Chapter 1: Despite the rapid growth of passive ownership over the past 30 years, there is no consensus on how or why passive ownership affects stock price informativeness. This paper provides a new answer to this question by examining how passive ownership changes investors' incentives to acquire information. I develop a model where passive ownership affects how many investors gather information and how investors allocate attention between systematic and idiosyncratic risk. The model also links investors' learning decisions to price informativeness through quantities that are readily observable in the data: trading volume, returns and volatility. The model's predictions motivate three new measures of price informativeness, all of which declined on average over the past 30 years. In the cross-section, increases in passive ownership are negatively correlated with price informativeness. To establish causality, I show that price informativeness decreases after quasi-exogenous increases in passive ownership arising from index additions and rebalancing. Chapter 2: Can an household-level financial transaction data yield new insights about firm-specific risk? Using an increasingly accessible class of household financial transaction data, we show we can construct accurate pictures of firm revenue, growth, geographic dispersion, and customer base characteristics. We then develop, and make public, two new measures characterizing firms' customer bases - the rate of churn in a firm's customer base and the pairwise similarity between firms' customer bases. While these measures of customer bases are impossible to construct utilizing traditional sources of firm data, we show that they provide important insights into the behavior of both real firm decisions and firm asset prices. Rates of customer churn affect the level and volatility of firm-level investment, markups, and profits. Churn also affects how quickly firms respond to shocks in the value of their growth options (i.e. Tobin's Q). Similarity between firms' customer bases highlights one under-explored type of predictability among stock returns - we demonstrate that significant alpha can be generated using a trading strategy that exploits our index of customer base similarity across firms. Chapter 3: We examine next-day newspaper accounts of large daily jumps in 16 national stock markets to assess their proximate cause, clarity as to cause, and the geographic source of the market-moving news. Our sample of 6,200 market jumps yields several findings. First, policy news - mainly associated with monetary policy and government spending - triggers a greater share of upward than downward jumps in all countries. Second, the policy share of upward jumps is inversely related to stock market performance in the preceding three months. This pattern strengthens in the postwar period. Third, market volatility is much lower after jumps triggered by monetary policy news than after other jumps, unconditionally and conditional on past volatility and other controls. Fourth, greater clarity as to jump reason also foreshadows lower volatility. Clarity in this sense has trended upwards over the past century. Finally, and excluding U.S. jumps, leading newspapers attribute one-third of jumps in their own national stock markets to developments that originate in or relate to the United States. The U.S. role in this regard dwarfs that of Europe and China.

Creator

• Sammon, Marco

DOI

• https://doi.org/10.21985/n2-gnft-zs56

Subject

• Economics
• Finance
• Economic theory

Language

• en

Alternate Identifier

• etdadmin_upload_818012
• http://dissertations.umi.com/northwestern:15554

Date created

• 2021-01-01

Resource type

• Dissertation

Rights statement

• In Copyright