We study the impact of algorithmic trading (AT) in the foreign exchange market using a long time series of high‐frequency data that identify computer‐generated trading activity. We find that AT causes an improvement in two measures of price efficiency: the frequency of triangular arbitrage opportunities and the autocorrelation of high‐frequency returns. We show that the reduction in arbitrage opportunities is associated primarily with computers taking liquidity. This result is consistent with the view that AT improves informational efficiency by speeding up price discovery, but that it may also impose higher adverse selection costs on slower traders. In contrast, the reduction in the autocorrelation of returns owes more to the algorithmic provision of liquidity. We also find evidence consistent with the strategies of algorithmic traders being highly correlated. This correlation, however, does not appear to cause a degradation in market quality, at least not on average.

Rating agencies have become more conservative in assigning corporate credit ratings over the period 1985 to 2009; holding firm characteristics constant, average ratings have dropped by three notches. This change does not appear to be fully warranted because defaults have declined over this period. Firms affected more by conservatism issue less debt, have lower leverage, hold more cash, are less likely to obtain a debt rating, and experience lower growth. Their debt spreads are lower than those of unaffected firms with the same rating, which implies that the market partly undoes the impact of conservatism on debt prices. This evidence suggests that firms and capital markets do not perceive the increase in conservatism to be fully warranted.

This study shows that the guardians behind underaged accounts are successful at picking stocks. Moreover, they tend to channel their best trades through the accounts of children, especially when they trade just before major earnings announcements, large price changes, and takeover announcements. Building on these results, we argue that the proportion of total trading activity through underaged accounts (labeled BABYPIN ) should serve as an effective proxy for the probability of information trading in a stock. Consistent with this claim, we show that investors demand a higher return for holding stocks with a greater likelihood of private information, proxied by BABYPIN .