Browsing by Author "Back, Kerry E"

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    Essays on Asset Pricing
    (2023-04-19) Kazempour, Seyed Mohammad; Back, Kerry E
    This thesis has three chapters. In the first chapter, titled "Disseminating Information on Twitter: Evidence from Investment Advisers," I show that investment advisers disseminate valuable stock information on their Twitter accounts. A one standard deviation increase in the sentiment of their tweets predicts a 12 bps increase in abnormal returns over the next week. This informativeness is not a result of pump-and-dump strategies or ex-post window-dressing. Advisers' tweets disseminate and interpret public news, especially analyst revisions and earnings announcements. Furthermore, they identify which recent trends in stock prices are fundamentally justified. Advisers offering financial planning services post more informative tweets. My results highlight the value of Twitter for connecting advisers and investors. The second chapter is titled "Validity, Tightness, and Forecasting Power of Risk Premium Bounds." In this chapter, we test recently-published bounds on market and individual stock risk premia conditionally. We cannot reject that they are valid, but we do reject that they are tight. Using the market bounds as forecasts appears unreasonable in many cases due to their high slackness. Adding past mean slackness is a potential improvement but is hampered by the brevity of the available data series. The correlation of the stock bounds with subsequent returns stems primarily from the time series rather than the cross-section. Finally, in the third chapter, titled "Democratizing Securities Research," I define democratization as reducing the cost of acquiring and disseminating analyst reports, and present a model featuring heterogeneous analysts and intermediaries with different levels of democratization. I show that a pecking order appears among intermediaries where less democratized ones, facing higher costs per analyst, employ analysts with higher skills. Hence my model justifies the observed heterogeneity in analysts' skills between brokerage houses and crowdsourcing platforms. The model predicts a range of consequences for democratization. Most importantly, adding a new, more democratized platform can increase or decrease the value of information available to investors.