Firm efficiency, foreign ownership and CEO gender in corrupt environments

We study the effects of corruption on firm efficiency using a unique dataset of private firms from 14 Central and Eastern European countries from 2000 to 2013. We find that an environment characterized by a high level of corruption has an adverse effect on firm efficiency. This effect is stronger for firms with a lower propensity to behave corruptly, such as foreign-controlled firms and firms managed by female CEOs, while local firms and firms with male CEOs are not disadvantaged. We also find that an environment characterized by considerable heterogeneity in the perception of corruption is associated with an increase in firm efficiency. This effect is particularly strong for foreign-controlled firms from low corruption countries, while no effect is observed for firms managed by a female CEO

Hedge fund replication with a genetic algorithm: breeding a usable mousetrap

This study tests the performance of 14 hedge fund index clones created using parsimonious outof- sample replication portfolios consisting solely of easily accessible assets. We employ a genetic algorithm to integrate two traditional hedge fund replication methods, the factor-based and payoff distribution replication methods, and evaluate over 4500 commonly held stocks, bonds and mutual funds as replicating portfolio components. In-sample performance indicates that hedge funds have return series similar to portfolios of commonly held assets, and out-of-sample results provide evidence that the in-sample relationships can hold with infrequent rebalancing. This hedge fund replication attempt rates well relatively to prior efforts as 11 replicating portfolios have out-of-sample correlation values of at least 60%. Overall, these results show promise for using a genetic algorithm technique to replicate hedge fund returns

Corporate profitability and the global persistence of corruption

We examine the persistence of corporate corruption for a sample of privately-held firms from 12 Central and Eastern European countries from 2001 to 2015. Using publicly available information and stochastic frontier analysis, we create a proxy for corporate corruption based on a firm's internal inefficiency. We find that corruption enhances a firm's profitability. A channel analysis further reveals that inflating staff costs is the most common approach by which firms divert funds to finance corruption. In spite of corruption's negative effects on a country's economy, we conclude that it persists because of its ability to improve corporate profitability. We refer to this effect as the Corporate Advantage Hypothesis

M&A activity and the capital structure of target firms

We study 6,083 European firms that were acquired between 1999 and 2015. Soon after the acquisition, the acquired firms promptly and substantially close the gap between their actual leverage ratios and their target (optimal) ratios. Firms that were over- (under-) leveraged at the start of their acquisition year move their debt-to-assets ratio from 34.1% to 20% (10% to 18.5%) by the end of the following year. Under-leveraged firms expand their assets rapidly following acquisition, as they gain improved access to investable resources. Our results are consistent with the trade-off theory of capital structure and with the existence of firm-specific target leverage ratios

Asymmetries in the Firm's use of debt to changing market values

Using a sample of U.S. firms over the period, 1984 to 2013, this study examines the relation between market and book leverage ratios. Unlike Welch (2004) who contends that changes in market leverage do not induce adjustments in book leverage, we find an asymmetric effect. That is, firms adjust their book leverage only when the changes in market leverage are due to increases in equity values. No adjustment is observed when firm equity values decrease. Our results are consistent with Myers (1977) and Barclay et al. (2006) who argue that optimal debt levels decrease with corporate growth opportunities. © 2017 The Author

Firm efficiency, foreign ownership and CEO gender in corrupt environments

We study the effects of corruption on firm efficiency using a unique dataset of private firms from 14 Central and Eastern European countries from 2000 to 2013. We find that an environment characterized by a high level of corruption has an adverse effect on firm efficiency. This effect is stronger for firms with a lower propensity to behave corruptly, such as foreign-controlled firms and firms managed by female CEOs, while local firms and firms with male CEOs are not disadvantaged. We also find that an environment characterized by considerable heterogeneity in the perception of corruption is associated with an increase in firm efficiency. This effect is particularly strong for foreign-controlled firms from low corruption countries, while no effect is observed for firms managed by a female CEO. © 2016 The Authors

Two essays on payout policy

The first essay examines the impact of insider trading law enforcement on dividend payout policy. We posit and confirm that firms use dividend payouts to mitigate agency costs caused by gaps in country-level investor protection. We find that first-time enforcement of insider trading laws leads to a lower likelihood of paying dividends, lower dividend amounts, lower dividend smoothing and target payout ratios. We also show that market value of dividends declines significantly following the enforcement of insider trading laws. These results suggest that dividends serve as a substitute bonding mechanism through which managers establish a reputation for the fair treatment of minority shareholders when insider trading is not restricted. Firms mitigate the shortcomings of a weak institutional environment by committing to higher and more consistent payout policies. The second essay investigates the interaction among dividend smoothing, equity value and agency costs. Using a comprehensive cross-country sample from 21 countries, we show that market puts a premium on smooth dividends and dividend smoothing increases with agency costs of equity. Most importantly, we find that the premium for smooth dividends is decreasing in shareholder rights, suggesting that when agency costs are small the market puts a low premium on smooth dividends. The bonding framework of dividend smoothing might also shed some light on why smoothing in the US has increased over time. Consistent with our findings, we argue that the necessity to smooth dividends has increased over time due to increasing repurchase-for-dividend substitution that is previously documented in Grullon and Michaely (2002). Further analyses show that on average $1 paid out through dividends contributes to equity value by about 40$1 paid out in repurchases using the most conservative model. Put differently, in order not to reduce the value of equity, firms need to substitute $1.4 in repurchases for$1 decrease in dividends. To manage the enormous payout burden of dividend-repurchase substitution and to maximize equity value, managers have been increasingly compelled to make dividends smoother. Consistently, we show that firms that pay smoother dividends substitute dividends for repurchases at 23% faster rate than the firms with less smooth dividends. Overall, these results support the view that dividend smoothing is a bonding mechanism used to undo the agency cost discount on equity valuation

Hedge fund replication with a genetic algorithm: breeding a usable mousetrap

This study tests the performance of 14 hedge fund index clones created using parsimonious outof- sample replication portfolios consisting solely of easily accessible assets. We employ a genetic algorithm to integrate two traditional hedge fund replication methods, the factor-based and payoff distribution replication methods, and evaluate over 4500 commonly held stocks, bonds and mutual funds as replicating portfolio components. In-sample performance indicates that hedge funds have return series similar to portfolios of commonly held assets, and out-of-sample results provide evidence that the in-sample relationships can hold with infrequent rebalancing. This hedge fund replication attempt rates well relatively to prior efforts as 11 replicating portfolios have out-of-sample correlation values of at least 60%. Overall, these results show promise for using a genetic algorithm technique to replicate hedge fund returns

Sentiment and Stock Returns: Anticipating a Major Sporting Event -- Online Appendix

Table 3 (Appendix): Average Daily Raw Returns around NFL Super Bowl Events for Firms Headquartered in Losing, Winning, Favored, and Non-Favored States and the S&P 500 Table 5 (Appendix): Average Daily Abnormal Returns around NFL Super Bowl Events for Firms Headquartered in Losing, Winning, Favored, and Non-Favored States Table 6 (Appendix): Average Daily Abnormal Returns around NFL Super Bowl Events for Firms Headquartered in Losing, Winning, Favored, and Non-Favored States Conditioned on whether the Firm is in a Losing or Winning State Table 7 (Appendix) : Sample Split into Size Quintiles Table 8 (Appendix) : Characteristics of the Matched Sample and Comparison to Main Sample Table 9 (Appendix) : Comparison of Mean Cumulative Abnormal Returns between the Main Sample and Its Matc

Hedge fund replication with a genetic algorithm: Breeding a usable mousetrap

This study tests the performance of 14 hedge fund index clones created using parsimonious out-of-sample replication portfolios consisting solely of easily accessible assets. We employ a genetic algorithm to integrate two traditional hedge fund replication methods, the factor-based and pay-off distribution replication methods, and evaluate over 4500 commonly held stocks, bonds and mutual funds as replicating portfolio components. In-sample performance indicates that hedge funds have return series similar to portfolios of commonly held assets, and out-of-sample results provide evidence that the in-sample relationships can hold with infrequent rebalancing. This hedge fund replication attempt rates well relatively to prior efforts as 11 replicating portfolios have out-of-sample correlation values of at least 60%. Overall, these results show promise for using a genetic algorithm technique to replicate hedge fund returns