Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book

We employ deep learning in forecasting high-frequency returns at multiple horizons for 115 stocks traded on Nasdaq using order book information at the most granular level. While raw order book states can be used as input to the forecasting models, we achieve state-of-the-art predictive accuracy by training simpler “off-the-shelf” artificial neural networks on stationary inputs derived from the order book. Specifically, models trained on order flow significantly outperform most models trained directly on order books. Using cross-sectional regressions, we link the forecasting performance of a long short-term memory network to stock characteristics at the market microstructure level, suggesting that “information-rich” stocks can be predicted more accurately. Finally, we demonstrate that the effective horizon of stock specific forecasts is approximately two average price changes.     

Exchange rate policies in Asia in an era of financial globalisation: An empirical assessment

Ebbs and flows of capital have complicated macroeconomic policy management for all emerging market and developing economies (EMDEs) regardless of whether they have adopted flexible or managed exchange rate regimes. In the light of the renewed interest in the trilemma versus dilemma debate, we contribute to the related literature by presenting an empirical analysis of exchange rate flexibility and intervention for selected Asian EMDEs over the time period 2001–2016. In addition to estimating augmented Frankel–Wei regressions, we employ a generalised auto‐regressive conditional heteroscedasticity (GARCH) model to assess the extent of foreign exchange (FX) intervention and whether there exist any asymmetries in the way countries intervene. Our results show that although there is greater flexibility in exchange rates, there is evidence of some countries potentially using FX intervention to manage currency movements. We also find evidence of asymmetry in intervention where exchange rate volatility responds more emphatically to FX sales than purchases.     

Monetary policy, foreign exchange intervention, and the exchange rate in a unifying framework

The structural VAR model is developed to jointly analyze the effects of foreign exchange intervention and (money or interest rate setting) conventional monetary policy on the exchange rate, the two types of policy reactions to the exchange rate, and interactions between the two types of policies. First, many interactions among the two types of policies and the exchange rate are found, which suggests that a joint analysis is important. Second, foreign exchange intervention has substantial effects on the exchange rate, reacts to the exchange rate significantly (to stabilize the exchange rate), and signals future conventional monetary policy stance changes (to back up the intervention). This suggests the importance of modeling foreign exchange intervention explicitly in the study of monetary policy and exchange rate behaviors. Many other interesting results on the interactions among the two types of policies and the exchange rate are also documented.     

Arbitrage in the foreign exchange market: Turning on the microscope

This paper provides real-time evidence on the frequency, size, duration and economic significance of arbitrage opportunities in the foreign exchange market. We investigate deviations from the covered interest rate parity (CIP) condition using a unique data set for three major capital and foreign exchange markets that covers a period of more than seven months at tick frequency. The analysis unveils that: i) short-lived violations of CIP arise; ii) the size of CIP violations can be economically significant; iii) their duration is, on average, high enough to allow agents to exploit them, but low enough to explain why such opportunities have gone undetected in much previous research using data at lower frequency.