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The current economic crisis has witnessed a strong deceleration in the growth of international trade. This has been even greater in the cases of the European Unionand the eurozone, where the rates of export growth have even reached negative figures. In this paper, the authors examine to which extent exchange rate volatility might account for the drop in the rate of growth of exports in the eurozone since the start of the crisis. To that end, they estimate export functions, augmented to include several measures of exchange rate volatility, for the four largest economies of the eurozone, i.e., France, Germany, Italy and Spain, for the period 1994:1–2014:4. In the empirical application, the authors make use of two alternative measures for exchange rate volatility, i.e., (i) the Standard deviation and (ii) the conditional variance from the GARCH methodology, of the change in the logarithm of the exchange rate, for both nominal and real exchange rates, and in the latter case computed using as deflators both Export prices and unit labour costs. The empirical results show no clear-cut evidence on the impact of exchange rate volatility on the exports of the countries analysed, suggesting that financial markets were developed enough so that exchange rate volatility does not hinder the evolution of exports.

Astorino, TA, Robson, T, and McMillan, DW. Classifying intensity domains from arm cycle ergometry differs versus leg cycling ergometry. J Strength Cond Res 37(11): 2192-2199, 2023--This study compared the distribution of exercise intensity domains in response to progressive leg cycle ergometry (LCE) and arm cycle ergometry (ACE). Seventeen active men and women (age and body fat 5 26 6 7 years and 18 6 3%) initially performed graded exercise on each modality to assess maximal oxygen uptake (VO2max) and peak power output (PPO). Using a randomized crossover design, they subsequently performed moderate intensity continuous exercise consisting of three 15-minute bouts at 20, 40, and 60% PPO on each modality. Gas exchange data (VO2, VCO2, and VE), respiratory exchange ratio, heart rate (HR), blood lactate concentration (BLa), and perceptual responses were acquired. Only 2 subjects were classified in the same intensity domains across modalities, with LCE eliciting more subjects exercising at "vigorous" and "near-maximal" intensities than ACE. Time spent above 70 (22 6 7 vs. 15 6 8 minutes, d 5 1.03) and 80 %HRmax (15 6 6 vs. 9 6 6 minutes, d 5 1.04) was significantly greater with LCE vs. ACE. Compared with ACE, LCE revealed significantly higher (p,0.05) peak (9466 vs. 8869 %HRmax, d50.81) and mean HR (7366 vs. 6666 %HRmax, d51.20), VO2 (5465 vs. 50 6 7 %VO2max, d 5 0.68), and BLa (5.5 6 2.0 vs. 4.7 6 1.5 mM, d 5 0.48). The results exhibit that progressive leg cycling at identical intensities elicits a greater cardiometabolic stimulus than ACE. [ABSTRACT FROM AUTHOR]

We investigate the joint ability of fundamental-based and market-based news to explain the anomalous underperformance of stocks with high idiosyncratic volatility (high IVOL). An out-of-sample prediction of future profitability is adopted as a proxy for fundamental–based news while market-based news is represented by the 52-week high price ratio. A sample of UK stocks over the period January 1996 to December 2017 is analysed. The empirical results indicate that both the fundamental-based projected profitability and the 52-week high price ratio are important in explaining the IVOL anomaly. In contrast, individually, neither variable fully accounts for the anomaly. This relation is more pronounced following a period of high sentiment and during an upmarket. Further results suggest that underreaction lies at the heart of this explanation. [ABSTRACT FROM AUTHOR]

Financial markets are expected to predict macroeconomic conditions as movement in the former depends upon expectations of future performance for the latter. However, existing evidence is mixed. We argue that this arises because the stock return and term structure series typically used in studies, fail to sufficiently capture investor risk preferences. For US data, we use the variance risk premium (VRP) and default yield (DFY) to better capture such a risk measure and demonstrate that these variables exhibit greater evidence of predictive power for key macroeconomic series. In addition to VRP and DFY, we include further variables that may also capture market risk. Given similar dynamics between different risk measures and the potential for multicollinearity in estimation, we consider variable combinations. Using results obtained through predictive regressions, out‐of‐sample forecasting and a probit model designed to capture periods of expansion and contraction, we show that these combination variables can predict future movements in macroeconomic conditions as well as results using individual variables. Of key interest, combinations that include the VRP and DFY are preferred across all macro‐series. [ABSTRACT FROM AUTHOR]