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MovingAveragesLibraryLibrary "MovingAveragesLibrary" This is a library allowing one to select between many different Moving Average formulas to smooth out any float variable. You can use this library to apply a Moving Average function to any series of data as long as your source is a float. The default application would be for applying Moving Averages onto your chart. However, the scope of this library is beyond that. Any indicator or strategy you are building can benefit from this library. You can apply different types of smoothing and moving average functions to your indicators, momentum oscillators, average true range calculations, support and resistance zones, envelope bands, channels, and anything you can think of to attempt to smooth out noise while finding a delicate balance against lag. If you are developing an indicator, you can use the 'ave_func' to allow your users to select any Moving Average for any function or variable by creating an input string with the following structure: var_name = input.string(, , ) Where the types of Moving Average you would like to be provided would be included in options. Example: i_ma_type = input.string(title = "Moving Average Type", defval = "Hull Moving Average", options = ) Where you would add after options the strings I have included for you at the top of the PineScript for your convenience. Then for the output you desire, simply call 'ave_func' like so: ma = ave_func(source, length, i_ma_type) Now the plotted Moving Average will be the same as what you or your users select from the Input. ema(src, len) Exponential Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. sma(src, len) Simple Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. rma(src, len) Relative Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. wma(src, len) Weighted Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. dv2(len) Donchian V2 function.   Parameters:      len : Lookback length to use.   Returns: Open + Close / 2 for the selected length. ModFilt(src, len) Modular Filter smoothing function.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. EDSMA(src, len) Ehlers Dynamic Smoothed Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: EDSMA smoothing. dema(x, t) Double Exponential Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: DEMA smoothing. tema(src, len) Triple Exponential Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: TEMA smoothing. smma(x, t) Smoothed Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: SMMA smoothing. vwma(x, t) Volume Weighted Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: VWMA smoothing. hullma(x, t) Hull Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: Hull smoothing. covwma(x, t) Coefficient of Variation Weighted Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: COVWMA smoothing. frama(x, t) Fractal Reactive Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: FRAMA smoothing. kama(x, t) Kaufman's Adaptive Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: KAMA smoothing. donchian(len) Donchian Calculation.   Parameters:      len : Lookback length to use.   Returns: Average of the highest price and the lowest price for the specified look-back period. tma(src, len) Triangular Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: TMA smoothing. VAMA(src, len) Volatility Adjusted Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: VAMA smoothing. Jurik(src, len) Jurik Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: JMA smoothing. MCG(src, len) McGinley smoothing.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: McGinley smoothing. zlema(series, length) Zero Lag Exponential Moving Average.   Parameters:      series : Series to use ('close' is used if no argument is supplied).      length : Lookback length to use.   Returns: ZLEMA smoothing. xema(src, len) Optimized Exponential Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: XEMA smoothing. EhlersSuperSmoother(src, lower) Ehlers Super Smoother.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      lower : Smoothing value to use.   Returns: Ehlers Super smoothing. EhlersEmaSmoother(sig, smoothK, smoothP) Ehlers EMA Smoother.   Parameters:      sig : Series to use ('close' is used if no argument is supplied).      smoothK : Lookback length to use.      smoothP : Smothing value to use.   Returns: Ehlers EMA smoothing. ave_func(in_src, in_len, in_type) Returns the source after running it through a Moving Average function.   Parameters:      in_src : Series to use ('close' is used if no argument is supplied).      in_len : Lookback period to be used for the Moving Average function.      in_type : Type of Moving Average function to use. Must have a string input to select the options from that MUST match the type-casing in the function below.   Returns: The source as a float after running it through the Moving Average function.
Perpustakaan Pine Script™
oleh CrackingCryptocurrency
7
[blackcat] L2 Zero-lag EMA Swing TradeLevel: 2 Background This script is a comprehensive work of mine, incorporating Ehlers zero-lag EMA and my first script published: MA fingerprint for long entries. Function Ehlers zero-lag EMA algorithm in this scripts is mainly used for short signal production, while my MA fingerprint algorithm is used for long entries. Key Signal a ---> Ehlers Zero-lag EMA fast line for subjective long jugement b ---> Ehlers Zero-lag EMA slow line for subjective short jugement long --> Swing long entry with partial postion short --> Swing short entry with partial postion Remarks Feedbacks are appreciated. This script is optimized for 1D time frame. Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Penunjuk Pine Script™
oleh blackcat1402
6
AM_ZLWMA Crossover_xDear All, Please find updated version of Zero lag WMA crossover. In addition to this added 20/50 EMA to get better results. Settings: ZLWMA = 8 identified by Blue line Fast WMA = 21 identified by Red line EMA Period 20/50 How to Trade: Buy: Wait for positive crossover (Blue cross above Red) to happen trade can be taken there but to get better results post crossover once price move above EMA 20 then buy can be initiated. Sell: Wait for negative crossover (Blue cross below Red) to happen trade can be taken there but to get better results post crossover once price move below EMA 20 then sell can be initiated. Reason to wait for confirmation of price action above / Below moving average is most of the time it happens that even after crossover happens sometimes it was just a pull back and from there it could be a possibility for reversal. Once price action confirms moving above / below EMA20 then trade will be initiated. Please comment and ask for any doubt
Strategi Pine Script™
oleh happyTacos
3
TA Basics: Creating a Zero Lag Moving Average using "Mirroring"we all know how moving averages suffer from lag - they have a delayed response to change in the underlying values - regardless if the underlying values are price movement or some kind of indicator formula that we are trying to smooth using a moving average. here's a simple technique that can help minimize the lag built into the moving average - you can use this technique while building your own indicator (say modifying RSI) or simply apply it to a price chart to generate some sort of signal. the concept here is simple and it actually depends on the fact that there's lag in moving averages - however, it was also observed that this lag is less when we use a weighted moving average (WMA) vs a simple moving average (SMA). (for a quick intro / refresher on Moving Averages, there's an awesome write-up here on TradingView that you can easily find with a quick search) so the idea is to take the delta between these 2 lines (which is mathematically equal to SMA - WMA) , and "mirror it" on the other side of the WMA to produce the new Zero-lag line (let's call it ZLMA. sounds easy, right? now, expanding on this concept just one step further, while we're at it, why don't we take, say, 1.5 times that delta, or 2 times and mirror it - wouldn't that produce an even less lagging line that moves in lockstep with the price (or whatever data series)? -- yes it would, we added that in the sample code here, but be careful with that, if you increase that factor too much, the ZLMA starts behaving "wildly" and loses relevance to the underlying data. so keep it from 1 to 2.5 -- an ideal value would be around the 1.5 (and of course, for the mathematically gifted, as you expect, you make that factor -1.0, and you end up with a ZLMA that is exactly same as the SMA :) .. if you don't use a ZLMA factor "f" -- then the simple equation is ZLMA = 2W - S, which you can simply add to any indicator to smoother it without introducing a lot of lag -- however, i still suggest you keep that smoothing to a small value between 3 and 6 -- to stay relevant to underlying data hope you like this and find it useful. let me know -- i'd like to know if there's interest in these types of concepts and there's more to come. pls stay safe,
Penunjuk Pine Script™
oleh RedKTrader
2