Essays in finance

Chapter 1 studies how short-sale constraints on stock lending affect asset prices in an equilibrium model with multiple assets. We endow investors with heterogeneous beliefs in order to generate short selling demand. We obtain a CAPM-like equation that links asset-specific excess returns with the market equity premium. In the presence of short-sale constraints in the market, the model gives rise to asset-specific alphas that are explained by both asset-specific and market-wide short-sale constraints; unconstrained stocks have higher risk-adjusted expected returns relative to the market portfolio, whereas the opposite holds for constrained stocks. In the absence of short-sale constraints, the model reduces to the standard CAPM. We test the model using extensive data on short interest and borrow fees. The model is able to empirically explain asset prices for 10 borrow-fee-sorted portfolios, as opposed to CAPM and factor models which produce unexplained alphas that are significantly different from zero for high borrow fee portfolios. Chapter 2 studies whether top-level insiders change their insider trading patterns when their stocks are short-sale constrained. Highly constrained stocks, which we identify using the asset-specific alpha from Chapter 1, are closely followed by specialized investors who are either keen to collect the high borrow fees on the long side or confident enough to pay the high borrow fees on the short side. Since insiders' transactions are publicly filed, they have the incentive to postpone any previously scheduled stock sales and even engage in purchasing, thus sending a reassuring signal to the market and ultimately increasing their stock-based compensation. Independently, insiders may be better informed than the market; if disagreement among investors is large, which we proxy for using borrowing demand, there is a greater opportunity for insiders to exploit their advantage and increase their insider purchasing or selling, as appropriate. We test our hypotheses using the Chapter 1 data on short interest and borrow fees combined with comprehensive data on insider transactions from public filings and find strong support for the signaling hypothesis in the case of sales but only partial support in the case of purchases, possibly due to confounding effects from fear of SEC enforcement actions. We find little evidence of informed trading. Chapter 3 studies how the innovation levels of startups that participate in seed accelerator programs change after participating in a program. Seed accelerator programs constitute the first round of institutional funding for a large fraction of the participants but, as opposed to angel and early-stage VC investment, involve a constant competitive interaction with similar startups and a shorter-term involvement with lower equity stakes for the investors. Angel and VC-backed startups' innovation rates increase after funding; I examine whether the same occurs for accelerator alumni. Using a sample of approximately 14,000 startups and 30,000 patents hand-collected from a variety of online sources, I compare patenting rates by seed accelerators' alumni to patenting rates by non-accelerated early stage startups with similar characteristics and that were funded by the same investors, matched by propensity score. I find that accelerator alumni startups' innovation rates do not change significantly from pre-program levels, as opposed to otherwise comparable startups that receive conventional seed funding.

Keywords: Economics.
Advisor: Bloom Nick
Berk Jonathan B.
Bernstein Shai