Heterogeneity and clustering of defaults

This paper provides a theoretical model which highlights the role of heterogeneity of information in the emergence of temporal aggregation (clustering) of defaults in a leveraged economy. We show that the degree of heterogeneity plays a critical role in the persistence of the correlation between defaults in time. Specifically, a high degree of heterogeneity leads to an autocorrelation of the time sequence of defaults characterised by a hyperbolic decay rate, such that the autocorrelation function is not summable (infinite memory) and defaults are clustered. Conversely, if the degree of heterogeneity is reduced the autocorrelation function decays exponentially fast, and thus, correlation between defaults is only transient (short memory). Our model is also able to reproduce stylized facts, such as clustered volatility and non-Normal returns. Our findings suggest that future regulations might be directed at improving publicly available information, reducing the relative heterogeneity

Hedging against risk in a heterogeneous leveraged market

This paper provides a theoretical model which highlights the role of heterogeneity of information in the emergence of temporal aggregation (clustering) of defaults in a leveraged economy. We show that the degree of heterogeneity plays a critical role in the persistence of the correlation between defaults in time. Specifically, a high degree of heterogeneity leads to an autocorrelation of the time sequence of defaults characterised by a hyperbolic decay rate, such that the autocorrelation function is not summable (infinite memory) and defaults are clustered. Conversely, if the degree of heterogeneity is reduced the autocorrelation function decays exponentially fast, and thus, correlation between defaults is only transient (short memory). Our model is also able to reproduce stylized facts, such as clustered volatility and non-Normal returns. Our findings suggest that future regulations might be directed at improving publicly available information, reducing the relative heterogeneity

Essays in economics of information and optimal contracting

In the first chapter, I explore the problem of optimal contracting under delegation of information acquisition. I study a model where equity-holders of a fund delegate their portfolio allocation to a fund manager in an environment where: i) the expected return of the implemented portfolio depends on the ex-ante unknown future price of an asset, ii) the manager can acquire costly information about the future price, and iii) information acquisition is unobservable and unverifiable. I characterize the optimal contract which incentivizes the manager to obtain information and take the profit-maximizing position based on the available information. I show that the optimal contract implies a premium for positions against the publicly available information: a long position when an asset is considered overvalued, and vice versa. This premium leads the manager to adopt contrarian positions more often than the first best. I argue that this ‘bias against the flow’ is supported by empirical evidence. In the second chapter, I explore the impact of Credit Rating Agencies (CRAs) on capital markets. I argue that the source for potential inefficiencies arising from CRAs might be more pathological than the literature recognizes; even in the absence of conflicts of interest or other distortions resulting from players’ behavior, a CRA might have an adverse effect on critical economics variables. I develop a model of investment financing which, similarly to capital markets, is characterized by information asymmetry and lack of commitment. In the benchmark setting, the CRA is capable of perfect monitoring and reveals its private information truthfully and without cost. I explore the impact of such an “ideal” CRA on the interest rate and the probabilities of project financing and default. I find that introducing such a CRA may lead to under-financing of projects with a positive net present value (NPV) that would otherwise be financed; a higher expected interest rate; and a higher expected probability of default. These findings relate to the feedback effect, which is inherent in capital markets, and its asymmetric impact on firms of different quality. I evaluate the policy of restricting CRAs to provide hard evidence with their ratings, and suggest that it might have an unfavorable effect on the probabilities of project financing and default. In the third chapter, I explore the problem of security design with endogenous implementation choice. I study an economy where an entrepreneur raises capital to finance an investment project. My focus is on an environment where the entrepreneur shares the same characteristics as the representative entrepreneur in crowdfunding platforms: i) there is no record regarding her ability, ii) she might be associated with a negative-NPV project, and iii) she has limited liability. Asymmetric information regarding the entrepreneur’s ability between the entrepreneur and potential investors gives rise to a signaling game when the former issues securities to raise capital. I characterize the optimal security, and show that it is always optimal to reward the non-implementation of the project after financing takes place. I show that compared to a case where the entrepreneur is obliged to implement the project after raising capital, endogenizing the project implementation choice: i) prevents market breakdown, ii) leads to a more efficient allocation of resources, and iii) strengthens the incentive of an entrepreneur to invest in her productivity

Heterogeneity and Clustering of Defaults

This paper studies an economy where privately informed hedge funds (HFs) trade a risky asset in order to exploit potential mispricings. HFs are allowed to have access to credit, by using their risky assets as collateral. We analyse the role of the degree of heterogeneity among HFs’ demand for the risky asset in the emergence of clustering of defaults. We find that fire-sales caused by margin calls is a necessary, yet not a sufficient condition for defaults to be clustered. We show that when the degree of heterogeneity is sufficiently high, poorly performing HFs are able to obtain a higher than usual market share at the end of the leverage cycle, which leads to an improvement of their performance. Consequently, their survival time is prolonged, increasing the probability of them remaining in operation until the downturn of the next leverage cycle. This leads to the increase of the probability of poorly and high-performing hedge funds to default in sync at a later time, and thus the probability of collective defaults

Hedging against Risk in a Heterogeneous Leveraged Market

This paper focuses on the use of interest rates as a tool for hedging against the default risk of heterogeneous hedge funds (HFs) in a leveraged market. We assume that the banks study the HFs survival statistics in order to compute default risk and hence the correct interest rate. The emergent non-trivial (heavy-tailed) statistics observed on the aggregate level, prevents the accurate estimation of risk in a leveraged market with heterogeneous agents. Moreover, we show that heterogeneity leads to the clustering of default events and constitutes thus a source of systemic risk