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Essays in financial economics

Nicolai, Francesco (2021) Essays in financial economics. PhD thesis, London School of Economics and Political Science.

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Identification Number: 10.21953/lse.00004302


This dissertation consists of three chapters. In the first, I study the impact of institutional investors on asset prices, by focusing on Collateralized Loan Obligations (CLOs). I document that, in order to satisfy constraints based on the par value of their assets, CLOs become forced sellers of leveraged loans. Loans sold for non fundamental reasons trade at depressed prices for up to nine months after the shock. The effect cannot be explained by selection on ex-ante or ex-post loan characteristics. A large fraction of the dislocation in secondary markets is transmitted to the market of issuance: shocked companies due to refinance their loans substitute away from institutional tranches towards other types of securities. I show that the substitution is imperfect, causing an increase in the cost of borrowing for affected firms. In the second chapter, which is co-authored with Simona Risteska, we use data on mutual fund portfolio holdings to extract fund managers’ stock return expectations. We use panel regressions and economic theory to demonstrate that we are able to partial out the effect of time-varying stock and manager characteristics (e.g., risk-aversion) and show that subjective expected returns are significantly affected by personal experience. Managers are more strongly influenced by recent returns and those experienced at the early stages of their holding period. The third chapter, co-authored with Marco Pelosi and Simona Risteska, provides evidence of the disparity in the incidence of property taxes levied at different points in time. Housing demand is significantly less elastic with respect to taxes deferred to the future relative to taxes levied at the moment of the purchase. We attribute this difference to the lack of salience of future taxes at the moment of purchase. We provide directions on the optimal tax mix between salient and nonsalient taxes with the help of a model.

Item Type: Thesis (PhD)
Additional Information: © 2021 Francesco Nicolai
Library of Congress subject classification: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
Sets: Departments > Finance
Supervisor: Lou, Dong

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