Order flows, news, and exchange rate volatility

Journal of Empirical Finance, 1997

This paper estimates the impact of market activity and news on the volatility of returns in the exchange market for Japanese Yen and US dollars. We examine the effects of news on volatility before, during and after news arrival, using three categories of news. Market activity is proxied by quote arrival, separated into a predictable seasonal component and an unexpected component. Results indicate that both components of market activity, as well as news releases, affect volatility levels. We conclude that both private information and news effects are important determinants of exchange rate volatility. Our finding that unexpected quote arrival positively impacts foreign exchange rate volatility is consistent with the interpretation that unexpected quote arrival serves as a measure of informed trading. Corroborating this interpretation is regression analysis, which indicates that spreads increase in the surprise component of the quote arrival rate, but not in the expected component. The estimated impact of a unit increase in unexpected quote arrival and the range of values observed for this variable imply an important volatility conditioning role for informed trading.

Journal of Banking & Finance, 2011

JEL classification: F31 G12 G15

Journal of Financial and Quantitative Analysis, 2008

In textbook models of exchange rate determination, the news contained in public information announcements is directly impounded into prices with there being no role for trading in this process of information assimilation. This paper directly tests this theoretical result using transaction level exchange rate return and trading data and a sample of scheduled macroeconomic announcements. The main result of the paper is that even information that is publicly and simultaneously released to all market participants is partially impounded into prices via the key micro level price determinant—order flow. We quantify the role that order flow plays and find that approximately one third of price-relevant information is incorporated via the trading process.

Accounting & Finance, 2009

We apply the trading model of . to a number of currency markets. The model posits that two markets can have common volatility structures as a result of receiving common information and from cross-hedging activity where a position in one currency is used to hedge risk in a position taken in another. Our results imply that the model is effective in identifying common information flows and volatility spillovers in the currency markets and that some of these effects are lost when simply examining raw correlations. A series of specification tests of the 21 bivariate systems that are examined provides support for the trading model in the foreign exchange context.

In macroeconomic models exchange rates are determined by public information. Trading activities are completely irrelevant. In general, these models have low explanatory power for short horizons, which might be due to the possible existence of private information. Dealers in the foreign exchange market consider the order flow from customers to be the most important source of private information. I test a microstructural trading model incorporating private information, including both order flow and macroeconomic variables. The results show that order flow is an important variable for explaining weekly changes in exchange rates, thereby indicating an important role for private information. The strongest effect comes from customer order flow, which highlights the fundamental role of customer demand.

Journal of International Financial Markets, Institutions and Money, 2009

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid-ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.

Economics Letters, 1995

The conditional variance for five different hourly foreign exchange rates is modeled using a GARCH model with the number of incoming quotes as a regressor in the conditional variance equation. We find that the number of quotes is positively and significantly related to the volatility of all rates examined. The empirical findings support the conjecture of a time-consuming information process.

Journal of Banking & Finance, 2011

This paper examines the effect that heterogeneous customer orders flows have on exchange rates by using a new, and the largest, proprietary dataset of weekly net order flow segmented by customer type across nine of the most liquid currency pairs. We make several contributions. Firstly, we investigate the extent to which customer order flow can help to explain exchange rate movements over and above the influence of macroeconomic variables. Secondly, we address the issue of whether order flows contain (private) information which explain exchange rates changes. Thirdly, we look at the usefulness of order flow in forecasting exchange rate movements at longer horizons than those generally considered in the microstructure literature. Finally we address the question of whether the out-of-sample exchange rate forecasts generated by order flows can be employed profitably in the foreign exchange markets.

International Journal of Finance & Economics - INT J FINANC ECON, 2009

This study investigates information asymmetry in the foreign exchange market by testing the hypothesis that top trading banks possess superior information on the macroeconomy because they process greater order flow, which, according to the micro-structure literature, helps them aggregate the dispersed information and feel the general movements of the economy. Examining the information share of the banks in the Reuters EFX system using indicative GBP–$US data over 5 years, we find that the top 10 banks, out of 100 quoting banks in the market, have a monthly average share of over 70% of total market information, and around 80% during some US macroannouncements. These results suggest the possibility of private information over public news in the foreign exchange market. Copyright © 2009 John Wiley & Sons, Ltd.

1998

This paper investigates the impact of the frequency of general and currency-specific news headlines on de-seasonalized intraday DEM-USD exchange rate changes. We find a significant relationship between volatility and the frequency of news. In particular, more news is associated with an increase in volatility. The result that spot exchange rates are more volatile during periods for which there is a lot of economic news accords with market participants' explanations for observed volatility clustering.