Clara Vega

Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market

We study the impact of algorithmic trading in the foreign exchange market using a long time series of high-frequency data that specifically identifies computer-generated trading activity. Using both a reduced-form and a structural estimation, we find clear evidence that algorithmic trading causes an improvement in two measures of price efficiency in this market: the frequency of triangular arbitrage opportunities and the autocorrelation of high-frequency returns. Relating our results to the recent theoretical literature on the subject, we show that the reduction in arbitrage opportunities is associated primarily with computers taking liquidity, while the reduction in the autocorrelation of returns owes more to the algorithmic provision of liquidity. We also find evidence that algorithmic traders do not trade with each other as much as a random matching model would predict, which we view as consistent with their trading strategies being highly correlated. However, the analysis shows that this high degree of correlation does not appear to cause a degradation in market quality.

Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices

We propose a formal test of the hypothesis that energy prices are predetermined with respect to U.S. macroeconomic aggregates. The test is based on regressing changes in daily energy prices on daily news from U.S. macroeconomic data releases. Using a wide range of macroeconomic news, we find no compelling evidence of feedback at daily or monthly horizons, contradicting the view that energy prices respond instantaneously to macroeconomic news and consistent with the commonly used identifying assumption that there is no feedback from U.S. macroeconomic aggregates to monthly innovations in energy prices.

Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market: Rise of the Machines

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.

Economic News and International Stock Market Co-Movement

We analyze the effects that real-time domestic and foreign news about fundamentals have on the co-movement between stock returns of a small, open economy, Portugal, and a large economy, the United States. Consistent with our theoretical model, we find that US macroeconomic news and Portuguese earnings news do not affect stock market co-movement, whereas Portuguese macroeconomic news lowers stock market co-movement. We find that US news affects Portuguese stock market returns, though less so when US stock market returns are included in the regression. We provide evidence, contrary to common wisdom, that this last result does not derive from contagion. Copyright 2009, Oxford University Press.

Strategic Cross-Trading in the U.S. Stock Market

We model and test for the role of heterogeneously informed, strategic multi-asset speculation for cross-price impact—the impact of trades in one asset on the prices of other (even unrelated) assets—in the U.S. stock market. Our investigation of the trading activity in New York Stock Exchange (NYSE) and National Association of Securities Dealers Automated Quotation System (NASDAQ) stocks between 1993 and 2004 reveals that, consistent with our model, (1) daily order imbalance in one industry or random stock has a significant, persistent, and robust impact on daily returns of other (even unrelated) industries or random stocks; (2) cross-price impact is often negative; and (3) both direct (i.e., an asset’s own) and absolute (i.e., unsigned) cross-price impact are smaller when speculators are more numerous, greater when market-wide dispersion of beliefs is higher, and greater among stocks dealt by the same specialist.

The Monetary Origins of Asymmetric Information in International Equity Markets

Existing studies using low-frequency data have found that macroeconomic shocks contribute little to international stock market covariation. However, these papers have not accounted for the presence of asymmetric information where sophisticated investors generate private information about the fundamentals that drive returns in many countries. In this paper, we use a new microstructure data set to better identify the effects of private and public information shocks about U.S. interest rates and equity returns. High-frequency private and public information shocks help forecast domestic money and equity returns over daily and weekly intervals. In addition, these shocks are components of factors that are priced in a model of the cross section of international returns. Linking private information to U.S. macroeconomic factors is useful for many domestic and international asset pricing tests.

The Impact of Credibility on the Pricing of Managerial Textual Content

This paper examines whether, and under what conditi s, the “soft” information contained in the text of management’s quarterly earnings press relea s s is incrementally informative over company-issued “hard” information. We use several t extual-analysis programs to extract various dimensions of managerial net optimism from more tha n 20,000 corporate earnings announcements over the period 1998 to 2006 and document that unan ticipated net optimism in managers’ language affects announcement period abnormal retur ns and predicts post-earnings announcement drift. We further find, consistent with economic th eory, that two key aspects of the information environment influence the price-responsiveness to n et optimism: (i) the informativeness of the contemporaneously available hard information; and ( ii) the likely credibility of the net optimism itself. We also show that the second moment of soft information, the level of uncertainty in the text, attenuates the market’s response to earnings a nouncement surprises, is associated with contemporaneous announcement period idiosyncratic v olatility, and predicts future idiosyncratic volatility incrementally to “hard” information. JEL Classifications: G14; D82; M41

Stock Market Microstructure Measures of Information Asymmetry are Related to Marketwide Information

This paper studies the impact of macroeconomic news on the stock market microstructure measures of information asymmetry. The results show that, due to the daily changes in the information environment, daily information asymmetry has a global impact, though on annual basis, the information asymmetry measures have significantly positive relations with the firm specific cash flow news constructed by using Vuolteenahos (2002) vector autoregressive model to decompose the individual stock return into cash flow and discount rate news. The daily information asymmetry measures we evaluated significantly increase during both the macroeconomic and the earnings announcement periods, which suggests the important role played by the macroeconomic news on the formation of information asymmetry. Stock information asymmetry measures also co-move with the stock market average and governement bond market information asymmetry measures, and the covariations are significantly larger during macroeconomic- and non-earnings-non-macroecomic-announcement periods than during the earnings announcement periods, suggesting that the macroeconomic news that influence all the firms in the economy mainly induces the covariations in information asymmetry. Furthermore, the results show that macroeconomic news is the important source of the global impact of information asymmetry for firms in both the same and different industries, while possibly correlated cash flow news affecting firms in the same industry is another source of the commonality of information asymmetry for firms within the same industry.

Is the intrinsic value of a macroeconomic news announcement related to its asset price impact

The literature documents a heterogeneous asset price response to macroeconomic news announcements. We relate this heterogeneity to a novel measure of the intrinsic value of an announcement—the announcement’s ability to nowcast GDP growth, inflation, and the federal funds target rate—and find that differences across the intrinsic values of several U.S. macroeconomic announcements explain a significant fraction of the variation in the impact each of these announcements has on U.S. Treasury yields. We also decompose the intrinsic value into the announcement’s relation to fundamentals, a timeliness premium, and a revision premium, and find that the former two characteristics are the most important ones in explaining the heterogeneous response.

Counterparty Risk and Counterparty Choice in the Credit Default Swap Market

We investigate how market participants price and manage counterparty risk in the post-crisis period using confidential trade repository data on single-name credit default swap (CDS) transactions. We find that counterparty risk has a modest impact on the pricing of CDS contracts, but a large impact on the choice of counterparties. We show that market participants are significantly less likely to trade with counterparties whose credit risk is highly correlated with the credit risk of the reference entities and with counterparties whose credit quality is relatively low. Furthermore, we examine the impact of central clearing on CDS pricing. Contrary to the previous literature, but consistent with our main findings on pricing, we find no evidence that central clearing increases transaction spreads.