double exponential moving average

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The C # Implementation of EMA computing (c # Exponential Moving Average (EMA) indicator ),

The C # Implementation of EMA computing (c # Exponential Moving Average (EMA) indicator ), Originally, the external source code (TechnicalAnalysisEngine src 1.25) internally calculates the EMA as follows: Var copyInputValues = input. ToList (); For (

C # Implementation of EMA calculation (C # exponential moving Average (EMA) indicator)

Originally a foreign source (technicalanalysisengine src 1.25) internal calculation of the EMA is:var copyinputvalues = input. ToList ();for (int i = period; I {var resultvalue = (Copyinputvalues[i]-returnvalues.last ()) * multiplier +

Research and development of high-frequency trading algorithm--moving average algorithm

Today, consider the application of the common EMA algorithm. In various trading software, we can often see MA indicator,EMA indicator and SMA indicator. First explain SMA Two semantics, if you are directly searching for SMA indicators in Baidu,

Smoothing, similarities, and differences average-macd

Smoothing, similarities, and differences average-macd Macd indicators, also known as exponential smoothing, similarities and differences, and moving averages, were created by Gerald apple, it is a technical analysis tool used to judge the stock

How to calculate the MACD in stock, what's the point?

        MACD called is developed from a double exponential moving average, with a fast exponential moving average (EMA12) minus the slow exponential moving average (EMA26) to get the fast line dif, then 2x (Fast line Dif-dif's 9th weighted moving

Python for data analysis, chapter tenth, time series

The tenth chapter of the book, "Python For Data Analysis", focuses on the processing of time series data.Label1. DateTime object, timestamp object, period object2. Two special indexes for pandas series and Dataframe object: Datetimeindex and

Ema algorithm C # implementation

Ema represents the exponential smoothing moving average, and its function is defined as Y = EMA (x, n) Then y = [2 * x + (N-1) * y']/(n + 1), where y' indicates the value of Y in the previous cycle. Calculate the n-day exponent smoothing moving

Adaptive Background Mixture Models for real-time tracking

Real-time tracking of adaptive hybrid background model Chris stauffer W. e.l grimsonbob Kuo Translation: Artificial Intelligence Laboratory of the Massachusetts Institute of Technology, Zhangye City, Ma 02139 SummaryCommon methods for real-time

Hello, C + + (9) Take the 216 bus to buy 3.5 yuan a catty of tomato--c++ how to express various numerical data 3.3 numeric data types

3.3 Numeric data typesFrom the moment we open our eyes every morning, we deal with numbers almost every hour: from 6:30 on the alarm clock to the 216 bus to work, from the news that the house price fell to 100 yuan per square meter to go home to buy

Hello, C + + (9) Take the 216 bus to buy 3.5 yuan a catty of tomato--c++ how to express various numerical data 3.3 numeric data types

3.3 Numeric data typesFrom the moment we open our eyes every morning, we deal with numbers almost every hour: from 6:30 on the alarm clock to the 216 bus to work, from the news that the house price fell to 100 yuan per square meter to go home to buy

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