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Sma

Directional filter VERSION 2The idea is to make it more visible if the moment is to seek buying or selling, based on moving averages, being SMA 21 and EMA 9. best BUYBAR has the EMA9 and SMA21 rising and closing above them. "relevance A" best SELLBAR has the EMA9 and SMA21 dropping and closing below them. "relevance A" Conditions for all colors of the candlesticks: BuyBar A = price closes above EMA9 and SMA21 with EMA9 and SMA21 rising. BuyBar B = price closes above SMA21 with SMA21 rising OR price closes above EMA9 and SMA21. BuyBar C = price closes above EMA9 with EMA9 rising and SMA21 falling. BuyBar Neutral = close> open. SellBar A = price closes below EMA9 and SMA21 with EMA9 and SMA21 falling. SellBar B = price closes below SMA21 with SMA21 falling OR price closes below EMA9 and SMA21. SellBar C = price closes below EMA9 with EMA9 falling and SMA21 rising. SellBar Neutral = close abertura. SellBar A = preço fecha abaixo de EMA9 e SMA21 com EMA9 e SMA21 caindo. SellBar B = preço fecha abaixo de SMA21 com SMA21 caindo OU preço fecha abaixo de EMA9 e SMA21. SellBar C = preço fecha abaixo de EMA9 com EMA9 caindo e SMA21 subindo. SellBar Neutral = fechamento < abertura. As medias moveis também alteram de acordo com a direção em que estão: EMA 9 subindo = azul EMA 9 caindo = laranja SMA 21 subindo = verde SMA21 caindo = vermelho
Pine Script™指标
由Coringa提供
1
Directional filter VERSION 2The idea is to make it more visible if the moment is to seek buying or selling, based on moving averages, being SMA 21 and EMA 9. best BUYBAR has the EMA9 and SMA21 rising and closing above them. "relevance A" best SELLBAR has the EMA9 and SMA21 dropping and closing below them. "relevance A" Conditions for all colors of the candlesticks: BuyBar A = price closes above EMA9 and SMA21 with EMA9 and SMA21 rising. BuyBar B = price closes above SMA21 with SMA21 rising OR price closes above EMA9 and SMA21. BuyBar C = price closes above EMA9 with EMA9 rising and SMA21 falling. BuyBar Neutral = close> open. SellBar A = price closes below EMA9 and SMA21 with EMA9 and SMA21 falling. SellBar B = price closes below SMA21 with SMA21 falling OR price closes below EMA9 and SMA21. SellBar C = price closes below EMA9 with EMA9 falling and SMA21 rising. SellBar Neutral = close abertura. SellBar A = preço fecha abaixo de EMA9 e SMA21 com EMA9 e SMA21 caindo. SellBar B = preço fecha abaixo de SMA21 com SMA21 caindo OU preço fecha abaixo de EMA9 e SMA21. SellBar C = preço fecha abaixo de EMA9 com EMA9 caindo e SMA21 subindo. SellBar Neutral = fechamento < abertura. As medias moveis também alteram de acordo com a direção em que estão: EMA 9 subindo = azul EMA 9 caindo = laranja SMA 21 subindo = verde SMA21 caindo = vermelho
Pine Script™指标
由Coringa提供
1
Autonomous Recursive Moving AverageIntroduction People often ask me what is my best indicators, i can't really respond to this question with a straight answer but i would say you to check this indicator. The Autonomous Recursive Moving Average (ARMA) is an adaptive moving average that try to minimize the sum of squares thanks to a ternary operator, this choice can seem surprising since most of the adaptive moving averages adapt to a smoothing variable thanks to exponential averaging, but there are lot of downsides to this method, i really wanted to have a flat filter during flat markets and this is what i achieved. The Indicator length control the amount of smoothing during trending periods, gamma is the trend sensitivity threshold, higher values of gamma will make an overall flat filter, adjust gamma to skip ranging markets. gamma = 2, we can adjust to 3 while preserving smoothing reactivity with trading periods. gamma = 3 low length and higher gamma create more boxy result, the filter add overshoots directly in the output, its unfortunate. The Zero-Lag option can reduce the lag as well as getting additional flat results without changing gamma. Conclusion The indicator need work, but i can't leave without publishing it, the overshoots are a big problems, changing sma for another stable filter can help. I hope you find an use to it, i really like this indicator. Thanks for reading
Pine Script™指标
由alexgrover提供
13
QuantNomad - MA Strategy - 1 minute - ETHUSDInteresting performance for simple MA strategy on 1m ETHUSD. I used only close price and 15 SMA in it. Performance is 55% over 10 days with a drawdown of only 3.5%. Percent profitable is only 30% with almost 2k trades. For sure this won't work as a standalone strategy, with 2k trades commission and slippage will destroy all your PNL but it can be a pretty good base for a more complicated strategy with good filters. And remember: Past performance does not guarantee future results.
Pine Script™策略
由QuantNomad提供
2
AVERAGE MULTI_SMAIndicator returns an average of 5 SMAs. an interesting point that I have noticed that the price has several times reacted on it. Note 1: Do not just use this as a criterion for buying and selling, use as one more aid. Note 2: It is possible to leave in the chart all the averages, if you feel it necessary. ------------------------------------//-------------------------------------------------- Indicador retorna uma média de 5 SMAs. um ponto interessante que tenho notado que o preço tem diversas vezes reagido nele. Observação 1: Não use apenas isso como critério para compra e venda, use como mais um auxilio. Observação 2: É possivel deixar no grafico todas as médias, caso você ache necessário.
Pine Script™指标
由Coringa提供
Smoothed Delta's Ratio OscillatorIntroduction Scaled and smoothed oscillators can provide easy to read/use information regarding price, therefore i will introduce a new oscillator who create smooth results and use a fast and practical scaling method. In order to allow for even more smoothness the option to smooth the input with a lsma has been added. Scaling Using Changes In this indicator scaling in a range of (1,-1) is achieved through the following calculations : a = sma(abs(change(src,length)),length) b = change(sma(src,length),length) c = b/a where src is our input. The two elements a and b are quite similar, a smooth the absolute change of the input over length period while b calculate the change of the smoothed input over length period, this make a > b and able us to perform scaling in a range of (1,-1). The Indicator Parameters Length control the differencing/smoothing period of the indicator, greater values create smoother and less volatile results, this mean that the oscillator will tend to be equal to 1 or -1 in a longer period of time if length is high. The smooth option allow for even smoother results by enabling the input to be smoothed by a lsma of length period. Conclusions I presented a smooth oscillator using a new rescaling technique. Parameters can be separated to provide different results, i believe the code is simple enough for everyone to modify it in order to provide interesting creations.
Pine Script™指标
由alexgrover提供
6
QMA/SMA DifferenceIntroduction The quadratic moving average (QMA) or quadratic weighted moving average (QWMA) is a type of moving average who is closer to the price when price is up trending. This moving average is defined as the square root of the moving average of the squared price. The QMA-SMA difference use this moving average to provide a new volatility indicator who aim to be reactive and filter noisy volatility in order to only provide essential information. QMA - SMA This indicator is defined as the difference between a quadratic moving average and a simple moving average of same period. Since the QMA emphasize up movements and tend to be away from down movements she is always greater than the simple moving average, so a simple difference between those moving average provide our volatility indicator. Below is a comparison with a standard deviation and the indicator of both period 100. Since its a difference between two moving average it can be interesting to use a simple moving as source for the standard deviation to provide another comparison The standard deviation is smoother but still contain more information as well as having less reactivity. Conclusion I have a presented a new volatility indicator based on the quadratic moving average and compared it with a classic standard deviation. It is possible to change the power order of the QMA in order to provide different results, in order to do so you must also change the root, this is done in pine with : pow(sma(pow(close,w),length),1/w) where w is the power order, notice that an high power order can provide non attributed values.
Pine Script™指标
由alexgrover提供
6
Dynamically Adjustable Moving AverageIntroduction The Dynamically Adjustable Moving Average (AMA) is an adaptive moving average proposed by Jacinta Chan Phooi M’ng (1) originally provided to forecast Asian Tiger's futures markets. AMA adjust to market condition in order to avoid whipsaw trades as well as entering the trending market earlier. This moving average showed better results than classical methods (SMA20, EMA20, MAC, MACD, KAMA, OptSMA) using a classical crossover/under strategy in Asian Tiger's futures from 2014 to 2015. Dynamically Adjustable Moving Average AMA adjust to market condition using a non-exponential method, which in itself is not common, AMA is described as follow : 1/v * sum(close,v) where v = σ/√σ σ is the price standard deviation. v is defined as the Efficacy Ratio (not be confounded with the Efficiency Ratio) . As you can see v determine the moving average period, you could resume the formula in pine with sma(close,v) but in pine its not possible to use the function sma with variables for length, however you can derive sma using cumulation. sma ≈ d/length where d = c - c_length and c = cum(close) So a moving average can be expressed as the difference of the cumulated price by the cumulated price length period back, this difference is then divided by length. The length period of the indicator should be short since rounded version of v tend to become less variables thus providing less adaptive results. AMA in Forex Market In 2014/2015 Major Forex currencies where more persistent than Asian Tiger's Futures (2) , also most traded currency pairs tend to have a strong long-term positive autocorrelation so AMA could have in theory provided good results if we only focus on the long term dependency. AMA has been tested with ASEAN-5 Currencies (3) and still showed good results, however forex is still a tricky market, also there is zero proof that switching to a long term moving average during ranging market avoid whipsaw trades (if you have a paper who prove it please pm me) . Conclusion An interesting indicator, however the idea behind it is far from being optimal, so far most adaptive methods tend to focus more in adapting themselves to market complexity than volatility. An interesting approach would have been to determine the validity of a signal by checking the efficacy ratio at time t . Backtesting could be a good way to see if the indicator is still performing well. References (1) J.C.P. M’ng, Dynamically adjustable moving average (AMA’) technical analysis indicator to forecast Asian Tigers’ futures markets, Physica A (2018), doi.org (2) www.researchgate.net (3) www.ncbi.nlm.nih.gov
Pine Script™指标
由alexgrover提供
15