a b s t r a c tThis paper adds to the research efforts that aim to bridge the divide between macro and micro approaches to exchange rate economics by examining the linkages between exchange rate movements, order flow and expectations of macroeconomic variables. The basic hypothesis tested is that if order flow reflects heterogeneous expectations about macroeconomic fundamentals, and currency markets learn about the state of the economy gradually, then order flow can have both explanatory and forecasting power for exchange rates.Using one year of high frequency data collected via a live feed from Reuters for three major exchange rates, we find that: i) order flow is intimately related to a broad set of current and expected macroeconomic fundamentals; ii) more importantly, order flow is a powerful predictor of daily movements in exchange rates in an out-of-sample exercise, on the basis of economic value criteria such as Sharpe ratios and performance fees implied by utility calculations.

No abstract

This paper investigates the empirical relation between order flow and macroeconomic information in the foreign exchange market, and the ability of microstructure models based on order flow to outperform a naïve random walk benchmark. If order flow reflects heterogeneous beliefs about macroeconomic fundamentals, and currency markets learn about the state of the economy gradually, then order flow can have both explanatory and forecasting power for exchange rates. Using one year of high frequency data for three major exchange rates, we demonstrate that order flow is intimately related to a broad set of current and expected macroeconomic fundamentals. More importantly, we find that order flow is a powerful predictor of daily movements in exchange rates in an out-of-sample exercise. The Sharpe ratio obtained from allocating funds using forecasts generated by an order flow model is generally above unity and substantially higher than the Sharpe ratios obtained from alternative models, including the random walk model.

Social distancing, self-isolation, quarantining, and lockdowns arising from the COVID-19 pandemic have been common restrictions as governments have attempted to limit the rapid virus transmission. In this study, we identified drivers of adverse mental and behavioral health during the COVID-19 pandemic and whether factors such as social isolation and various restrictions serve as additional stressors for different age groups. Univariate and multivariate regression analyses were conducted on a unique dataset based on a national probability-based survey dedicated to understanding the impact of COVID-19 in the U.S., which includes 19 questions on the individual impact of restrictions, bans, and closures. The analysis used a moderate distress scale built on five questions related to mental health for 3,646 respondents. The mental health of young adults (18−34 years old) was the most affected by restrictions, while that of older adults (>55 years old) was less affected. In addition, demographic and health characteristics associated with differences in mental health varied by age group. The findings in this analysis highlight the differential mental health needs of different age groups and point to the marked necessity for differentiated and targeted responses to the mental health effects of COVID-19 by age group.

Recent research demonstrates that the well-documented feeble link between exchange rates and economic fundamentals can be reconciled with conventional exchange rate theories under the assumption that the discount factor is near unity (Engel and West 2005). We provide empirical evidence that this assumption is valid, lending further support to the above explanation of the empirical disconnect between nominal exchange rates and fundamentals. Copyright (c) 2009 The Ohio State University.