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FIS kalendarz onet 100%

PAP Kamil Stoch Po​ dob​ nie jak pod​ czas ubie​ gło​ rocz​ nej edy​ cji, in​ au​ gu​ ra​ cja Let​ nie​ go Grand Prix 2015 zo​ sta​ ła za​ pla​ no​ wa​ na na skocz​ ni im.

https://www.pdf-archive.com/2015/04/02/fis-kalendarz-onet/

02/04/2015 www.pdf-archive.com

советники для mt4 mt5 94%

Пишу под заказ советник индикаторы и скрипты для торговых платформ forex советники mt5 индикаторы форекс индикаторы форекс советник exp_slow-stoch — это торговый алгоритм, который основан на осцилляторе, а не на трендовом индикаторе, как это обычно бывает.

https://www.pdf-archive.com/2015/04/06/mt4-mt5/

06/04/2015 www.pdf-archive.com

R语言金融深度学习 89%

R语言金融深度学习 李智 Q群261821669,本篇数据下载 July 31, 2017 Chapter 1 深度学习 1.1 Deep Learning 使用R语言可以比较容易地实现深度学习(Deep Learning)。深度学习的具 体程序编写都是使用神经网络,这是利用了神经网络可以有多个层级的特 性。本篇资料使用deepnet包,当然也有其他的包可以做深度学习。深度学 习又被称作分级学习(Hierarchical Learning),是因为数据本身都是分层级 的,数据处理也必须分层级。细节请参考传统Bayesian理论。首先我们还 是使用features()函数提取数据里的特色变量。 features<-function(price,p = 14){ temp <- subset(price[,5:8]) Med <- (Hi(price) + Lo(price))/2 price <- cbind(temp, Med) adx<-ADX(price, n = p) ar<-aroon(price[ ,c(’High’, ’Low’)], n=p)[ ,’oscillator’] cci<-CCI(price[ ,2:4], n = p) chv<-chaikinVolatility(price[ ,2:4], n = p) 1 cmo<-CMO(price[ ,’Med’], n = p) macd<-MACD(price[ ,’Med’], 12, 26, 9)[ ,’macd’] osma<-macd - MACD(price[ ,’Med’],12, 26, 9)[ ,’signal’] rsi<-RSI(price[ ,’Med’], n = p) stoh<-stoch(price[ ,2:4],14, 3, 3) vol<-volatility(price[ ,1:4],n = p,calc="yang.zhang", N=96) xavg<-EMA(price[,4],n=p) trend<-price[,4]-xavg;

https://www.pdf-archive.com/2017/07/31/r/

31/07/2017 www.pdf-archive.com

intraday trading auto buy sell signal software 89%

The circle inside our trading system and also few indicators listed below namely RSI, MACD, Stoch, and ADX are known as trend watchers which will help you analyze that how other indicator are performing in the present market conditions.

https://www.pdf-archive.com/2014/12/04/intraday-trading-auto-buy-sell-signal-software/

04/12/2014 www.pdf-archive.com

Me&Economy 78%

Małgorzata Stoch:

https://www.pdf-archive.com/2014/08/05/me-economy/

05/08/2014 www.pdf-archive.com