scholarly journals Projecting the Short-Term Trend of COVID-19 in Iraq

2020 ◽  
Vol 2 (1) ◽  
pp. 1-7
Author(s):  
Murtadha Aldeer ◽  
Ahmed Al Hilli ◽  
Issam S. Ismail
Keyword(s):  
Short Term ◽  
Term Trend ◽  
Short Term Trend

scholarly journals Assessment of Seam Properties of Ahimsa Silk Union Fabrics

2019 ◽  
Vol 8 (4) ◽  
pp. 3059-3062
Keyword(s):  
Cotton Fabric ◽  
Natural Fiber ◽  
Silk Fiber ◽  
Short Term ◽  
Term Trend ◽  
The Earth ◽  
Cotton Yarns ◽  
Sustainable Fashion ◽  
Short Term Trend ◽  
Eri Silk

Sustainable fashion is not merely a short term trend but it could last many seasons and for generations to survive on the earth. Silk fiber is the most beautiful natural fiber known as the “Queen of Textiles”. Ahimsa silk is a non-violent, eco-friendly and sustainable process of the production. Hand spun and hand woven cotton fabric is another model of sustainable fabrics. Therefore, union fabrics in different ratio viz. 33:67, 50:50 and 67:33 were prepared from cotton with Ahimsa (Eri) silk and Conventional (Muga and Tussar) silk yarns. Objective of the study was to assess sewability parameters of union fabrics. These fabrics were tested for their seam puckering, seam stiffness and seam thickness parameters. The results indicate that union fabrics produced by Ahimsa silk with cotton were compatible to the union fabrics produced by Conventional silk with cotton yarns in their sewability parameters, so these should be preferred for construction of various fashion garments and textile products

A short-term trend reversed

Science ◽  
2018 ◽  
Vol 360 (6386) ◽  
pp. 280.16-282
Author(s):  
Andrew M. Sugden
Keyword(s):  
Short Term ◽  
Term Trend ◽  
Short Term Trend

scholarly journals A new set of asymmetric filters for tracking the short-term trend in real-time

2015 ◽  
Vol 9 (3) ◽  
pp. 1433-1458 ◽  
Author(s):  
Estela Bee Dagum ◽  
Silvia Bianconcini
Keyword(s):  
Real Time ◽  
Short Term ◽  
Term Trend ◽  
Short Term Trend

Short-Term Trend: A Jewel Hidden in Daily Returns

2020 ◽  
Vol 47 (1) ◽  
pp. 154-167
Author(s):  
Marat Molyboga ◽  
Larry Swedroe ◽  
Junkai Qian
Keyword(s):  
Short Term ◽  
Term Trend ◽  
Short Term Trend ◽  
Daily Returns

scholarly journals Deep LSTM with Reinforcement Learning Layer for Financial Trend Prediction in FX High Frequency Trading Systems

2019 ◽  
Vol 9 (20) ◽  
pp. 4460 ◽  
Author(s):  
Francesco Rundo
Keyword(s):  
Reinforcement Learning ◽  
High Frequency ◽  
Foreign Exchange Market ◽  
Learning Algorithm ◽  
High Frequency Trading ◽  
Short Term ◽  
Trend Prediction ◽  
Trading Systems ◽  
Term Trend ◽  
Short Term Trend

High-frequency trading is a method of intervention on the financial markets that uses sophisticated software tools, and sometimes also hardware, with which to implement high-frequency negotiations, guided by mathematical algorithms, that act on markets for shares, options, bonds, derivative instruments, commodities, and so on. HFT strategies have reached considerable volumes of commercial traffic, so much so that it is estimated that they are responsible for most of the transaction traffic of some stock exchanges, with percentages that, in some cases, exceed 70% of the total. One of the main issues of the HFT systems is the prediction of the medium-short term trend. For this reason, many algorithms have been proposed in literature. The author proposes in this work the use of an algorithm based both on supervised Deep Learning and on a Reinforcement Learning algorithm for forecasting the short-term trend in the currency FOREX (FOReign EXchange) market to maximize the return on investment in an HFT algorithm. With an average accuracy of about 85%, the proposed algorithm is able to predict the medium-short term trend of a currency cross based on the historical trend of this and by means of correlation data with other currency crosses using techniques known in the financial field with the term arbitrage. The final part of the proposed pipeline includes a grid trading engine which, based on the aforementioned trend predictions, will perform high frequency operations in order to maximize profit and minimize drawdown. The trading system has been validated over several financial years and on the EUR/USD cross confirming the high performance in terms of Return of Investment (98.23%) in addition to a reduced drawdown (15.97 %) which confirms its financial sustainability.

A short-term trend prediction model of topic over Sina Weibo dataset

2013 ◽  
Vol 28 (3) ◽  
pp. 613-625 ◽  
Author(s):  
Juanjuan Zhao ◽  
Weili Wu ◽  
Xiaolong Zhang ◽  
Yan Qiang ◽  
Tao Liu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Short Term ◽  
Trend Prediction ◽  
Sina Weibo ◽  
Term Trend ◽  
Short Term Trend
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