Essays on amplification mechanisms in financial markets

In Chapter 1, I explore how speculators can destabilize financial markets by amplifying negative shocks in periods of market turmoil, and confirm the main predictions of the theoretical analysis using data on money market funds (MMFs). I propose a dynamic trading model with two types of investors - long-term and speculative - who interact in a market with search frictions. During periods of turmoil created by an uncertainty shock, speculators react to declining asset prices by liquidating their holdings in hopes of buying them back later at a gain, despite the asset's cash flows remaining the same throughout. Interestingly, I show that a reduction in trading frictions leads to more severe fluctuations in asset prices. At the root of this result are the strategic complementarities between speculators expected to follow similar strategies in the future. Using a novel dataset on MMFs' portfolio holdings during the European debt crisis, I gauge the strength of funds' strategic interactions as the number of funding relationships each issuer has with MMFs. I show that funds are more likely to liquidate the securities of issuers that have fewer funding relationships with other funds, obliging them to borrow at shorter maturity and higher interest rates. In Chapter 2, co-authored with Marco Pagano, I study a model where some investors ("hedgers") are bad at information processing, while others ("speculators") have superior information-processing ability and trade purely to exploit it. The disclosure of financial information induces a trade externality: if speculators refrain from trading, hedgers do the same, depressing the asset price. Market transparency reinforces this mechanism, by making speculators' trades more visible to hedgers. As a consequence, asset sellers will oppose both the disclosure of fundamentals and trading transparency. This is socially inefficient if a large fraction of market participants are speculators and hedgers have low processing costs. But in these circumstances, forbidding hedgers' access to the market may dominate mandatory disclosure. In Chapter 3, I show that reputation concerns are important sources of discipline for institutional investors, but their effectiveness varies along the business cycle. I propose a dynamic model of reputation formation in which investors learn about fund managers' skill upon observing past returns. Managers can generate active returns at a disutility and determine the fund's exposure to tail risk. The model delivers rich dynamics for managers' behavior. Good reputation managers exploit their status by extracting higher rents from investors, while intermediate reputation managers tend to improve their returns to attract more funds. Finally, for bad performers there exists a reputation trap: their perceived low quality prevents them from attracting investors' capital and then also from improving their track record. Furthermore, when the economy is subject to aggregate shocks, fund managers tend to exacerbate fluctuations by exposing the fund to tail risk to increase short-term returns. The model provides a framework to analyze the investment strategies adopted by mutual funds and hedge funds during the recent financial crisis.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Economics.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Di Maggio, Marco, 1985-

Advisor dc:contributor.advisor

• Daron Acemoglu, Abhijit Banerjee and Stephen A. Ross.

• Economics.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/81040

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/81040