Robust model rankings of forecasting performance

This paper investigates robust model rankings in out‐of‐sample, short‐horizon forecasting. We provide strong evidence that rolling window averaging consistently produces robust model rankings while improving the forecasting performance of both individual models and model averaging. The rolling window averaging outperforms the (ex post) “optimal” window forecasts in more than 50% of the times across all rolling windows.     

Exchange rate forecasting and the performance of currency portfolios

We examine the potential gains of using exchange rate forecast models and forecast combination methods in the management of currency portfolios for three exchange rates: the euro versus the US dollar, the British pound, and the Japanese yen. We use a battery of econometric specifications to evaluate whether optimal currency portfolios implied by trading strategies based on exchange rate forecasts outperform single currencies and the equally weighted portfolio. We assess the differences in profitability of optimal currency portfolios for different types of investor preferences, two trading strategies, mean squared error‐based composite forecasts, and different forecast horizons. Our results indicate that there are clear benefits of integrating exchange rate forecasts from state‐of‐the‐art econometric models in currency portfolios. These benefits vary across investor preferences and prediction horizons but are rather similar across trading strategies.     

Google Trends and the forecasting performance of exchange rate models

In this paper, we use Google Trends data for exchange rate forecasting in the context of a broad literature review that ties the exchange rate movements with macroeconomic fundamentals. The sample covers 11 OECD countries’ exchange rates for the period from January 2004 to June 2014. In out‐of‐sample forecasting of monthly returns on exchange rates, our findings indicate that the Google Trends search query data do a better job than the structural models in predicting the true direction of changes in nominal exchange rates. We also observed that Google Trends‐based forecasts are better at picking up the direction of the changes in the monthly nominal exchange rates after the Great Recession era (2008–2009). Based on the Clark and West inference procedure of equal predictive accuracy testing, we found that the relative performance of Google Trends‐based exchange rate predictions against the null of a random walk model is no worse than the purchasing power parity model. On the other hand, although the monetary model fundamentals could beat the random walk null only in one out of 11 currency pairs, with Google Trends predictors we found evidence of better performance for five currency pairs. We believe that these findings necessitate further research in this area to investigate the extravalue one can get from Google search query data.     

Recent results on hydrogen and hydration in biology studied by neutron macromolecular crystallography

Neutron diffraction provides an experimental method of directly locating hydrogen atoms in proteins, a technique complimentary to ultra-high-resolution [1, 2] X-ray diffraction. Three different types of neutron diffractometers for biological macromolecules have been constructed in Japan, France and the United States, and they have been used to determine the crystal structures of proteins up to resolution limits of 1.5-2.5 A. Results relating to hydrogen positions and hydration patterns in proteins have been obtained from these studies. Examples include the geometrical details of hydrogen bonds, H/D exchange in proteins and oligonucleotides, the role of hydrogen atoms in enzymatic activity and thermostability, and the dynamical behavior of hydration structures, all of which have been extracted from these structural results and reviewed. Other techniques, such as the growth of large single crystals, the preparation of fully deuterated proteins, the use of cryogenic techniques, and a data base of hydrogen and hydration in proteins, will be described.     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

泡沫铝／环氧树脂复合材料压缩力学行为的仿真分析

根据所制备的开孔泡沫铝／环氧树脂复舍材料的结构特点,对其材料结构进行了合理的简化。在此基础上采用ANSYS／KS—DYNA软件对该材料的压缩力学行为进行有限元仿真分析;得出了该材料在压缩过程中的变形和失效过程以及应力-应变关系随其结构参数（泡沫铝孔径、泡沫铝相等密度）及应变率的变化规律。如上规律与已有文献的物理实验研究结果相一致,从而证明了该仿真方法的合理可行性,为泡沫铝孔洞填充复合材料的性能研究提供了一种新方法。     

层状Lix[Mn1-yCoy]O2正极材料的合成及电化学性能研究

采用柠檬酸溶胶凝胶法合成了钠锰青铜Nax[Mn1-yCoy]O2,其中Nax[Mn1-yCoy]O2(0.3≤y≤0.5)具有理想的层状P2结构;以P2结构的Nax[Mn1-yCoy]O2为前驱体,离子交换后得到O2结构产物Lix[Mn1-yCoy]O2,并进行了XRD,ICP和电化学性能研究,结果表明不同Mn/Co投料比对前驱体中Nax[Mn1-yCoy]O2的结构有较大的影响,并且不同的离子交换方法对产物Lix[Mn1-yCoy]O2的结构和组成有较大的影响。对Li0.9Mn0.7Co0.3O2在充放电电压为2.6-4.5V(vs.Li /Li),电流密度为0.2mA/cm2的充放电条件下进行电化学测试后发现,该材料的首次充放电容量达152.70mAh/g,且循环性能良好。     

大孔树脂纯化复方中总苷类成分的吸附特征

研究D-101大孔树脂分离纯化金匮肾气丸中总苷类成分的工艺条件及参数.以马钱苷、芍药苷、总苷和总皂苷的质量分数为指标,比较四种大孔树脂对金匮肾气丸苷类成分的吸附性能,筛选出效果较好的D-101大孔树脂.通过对树脂的漏点质量浓度、吸附动力学曲线、药液pH值对树脂吸附的影响,以及对洗脱剂质量浓度、用量、pH值的考察,筛选出最佳的吸附洗脱工艺.D-101大孔树脂能有效地吸附和解吸金匮肾气丸中的苷类成分,最佳的吸附工艺参数苷类样品液质量浓度0.25 g/mL,药液的pH值6,吸附时间为8 h.以pH=8的70%乙醇为洗脱液,洗脱体积为30BV.树脂可重复利用2次.终产品中总苷的质量分数达43.87%,总皂苷的质量分数为4.93%.用大孔树脂对金匮肾气丸中总苷成分类进行纯化是可行的.     

离子强度对牛磺酸离子交换平衡的影响

采用静态吸附法研究离子强度对牛磺酸/OH-体系在阴离子树脂D290上离子交换平衡的影响,测定了不同离子强度下牛磺酸在碱式阴离子交换树脂上的交换平衡等温线.研究结果表明:(1)随着溶液离子强度的升高,阴离子树脂对牛磺酸的平衡交换吸附容量逐渐降低,牛磺酸在树脂上的分配系数λTau逐渐下降;(2)随着溶液离子强度增大,达到平衡时液相的pH值升高,溶液中牛磺酸阴离子Tau±含量迅速增加,而牛磺酸两性离子Tau±含量迅速降低;(3)在一定的牛磺酸浓度范围内,溶液离子强度增大,有利于提高离子交换树脂对牛磺酸的选择性.     

废玻璃-粉煤灰制备树脂混凝土的试验研究

将废玻璃破碎人工级配作集料、粉煤灰作填料、碳纤维作增强材料与环氧树脂胶粘剂结合,成功配制出7 d抗压强度达到51.23 MPa、抗折强度达到21.68 MPa的树脂混凝土.采用均匀试验设计安排试验方案,利用SPSS技术处理试验数据并建立强度回归方程,用MATLAB技术得到树脂混凝土的配合比优化范围.该项目吃＂渣＂大,废玻璃、粉煤灰取代天然砂石占树脂混凝土总质量88%以上,研究成果对固体废弃物的治理有重要的现实意义.