Knowledge that Transforms

Most affine models of the term structure with stochastic volatility predict that the variance of the short rate should play a ‘dual role’ in that it should also equal a linear combination of yields. However, we find that estimation of a standard affine three-factor model results in a variance state variable that, while instrumental in explaining the shape of the yield curve, is essentially unrelated to GARCH estimates of the quadratic variation of the spot rate process or to implied variances from options. We then investigate four-factor affine models. Of the models tested, only the model that exhibits ‘unspanned stochastic volatility’ (USV) generates both realistic short rate volatility estimates and a good cross-sectional fit. Our findings suggest that short rate volatility cannot be extracted from the cross-section of bond prices. In particular, short rate volatility and convexity are only weakly correlated.

We find that fixed effects related to the location of firms’ headquarters explain variation in broad based option grants after controlling for industry effects and firm characteristics traditionally known to affect option granting. Location matters because of local labor market conditions and social interaction with neighboring firms. Broad based option grants are higher: (i) when a firm's stock prices co-move more with stock prices of other firms located in that Metropolitan Statistical Area (MSA); (ii) in states that are less likely to enforce non-compete agreements; and (iii) in MSAs where employees prefer options because stocks there experience abnormally high returns.

This paper examines whether cross-listing in the U.S. reduces firms’ costs of capital. We estimate cost of capital effects implied by market prices and analyst forecasts, which accounts for changes in growth expectations around cross-listings. Firms with cross-listings on U.S. exchanges experience a decrease in their cost of capital between 70 and 120 basis points. These effects are sustained and exist after the Sarbanes-Oxley Act. We find smaller reductions for cross-listings in the over-the-counter market and for exchange-listings from countries with stronger legal institutions. For exchange-traded cross-listings, the cost of capital reduction accounts for over half of the increase in firm value, whereas for other types of cross-listings the valuation effects are primarily attributable to contemporaneous revisions in growth expectations.

Equity-based compensation affects managers’ risk-taking behavior, which in turn has an impact on shareholder wealth. In response to an exogenous increase in takeover protection in Delaware during the mid-1990s, managers lower firm risk by 6%. This risk reduction is concentrated among firms with low managerial equity-based incentives, in particular firms with low chief executive officer portfolio sensitivity to stock return volatility. Furthermore, the risk reduction is value-destroying. Finally, firms respond to the increased protection accorded by the regime shift by providing managers with greater incentives for risk-taking.

Theory suggests that banks’ private information lets them hold up borrowers for higher interest rates. Since new information about a firm is revealed at the time of its bond IPO, it follows that banks will be forced to adjust their loan interest rates downwards after firms undertake their bond IPO. We test this hypothesis and find that firms are able to borrow at lower interest rates after their bond IPO. Importantly, firms that get their first credit rating at the time of their bond IPO benefit from larger interest rate savings than those that already had a credit rating. These findings provide support for the hypothesis that banks price their informational monopoly. We also find that it is costly for firms to enter the public bond market.

In this paper, I propose that technological innovations increase expected stock returns and premiums at the aggregate level. I use aggregate patent data and research and development (R&D) data to measure technological innovations in the U.S., and find that patent shocks and R&D shocks have positive and distinct predictive power for U.S. market returns and premiums. Similar patterns are also found in international data including other G7 countries, China, and India. These findings are consistent with previous empirical studies based on firm-level data, and call for further theoretical explanations.

We consider a dynamic limit order market in which traders optimally choose whether to acquire information about the asset and the type of order to submit. We numerically solve for the equilibrium and demonstrate that the market is a “volatility multiplier”: prices are more volatile than the fundamental value of the asset. This effect increases when the fundamental value has high volatility and with asymmetric information across traders. Changes in the microstructure noise are negatively correlated with changes in the estimated fundamental value, implying that asset betas estimated from high-frequency data will be incorrect.

This paper shows that active investors, such as venture capitalists, can affect the speed at which new ventures grow. In the absence of product market competition, new ventures financed by active investors grow faster initially, though in the long run those financed by passive investors are able to catch up. By contrast, in a competitive product market, new ventures financed by active investors may prey on rivals that are financed by passive investors by “strategically overinvesting” early on, resulting in long-run differences in investment, profits, and firm growth. The value of active investors is greater in highly competitive industries as well as in industries with learning curves, economies of scope, and network effects, as is typical for many “new economy” industries. For such industries, our model predicts that start-ups with access to venture capital may dominate their industry peers in the long run.

Given the key role of liquidity in finance research, identifying high quality proxies based on daily (as opposed to intraday) data would permit liquidity to be studied over relatively long timeframes and across many countries. Using new measures and widely employed measures in the literature, we run horseraces of annual and monthly estimates of each measure against liquidity benchmarks. Our benchmarks are effective spread, realized spread, and price impact based on both Trade and Quote (TAQ) and Rule 605 data. We find that the new effective/realized spread measures win the majority of horseraces, while the Amihud [2002. Illiquidity and stock returns: cross-section and time-series effects. Journal of Financial Markets 5, 31–56] measure does well measuring price impact.

Similarly priced stocks move together. Stocks that undergo splits experience an increase in comovement with low-priced stocks and a decrease in their comovement with high-priced stocks. Price-based comovement is not explained by economic fundamentals, firm size, or changes in liquidity or information diffusion. The shift in comovement following splits is greater for large stocks, high-priced stocks, and when investor sentiment is high. In the full cross-section, price-based portfolios explain variation in stock-level returns after controlling for movements in the market and industry portfolios as well as portfolios based on size, book-to-market, transaction costs, and return momentum. The results suggest that investors categorize stocks based on price.