Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System(PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the IntegratedMultisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained

Deep Learning for Forecasting Stock Returns in the Cross-Section

Many studies have been undertaken by using machine learning techniques, including neural networks, to predict stock returns. Recently, a method known as deep learning, which achieves high performance mainly in image recognition and speech recognition, has attracted attention in the machine learning field. This paper implements deep learning to predict one-month-ahead stock returns in the cross-section in the Japanese stock market and investigates the performance of the method. Our results show that deep neural networks generally outperform shallow neural networks, and the best networks also outperform representative machine learning models. These results indicate that deep learning shows promise as a skillful machine learning method to predict stock returns in the cross-section.Comment: 12 pages, 2 figures, 8 tables, accepted at PAKDD 201

Individual patient data meta-analysis of randomized controlled trials of community occupational therapy for stroke patients

<p><b>Background and Purpose:</b> Trials of occupational therapy for stroke patients living in the community have varied in their findings. It is unclear why these discrepancies have occurred.</p> <p><b>Methods:</b> Trials were identified from searches of the Cochrane Library and other sources. The primary outcome measure was the Nottingham Extended Activities of Daily Living (NEADL) score at the end of intervention. Secondary outcome measures included the Barthel Index or the Rivermead ADL (Personal ADL), General Health Questionnaire (GHQ), Nottingham Leisure Questionnaire (NLQ), and death. Data were analyzed using linear or logistic regression with a random effect for trial and adjustment for age, gender, baseline dependency, and method of follow-up. Subgroup analyses compared any occupational therapy intervention with control.</p> <p><b>Results:</b> We included 8 single-blind randomized controlled trials incorporating 1143 patients. Occupational therapy was associated with higher NEADL scores at the end of intervention (weighted mean difference [WMD], 1.30 points, 95% confidence intervals [CI], 0.47 to 2.13) and higher leisure scores at the end of intervention (WMD, 1.51 points; 95% CI, 0.24 to 2.79). Occupational therapy emphasizing activities of daily living (ADL) was associated with improved end of intervention NEADL (WMD, 1.61 points; 95% CI, 0.72 to 2.49) and personal activities of daily living (odds ratio [OR], 0.65; 95% CI, 0.46 to 0.91), but not NLQ. Leisure-based occupational therapy improved end of intervention NLQ (WMD, 1.96 points; 95% CI, 0.27 to 3.66) but not NEADL or PADL.</p> <p><b>Conclusions:</b> Community occupational therapy significantly improved personal and extended activities of daily living and leisure activity in patients with stroke. Better outcomes were found with targeted interventions.</p&gt

Economic Integration in East Asia: Trends, Prospects, and a Possible Roadmap

This paper, which is a revised version of the ADB Working Paper on Regional Economic Integration No. 2, reviews trends in East Asian regionalism in the areas of trade and investment, money and finance, and infrastructure. It finds that trade and, to a lesser extent, financial integration is starting to increase in the region. It also finds that business cycles are starting to be more synchronized, enhancing the case for further monetary integration among these countries. The paper also outlines a roadmap for East Asian integration.

Economic Integration in East Asia: Trends, Prospects, and a Possible Roadmap

This paper reviews trends in East Asian regionalism in the areas of trade and investment, money and finance, and infrastructure. It presents various measures of trade and financial integration. An important finding of the paper is that increasing trade and financial integration in the region is now starting to lead to a synchronization of business cycles in a selected group of countries, further enhancing the case for monetary integration among these countries. The paper also outlines a roadmap for East Asian integration.ASEAN/East Asian economic cooperation and integration; business cycle synchronization; free trade agreements; policy coordination

International Stock Return Comovements

We examine international stock return comovements using country-industry and country-style portfolios. We first establish that parsimonious risk-based factor models capture the covariance structure of the data better than the popular Heston-Rouwenhorst (1994) model. We then establish the following stylized facts regarding stock return comovements. First, we do not find evidence for an upward trend in return correlations, excpet for the European stock markets. Second, the increasing imporatnce of industry factors relative to country factors was a short-lived, temporary phenomenon. Third, we find no evidence for a trend in idiosyncratic risk in any of the countries we examine.

Geographical versus Industrial Diversification: A Mean Variance Spanning Approach

This paper addresses whether country allocation provides benefits over industry allocation in a sample of European country and industry indexes. Strategy performance is compared using a mean-variance spanning test. We find that, for investors with low risk aversion, industry allocation is as good as investing in the complete set of assets. Moreover, in the most recent subperiod coinciding with the inception of the Euro, country and industry diversification are both effective. By contrast, investors with high risk aversion should always mix country and industry portfolios. A striking aspect of our analysis is that we do not find empirical evidence to support the argument that country diversification is a superior approach.Diversification gains, EMU, mean-variance spanning, portfolio allocation strategies