The question of whether and to what extent option trading affects underlying stock prices has been of interest to researchers since exchange-based options trading began in 1973. Recent research presents evidence of an informational channel through which option trading affects stock prices by showing that option market makers’ stock trades to hedge new options positions cause the information reflected in option trading to be impounded into underlying equity prices. This paper provides evidence of a noninformational channel through which option market maker hedge rebalancing affects stock return volatility and the probability of large stock price moves.

By buying convertibles and shorting the underlying stock, hedge funds distribute equity exposure to well-diversified shareholders. We find that firms with characteristics that make seasoned equity offerings expensive are more likely to issue convertibles to hedge funds. We conclude that hedge funds provide opportunities for firms to issue convertible securities at a lower cost than seasoned equity by serving as relatively low-cost distributors of equity exposure. A higher fraction of a convertible is privately placed with hedge funds when institutional ownership, stock liquidity, issue size, concurrent stock repurchases, and limitations on callability suggest that shorting costs will be lower.

We examine the effects of price disclosure on market performance in a continuous experimental multiple-dealer market in which seven professional market makers trade a single security. The dealers trade with one another and with computerized informed and liquidity traders. Our key comparison is between fully public price queues (pretrade transparent market) and bilateral quoting (pretrade opaque). We find that opening spreads are wider and trading volume is lower in the opaque markets due to higher search costs there. More importantly, however, higher search costs also induce more aggressive pricing strategies, so that price discovery is much faster in the opaque markets.

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure employs continuous approximations of filtering densities, and delivers unconditionally optimal global approximations of targeted integrands to achieve likelihood approximation. Optimized approximations of targeted integrands are constructed via efficient importance sampling. Resulting likelihood approximations are continuous functions of model parameters, greatly enhancing parameter estimation. We illustrate our procedure in applications to dynamic stochastic general equilibrium models.

We hypothesize that financial risk-taking originates in preindustrial interpersonal population diversity. We use data on immigrants residing in the United States and show that controlling for all known determinants of portfolio decisions and more than 100 control variables, diversity in the country of immigrants’ origin positively affects stock market participation and the level of risky asset holdings. Our results remain robust when instrumenting diversity with plant variety. We also identify the channels through which the effect of diversity operates (mostly individualism and human capital), but also conclude that diversity exerts an independent effect.

Lending to corporates in foreign currencies can expose banks to substantial currency risk. Using global syndicated loan data, we find that a one-standard-deviation increase in exchange rate volatility increases loan spreads somewhere in the range between 5.5 and 16.1 basis points for loans made in a currency different from the lenders’. This implies excess interest of approximately 1 to 3 USD million for loans of average size and duration. We also show that this finding is mostly attributed to credit constraints and deviations from perfect competition in international lending markets, and that borrowers can lower the extra cost by forming strong lending relationships with their banks.

In this paper, we investigate the dynamic relationship between financial market volatility, macroeconomic fundamentals and investor sentiment, employing a two-factor model to decompose volatility into a persistent long run component and a transitory short run component. Using a structural VAR model with Bayesian sign restrictions, we show that adverse shocks to aggregate demand and supply cause an increase in the persistent component of both stock and bond market volatility, and that adverse shocks to the persistent component of either stock or bond market volatility cause a deterioration in macroeconomic fundamentals. We find no evidence of a relationship between the transitory component of volatility and macroeconomic fundamentals. Instead, we find that the transitory component is more closely associated with changes in investor sentiment. Our results are robust to a wide range of alternative specifications. Out-of-sample forecasting shows that the components of volatility can improve forecasts of macroeconomic fundamentals, and vice versa.

This paper investigates the relations between female leadership, firm performance, and corporate governance in a global panel of 329 Microfinance Institutions (MFIs) in 73 countries covering the years 1998–2008. The microfinance industry is particularly suited for studying the impact of female leadership on governance and performance because of its mission orientation, its entrepreneurial nature, diverse institutional conditions, and high percentage of female leaders. We find female leadership to be significantly associated with larger boards, younger firms, a non-commercial legal status, and more female clientele. Furthermore, we find that a female chief executive officer and a female chairman of the board are positively related to MFI performance, but this result is not driven by improved governance.

This paper reconsiders the formal estimation of bank risk using the variability of the profit function. In our model, point estimates of the variability of profits are derived from a model where this variability is endogenous to other bank characteristics, such as capital and liquidity. We estimate the new model on the entire panel of US banks, spanning the period 1985q1–2012q4. The findings show that bank risk was fairly stable up to 2001 and accelerated quickly thereafter up to 2007. We also establish that the risk of the relatively large banks and banks that failed in the subprime crisis is higher than the industry’s average. Thus, we provide a new leading indicator, which is able to forecast future solvency problems of banks.