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Parisa Sarzaeim and Francisco Muñoz-Arriola
Throughout history, the pursuit of diagnosing and predicting crop yields has evidenced genetics, environment, and management practices intertwined in achieving food security. However, the sensitivity of crop phenotypes and genetic responses to climate st...
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Lingjiang Tao
With an El Niño prediction model, an advanced approach of conditional nonlinear optimal perturbation (CNOP) is used to reveal the maximum impacts of the errors occurring in initial conditions (ICs) and model parameters (MPs) on the El Niño predictions. T...
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Siyuan Liu, Qi Shao, Wei Li, Guijun Han, Kangzhuang Liang, Yantian Gong, Ru Wang, Hanyu Liu and Song Hu
Conditional nonlinear optimal perturbation (CNOP) represents the initial perturbation that satisfies a certain physical constraint condition, and leads to a maximum prediction error at the moment of prediction. The CNOP method is a useful tool in studyin...
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Ying Li and Samuel N. Stechmann
Intuitively, one would expect a more skillful forecast if predicting weather averaged over one week instead of the weather averaged over one day, and similarly for different spatial averaging areas. However, there are few systematic studies of averaging ...
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Quanhong Liu, Ren Zhang, Yangjun Wang, Hengqian Yan and Mei Hong
To meet the increasing sailing demand of the Northeast Passage of the Arctic, a daily prediction model of sea ice concentration (SIC) based on the convolutional long short-term memory network (ConvLSTM) algorithm was proposed in this study. Previously, s...
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Danielle Preziuso, Gabriel García-Medina, Rebecca O?Neil, Zhaoqing Yang and Taiping Wang
Although tidal energy conversion technologies are not yet commercially available or cost-competitive with other renewable energy technologies like wind turbines and solar panels, tides are a highly predictable resource. Tidal energy?s predictability indi...
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Klaus Gierens, Sigrun Matthes and Susanne Rohs
Persistent contrails and contrail cirrus are responsible for a large part of aviation induced radiative forcing. A considerable fraction of their warming effect could be eliminated by diverting only a quite small fraction of flight paths, namely those th...
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Henri Siro Evrard,June Alisson Westarb Cruz
Pág. 59 - 92
The present work aims to verify the efficiency of factors of return in predicting stocks? returns traded in BM&FBovespa. Have been tested 39 models, grouping 16 variables in their totality, in families and in isolation. All the models have been tested us...
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Hong-Li Ren and Pengfei Ren
The impact of Madden?Julian oscillation (MJO) upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM) index and daily precipitation data from high-resolution stations in China. The probability-distribution function ...
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Yuiko Ichikawa and Masaru Inatsu
This study proposes an alternative method to estimate the potential predictability without assuming the perfect model. A theoretical consideration relates a maximum possible value of the initial-value error to the covariance between analysis and bias-cor...
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Muhammad Iqbal,Buddi Wibowo
Pág. 335 - 348
Assorted types of market anomalies occur when stock prices deviate from the prediction of classical asset pricing theories. This study aims to examine asset growth anomaly where stocks with high asset growth will be followed by low returns in the subsequ...
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Brian A. Colle, Malcolm J. Bowman, Keith J. Roberts, M. Hamish Bowman, Charles N. Flagg, Jian Kuang, Yonghui Weng, Erin B. Munsell and Fuqing Zhang
This paper describes storm surge simulations made for Sandy (2012) for the Metropolitan New York (NYC) area using the Advanced Circulation (ADCIRC) model forced by the Weather Research and Forecasting (WRF) model. The atmospheric forecast uncertainty was...
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Stefan Strauß
This contribution explores the fine line between overestimated expectations and underrepresented momentums of uncertainty that correlate with the prevalence of big data. Big data promises a multitude of innovative options to enhance decision-making by em...
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Glener de Almeida Dourado,Benjamin Miranda Tabak
Pág. 517?553
The goal of this paper is to evaluate Brazilian stock market efficiency using daily data for the Sao Paulo Stock Exchange Index from January 1995 to December 2012. We employ a variance ratio statistic with wild bootstrap, developed to test linear depende...
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Walter Gonçalves Junior,Fábio Gallo Garcia,William Eid Junior,Luciana Ribeiro Chalela
Pág. 227 - 256
Investors constantly look for significant predictors and accurate models to forecast future results, whose occasional efficacy end up being neutralized by market efficiency. Regardless, such predictors are widely used for seeking better (and more unique...
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Regis Augusto Ely
Pág. 571 - 584
This paper searches for evidence of predictability in the Brazilian stock market using portfolios grouped by sector and firm size with data from 1999 to 2008. I conduct an automatic variance ratio test using wild bootstrap. This methodology eliminates th...
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Luciano Martin Rostagno,Gilberto de Oliveira Kloeckner,João Luiz Becker
Pág. pp. 183 - 206
This paper examines the hypothesis of asst return predictability in the Brazilian Stock Market (Bovespa). Evidence suggests that seven factors explain most of the monthly differential returns of the stocks included in the sample. Within the factors that ...
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Yanling Wu and Xiaoqin Yan
In this study, we investigate the changes in the multiyear predictability of the Pacific decadal oscillation (PDO) since 1900. A newly developed method, the model-analog method, is used to hindcast the PDO from 1900 to 2015. Model-analog hindcast provide...
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Eike Jakubowitz, Thekla Feist, Alina Obermeier, Carina Gempfer, Christof Hurschler, Henning Windhagen and Max-Heinrich Laves
Human grasping is a relatively fast process and control signals for upper limb prosthetics cannot be generated and processed in a sufficiently timely manner. The aim of this study was to examine whether discriminating between different grasping movements...
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Chul-Gyum Kim, Jeongwoo Lee, Jeong Eun Lee and Hyeonjun Kim
This study examines the long-term climate predictability in the Seomjin River basin using statistical methods, and explores the effects of incorporating the duration of climate indices as predictors. A multiple linear regression model is employed, utiliz...
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