Essays in finance: initial public offerings and risk backtesting

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Date

2020

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Abstract

Asset prices are a central research object in financial economics. In this thesis, Chapters 2 and 3 are concerned with studying the initial public offering (IPO), the process by which previously private firms offer their shares to the general public for the first time, eventually resulting in a first stock exchange valuation. Chapter 2 proposes a new measure of investor sophistication using the internet log file data set of the United States Securities and Exchange Commission (SEC) Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system and investigates the role of sophisticated and unsophisticated investor attention for IPO pricing. Chapter 3 defines a daily SEC workload measure at the SEC industry office level and performs an analysis of the SEC filing review process for IPOs, including textual analysis of SEC comments. The dissertation uses this to examine the interaction among high SEC workload, filing review outcomes, and IPO pricing. The second main focus of this dissertation, set out in Chapters 4 and 5, is backtesting of market risk forecasts for financial returns, which is a central concern of risk managers as soon as an asset is traded publicly. Chapter 4 proposes novel Value-at-Risk (VaR) backtests for the independence property of VaR forecasts using the extremal index, which is a concept from extreme value theory. The tests are analyzed and compared to existing alternatives using Monte Carlo simulations. Chapter 5 conducts a critical analysis of volatility forecasting capabilities of a large set of Generalized Autoregressive Conditional Heteroscedasticity (GARCH)-type models for returns on the Bitcoin cryptocurrency, known for its extreme price changes. Model confidence sets are calculated for different loss functions, volatility proxies, and significance levels to obtain models with equal predictive ability.

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Corporate finance, Risk management

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