Order Flow and Exchange Rate Dynamics in Brazil

By O. R. D. Medeiros. 2004

222 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/42a31f24aeafe8b4bb79bf01c756963e8eb2c697

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In Economics and Econometrics

Citations in the corpus

Exchange Rate Disconnect in General Equilibrium (2017, unknown): “Alternative models of endogenous UIP deviations include models with incomplete information, expectational errors, and heterogeneous beliefs (Evans and Lyons 2002; Gourinchas and Tornell 2004; Bacchetta and van Wincoop 2006; Burnside et al. 2011), financial frictions (Adrian, Etula, and Shin 2015;…”
Liquidity provision in the overnight foreign exchange market (2005, background): “In light of the Evans and Lyons (2002) model, it is possible to interpret our results such that the typical aggressive round 1 customer is financial, while the typical liquidity providing round 3 customer is non-financial.”
Order Flow and Exchange Rate Dynamics in Electronic Brokerage System Data (2005, unknown): “Our dataset has several advantages relative to that used by Evans and Lyons (2002), and our paper offers several new contributions.”
When do central bank interventions influence intra-daily and longer-term exchange rate movements? (2006, unknown): “DeGennaro and Shrieves ( 1997 ) , Evans and Lyons ( 2002b ) and Bauwens et al .”
The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis (2007, background): “…and Taylor (2006) for a comprehensive analysis of the structure of the foreign exchange market. relating to the value of foreign exchange transactions signed according to the originator of the trade—see e.g. Ito, Lyons and Melvin, 1998; Lyons, 2001; Sarno and Taylor, 2001; Evans and Lyons, 2002).”
Limit order books (2010, methodology): “If the former could be demonstrated, it would support the widely held belief that many traders consider realized volatility to be an important factor in deciding when to place a limit order (Zovko and Farmer 2002). best prices, time of day, and recent order flows.”
Market Microstructure: A Survey of Microfoundations, Empirical Results, and Policy Implications (2005, background): “, Meese and Rogoff, 1983), Evans and Lyons (2002) find that signed order flow has significant explanatory power. In the same spirit, Chordia, Roll and Subrahmanyam (2002) find that stock market returns are affected by order imbalance. While the finding that trades have a permanent impact on prices i”
Can Oil Prices Forecast Exchange Rates (2011, unknown): “We consider a total of 32 macroeconomic announcements.15 Table 2 reports the performance of the models with macroeconomic news 14Interesting work by Evans and Lyons (2002) has shown that order ows are a good predictor for exchange rates.”
Informed and Strategic Order Flow in the Bond Markets (2006, unknown): “2, a public signal can induce price (and yield) changes through two channels that, in the spirit of Evans and Lyons (2003), we call direct (through MMs’ belief updating process) and indirect (through speculators’ trades in the order flow).”
The Long Memory of the Efficient Market (2003, unknown): “…and Bouchaud, 2002, Lillo, Farmer and Mantegna, 2003) have shown that the average market impact is a concave function of either order or transaction volume, matching other studies based on time-aggregated volume (Torre, 1997, Kempf and Korn, 1999, Plerou et al., 2001, Evans and Lyons, 2002).”
Exchange rate puzzles: A tale of switching attractors (2006, unknown): “A second approach starts from the analysis of the microstructure of the foreign exchange market (Evans and Lyons, 1999; Lyons, 2001).”
Arbitrage in the foreign exchange market: Turning on the microscope (2008, unknown): “…to international currency patterns, trading behavior, and the role of order flow in explaining exchange rate movements (e.g. Lyons, 1995, 2001; Osler, 2000, 2003, 2005; Covrig and Melvin, 2002; Evans, 2002; Evans and Lyons, 2002a,b, 2005; Payne, 2003; Bjønnes and Rime, 2005; Lyons and Moore, 2005).”
Statistical Modeling of High-Frequency Financial Data (2011, background): “Starting with Hasbrouck [37], empirical studies on public data [28, 31, 37, 42, 43, 56, 53] have investigated the relation between the direction and sizes of trades and price changes and typically conclude that the price impact of trades is an increasing, concave (“square root”) function of their si”