Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market
Published: 9/12/2014, Volume: 69, Issue: 5 | DOI: 10.1111/jofi.12186 | Cited by: 449
ALAIN P. CHABOUD, BENJAMIN CHIQUOINE, ERIK HJALMARSSON, CLARA VEGA
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.
Good News, Bad News, Volatility, and Betas
Published: 12/1995, Volume: 50, Issue: 5 | DOI: 10.1111/j.1540-6261.1995.tb05189.x | Cited by: 282
PHILLIP A. BRAUN, DANIEL B. NELSON, ALAIN M. SUNIER
We investigate the conditional covariances of stock returns using bivariate exponential ARCH (EGARCH) models. These models allow market volatility, portfolio‐specific volatility, and beta to respond asymmetrically to positive and negative market and portfolio returns, i.e., “leverage” effects. Using monthly data, we find strong evidence of conditional heteroskedasticity in both market and non‐market components of returns, and weaker evidence of time‐varying conditional betas. Surprisingly while leverage effects appear strong in the market component of volatility, they are absent in conditional betas and weak and/or inconsistent in nonmarket sources of risk.