmo, we show a novel crowd-out effect within social networks — peers with divergent interests compete for the limited attention or time of their friends. Using exogenous shocks to the exposure of peers to cryptocurrencies and online gambling, we show that peers with interests in cryptocurrencies (gambling) amplify the adoption of crypto (gambling) among their peers, at the expense of the other activity. Therefore, “pre-existing” peer interests in one activity impede (and partially crowd out) the adoption of the other. We hypothesize that this is due to limited attention or resources on the part of peers.

This paper examines the economics of Cardano staking markets, which provide a laboratory of intermediary competition in a fully digital environment. Detailed blockchain data allows us to observe not only flows between staking pools but also the switching behavior of investors. Our central finding is that investor inattention in this market is just as widespread as it is among bank depositors and fund investors, yet it sustains far smaller rents. We show that a relatively small subset of attentive investors who move across pools for better returns exerts a strong positive externality for the entire population of delegators and disciplines fees across the market.

The paper develops a model of bubbles that can be taken to the data and explain the behavior of asset prices and their statistics. We depart from the rational expectations framework and assume that investors are only boundedly rational. They observe the price process, but do not fully understand how its volatility and expected returns are determined in equilibrium. Investors learn about the market by looking at past prices. When they observe unexpectedly high returns, they infer that the asset must currently have a high Sharpe ratio, and therefore, allocate a higher share of their wealth to the asset, further increasing the asset price. The interaction of this feedback effect with investors’ wealth effect determines the price dynamics and evolution of investors’ beliefs in the model. We fit the model to cryptocurrency markets and show that it can successfully explain many empirical facts in these markets.

This paper develops a model in which arbitrageurs are collectively unconstrained, but may still prefer to incur individual limits to arbitrage rather than make full use of their combined resources. These deliberate limits arise because the communication of an arbitrage position reveals the underlying idea, which creates future competition in the absence of relevant property rights. We allow arbitrage opportunities to vary along two dimensions: the ease with which they can be identified and the speed at which they mature. We find that deliberate limits to arbitrage arise for opportunities in the mid-range of the maturity dimension. This range widens when the opportunities are easier to find. Our results thus offer a set of theoretical predictions about the arbitrage trades that are likely to exist in the market.

Using the restrictions implied by the heteroskedasticity of stock returns, we identify four factors in the U.S. industry returns. The first correlates highly with the market portfolio; the second is a portfolio of stocks that produce investment goods minus stocks that produce consumption goods; the third differentiates between cyclical and noncyclical stocks. The fourth, a portfolio of industries that produce input goods minus the rest of the market, is a robust predictor of excess returns on the market portfolio and bond returns. The extracted factors are shown to contain significant information about future macroeconomic and financial variables.

This paper presents a comprehensive analysis of the Bitcoin ecosystem using blockchain data from 2009–2025, examining transaction patterns, mining concentration, and ownership distribution. Our findings show that the Bitcoin network has become increasingly dominated by large, concentrated players, contradicting its original decentralized vision. The top 50 miners control nearly 50% of network power, while the top 0.01% of individual investors hold approximately 25% of circulating supply. Exchanges and trading-related entities account for 70% of all blockchain activity, suggesting that Bitcoin functions primarily as a traded financial asset rather than a medium of exchange.

We examine the dramatic collapse of the Terra blockchain in May 2022. Using granular blockchain data, we analyze the mechanisms underlying the run and draw parallels to the traditional financial system. We show that the early success of Terra’s algorithmic stablecoin, UST, was fueled by highly subsidized deposit rates, which attracted many investors but created a fragile system prone to runs. The blockchain allowed investors to observe Terra’s worsening fundamentals and monitor each other’s exits. The presence of large investors, whose actions were observable and could impact prices, alleviated the need for coordination typical in canonical models of runs. Larger and sophisticated investors reacted faster to adverse signals and served as catalysts for the run. These findings challenge the idea that blockchain transparency levels the playing field and highlight how greater observability and concentration can amplify financial fragility. Our results contribute to the understanding of the limits of private money and the dynamics of runs in fully digital financial systems.

Entrepreneurs typically seek financing in decentralized markets, where they approach investors sequentially. We develop a model of sequential capital markets with privately informed investors. The sequential market creates a dynamic adverse selection externality that leads to overinvestment and excessive rents to intermediaries, even as the number of competing investors becomes arbitrarily large. The resulting rents lead to excessive entry of investors and insufficient entry of entrepreneurs. Moving to a centralized market structure or reducing transparency restores competitiveness but may harm efficiency. The model also explains how even a small skill advantage for an investor can lead to preferential deal flow and outsized returns.

Trading in cryptocurrencies grew rapidly over the last decade, dominated by retail investors. Using data from eToro, we show that retail traders have different models of the underlying price dynamics of cryptocurrencies relative to other assets: they are contrarian in stocks and gold, yet these same traders follow a buy-and-hold strategy in cryptocurrencies. The differences are not explained by individual characteristics, investor composition, inattention, differences in fees, nor preference for lottery-like stocks. We conjecture that retail investors have a model where cryptocurrency price changes also affect the likelihood of future widespread adoption, which pushes prices further in the same direction.

A central role for financial markets is to assess whether new projects are worth pursuing or not. We extend standard auction theory to capture this role by studying new venture financing. Paradoxically, when the information generated in the auction is valuable for making real investment decisions, the informational efficiency of the market is destroyed. To add to the paradox, as the number of market participants with useful information increases a growing share of them fall into an “informational black hole,” making markets even less efficient. Contrary to the predictions of standard auction theory, social surplus and seller revenues can be decreasing in the number of bidders, the linkage principle of Milgrom and Weber (1982) may not hold, and collusion among investors may be beneficial for the seller.

The paper provides an overview of cryptocurrencies and decentralized finance. The discussion lays out potential benefits and challenges of the new system and presents a comparison to the traditional system of financial intermediation. Our analysis highlights that while the DeFi architecture might have the potential to reduce transaction costs, similar to the traditional financial system, there are several layers where rents can accumulate due to endogenous constraints to competition. We show that the permissionless and pseudonymous design of DeFi generates challenges for enforcing tax compliance, anti-money laundering laws, and preventing financial malfeasance. We highlight ways to regulate the DeFi system which would preserve a majority of the benefits of the underlying blockchain architecture but support accountability and regulatory compliance.

Cryptocurrency markets exhibit periods of large, recurrent arbitrage opportunities across exchanges. These price deviations are much larger across than within countries, and smaller between cryptocurrencies, highlighting the importance of capital controls for the movement of arbitrage capital. Price deviations across countries co-move and open up in times of large bitcoin appreciation. Countries with higher bitcoin premia over the US bitcoin price see widening arbitrage deviations when bitcoin appreciates. Finally, we decompose signed volume on each exchange into a common and an idiosyncratic component. The common component explains 80% of bitcoin returns. The idiosyncratic components help explain arbitrage spreads between exchanges.

We study how price discovery happens in the Bitcoin market. We build on our earlier work documenting that cryptocurrency markets around the world are partially segmented and experience extended periods where prices deviate substantially from the law of one price. These price deviations seem to persist due to slow-moving capital and capital controls in many countries that hinder the efficient flow of arbitrage capital across exchanges. We find that the marginal investor outside the US and Europe is willing to pay more for Bitcoin in response to booms in crypto prices.

This paper develops a model of active asset management in which fund managers may forego alpha-generating strategies, preferring instead to make negative-alpha trades that enable them temporarily to manipulate investors’ perceptions of their skills. We show that such trades are optimally generated by taking on hidden-tail risk, and that they are more likely to occur when fund managers are impatient, and when their trading skills are scalable and generate a high profit per unit of risk. We propose long-term contracts that deter this behavior by dynamically adjusting the dates on which the manager is compensated in response to her cumulative performance.

This paper develops an equilibrium model of a subprime mortgage market. Our goal is to offer a benchmark with which the recent subprime boom and bust can be compared. The model is tractable and delivers plausible orders of magnitude for borrowing capacities, as well as default and trading intensities. We offer simple explanations for several phenomena in the subprime market, such as the prevalence of teaser rates and the clustering of defaults. In our model, both nondiversifiable and diversifiable income risks reduce debt capacities. Thus, debt capacities need not be higher when a larger fraction of income risk is diversifiable.

We analyze auctions for the settlement of credit default swaps (CDS) theoretically and evaluate them empirically. The requirement to settle in cash with an option to settle physically leads to an unusual two-stage process. In the first stage, participants affect the amount of the bonds to be auctioned off in the second stage. Participants in the second stage may hold positions in derivatives on the assets being auctioned. We show that the final auction price might be either above or below the fair bond price because of strategic bidding on the part of participants holding CDS. Empirically, we observe both types of outcomes, with undervaluation occurring in most cases. We find that auctions undervalue bonds by an average of 6% on the auction day. Undervaluation is related positively to the amount of bonds exchanged in the second stage of the auction, as predicted by the theory. We suggest modifications of the settlement procedure to minimize the underpricing.

We study the properties of rational expectation equilibria (REE) in dynamic asset pricing models with heterogeneously informed agents. We show that under mild conditions the state space of such models in REE can be infinite dimensional. This result indicates that the domain of analytically tractable dynamic models with asymmetric information is severely restricted. We also demonstrate that even though the serial correlation of returns is predominantly determined by the dynamics of stochastic equity supply, under certain circumstances asymmetric information can generate positive autocorrelation of returns.

Our objective in this article is to study analytically the effect of borrowing constraints on asset returns. We explicitly characterize the equilibrium for an exchange economy with two agents who differ in their risk aversion and are prohibited from borrowing. In a representative-agent economy with CRRA preferences, the Sharpe ratio of equity returns and the riskfree rate are linked by the risk aversion parameter. We show that allowing for preference heterogeneity and imposing borrowing constraints breaks this link. We find that an economy with borrowing constraints exhibits simultaneously a relatively high Sharpe ratio of stock returns and a relatively low riskfree interest rate, compared to both representative-agent and unconstrained heterogeneous-agent economies.

The returns to hedge funds and other alternative investments are often highly serially correlated, in sharp contrast to the returns of more traditional investment vehicles such as long-only equity portfolios and mutual funds. In this paper, we explore several sources of such serial correlation and show that the most likely explanation is illiquidity exposure, i.e., investments in securities that are not actively traded and for which market prices are not always readily available. For portfolios of illiquid securities, reported returns will tend to be smoother than true economic returns, which will understate volatility and increase risk-adjusted performance measures such as the Sharpe ratio. We propose an econometric model of illiquidity exposure and develop estimators for the smoothing profile as well as a smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds drawn from the TASS database, we show that our estimated smoothing coefficients vary considerably across hedge-fund style categories and may be a useful proxy for quantifying illiquidity exposure.

In this paper we study, both theoretically and empirically, the relationship between barter and the indebtedness of Russian firms. We build a model in which a firm uses barter to protect its working capital against outside creditors even when barter involves high transaction costs. The main innovation of our work is to allow renegotiation between the firm and its creditors. If the creditors are rational, they often agree to postpone debt payments in order to avoid destroying the firm’s working capital. It turns out, however, that even if the firm cannot ensure it will not divert cash ex post, the outcome of renegotiation still provides ex ante incentives to use barter. We show that the greater the debt overhang, the more likely the use of barter, and although the possibility of debt restructuring reduces barter, it does not eliminate it altogether. We also discuss the role of the government bond market and weak bankruptcy legislation. The firm-level evidence is consistent with the model’s predictions.