Cracking Cryptocurrency - Exponential Moving AveragesCracking Cryptocurrency - Exponential Moving Averages
This is the preferred EMA Indicator of Cracking Cryptocurrency Traders. We have based our statistical levels of support and resistance , trend, and momentum utilizing Fibonacci Numbers for our EMA inputs.
This script utilizes the Key Numbers of 8, 13, 21, 55, 100, and 200 as we have found those to work the best for Bitcoin and other Cryptocurrencies.
Features and Functions
Multi-Time Frame Function
Multiple Source Rendering
Multiple Smoothing Options
Adjust Look back Length
Plot Custom Signals
Multiple Time Frame Feature
Do you want to watch the EMA's of a higher or lower time frame while analyzing the price action of a different time frame? With this indicator, it's quite easy! Just select the desired Time Frame to display your EMA's and they will automatically change without affecting the price action you're currently looking at, or having to change your Time Frame Resolution. This has been upgraded and simplified with a drop-down menu for selecting your desired Time Frame.
Plot Crossovers
Want to keep it simple? Select Plot Crossovers and this script will display optimum times to buy and sell based on Trending Momentum utilizing your selected EMA crosses. Highly effective, back-test it and see!
Hull Moving Average (HMA)
TSI CCI Hull with profit$$$This is a modified version of @SeaSide420 TSI CCI Hull with profits exit on long and short order
ORIGINAL SCRIPT:
/// /// feel free to edit/improve and comment
Hull Suite StrategyConverted the hull suite into a strategy script for easy backtesting and added ability to specify a time periods to backtest over.
1337 StrategyThis is a WIP strategy based on the 1337 Oscillator. It seems to catch some of the nice trending moves on the 1H but needs work to filter the choppy signals after a move and during consolidation.
VolHMA [sluggishmoney]Currently published volume scripts typically plot volume as a positive value. This one is different.
---WHAT IS IT---
If the close is greater than the open, the volume is considered positive, and if the close is less than the open, the volume is made negative. I have taken the HMA (Hull Moving Average) of this positive or negative volume with a default length of 100, and have plotted it as a histogram that is green if positive, and red if negative. The signal line is an SMA of this volume HMA with a default length of 10. The purple background is a suggested holding period for a potential long position.
---HOW TO USE IT---
When the HMA100 crosses above 0, this is considered a buy signal. This means that the smoothed volume is starting to become bullish (but delayed due to length of moving averages). When the HMA100 crosses under the signal, this is considered a sell signal.
---WHICH MARKETS---
I wrote this script specifically for cryptocurrency markets. The indicator does best with continuous volume data that's typically found in crypto markets, although I can picture this working well in FOREX as well. A volatile and continuous market can provide volume data that best captures the magnitude and direction of a move.
OneGreenCandle - Hull Keltner Channel
The Keltner Channel, a classic indicator of technical analysis developed by Chester Keltner in 1960.
The indicator is a bit like Bollinger Bands and Envelopes.
This variation uses the Hull Moving Average as the centre line for the channel.
Squeeze Momentum Indicator [LazyBear] vHMAThis is a remake of the famous LazyBear Indicator, the Squeeze Momentum Indicator.
All i did was take out the SMA's and replace them with HMA's. HMA is a more responsive moving average.
Hull Moving Average.
This is a derivative of John Carter's "TTM Squeeze" volatility indicator, as discussed in his book "Mastering the Trade" (chapter 11).
Black crosses on the midline show that the market just entered a squeeze ( Bollinger Bands are with in Keltner Channel). This signifies low volatility , market preparing itself for an explosive move (up or down). Gray crosses signify "Squeeze release".
Mr.Carter suggests waiting till the first gray after a black cross, and taking a position in the direction of the momentum (for ex., if momentum value is above zero, go long). Exit the position when the momentum changes (increase or decrease --- signified by a color change). My (limited) experience with this shows, an additional indicator like ADX / WaveTrend, is needed to not miss good entry points. Also, Mr.Carter uses simple momentum indicator , while I have used a different method (linreg based) to plot the histogram.
More info:
- Book: Mastering The Trade by John F Carter
Here is the original version:
TSI CCI HullThis Strategy is Using TSI and CCI and Hull Moving Average to make swing trades on 1H chart but can be used on any pair and timeframe just change settings to suit (Hull Period mostly)
Open Close Profit - [Alerts]This script comes with the following indicators and features:
Moving Average trend filter (Hull, ZLEMA, McGinley)
Pin Bar Filter
MACD indicator
Pump and Dump filter
Entry, Take Profit, and Stop Loss Alerts
And a few more indicators in the back-end to increase accuracy, optimize entries and filter out sideways PA
This script works really well as a scalper on lower Time Frames as well as on higher Time Frames. Besides that you can also use it on pretty much any coin or asset.
This script is not repainting. We advise to use alerts on “Once Per Bar Close”.
If you’d like to automate this script you can do that by using AutoView, ProfitView, ProfitTrailer, CryptoHopper etc.
Leave a message if you’d like to try it out.
The V_Wave: Volatility Adaptive Moving AverageThis is work in progress - but i wanted to see if there's interest to use or test it - or if someone finds it useful. there's already a crowd of great moving averages out there :)
This is a different type of zero-lag weighted moving average - and it's a concept that i have been working on for a while now. Given that this is WIP, i decided to keep the code protected for now.
The idea is to create a moving average that responds faster to the changes in the underlying data - which is the case with other zero-lag moving averages - but in this case, i also wanted to make it adaptive, so it accelerate when the volatility increases and at the same time, maintain limited lag and reasonable smoothing, even at longer length.
How Does it Compare to other MA's
==============================
in the chart, we can see a comparison between the V_Wave (thick yellow line) and the 3 common MAs, Hull Moving Average (HMA, aqua), a Weighted Moving Average (WMA, brown) and an Exponential Moving Average (EMA, grey)
the most important advantage in V_Wave, is because of the way the algorithm works, and that it maintains direct association with the underlying data and the given length, the V_Wave will have less overshoot when compared to other moving averages - i.e, it stays closer to the underlying data points at times of quick reversals or big changes - like the V reversal on the right of the chart. You can also test it against other MAs you may be already using and share your findings back with me.
settings:
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- the settings provide the ability to choose the source data (close vs hl2, ..etc), the length, and the ability to adjust the "aggressiveness" of the line (Accelerator) ..
- this accelerator is the factor that tells the V_Wave how fast to respond to the volatility changes. when you increase the accelerator, the V_Wave is more aggressive, and will respond faster to changes in volatility -- it becomes more responsive to changes in the trend, but that will sacrifice the smoothness of the line.
- i capped this value to 7, because beyond that, the accelerator will have a diminished effect.
- Also note that due to association with volatility, the V_Wave will behave differently at lower time frames -- and becomes closer to an EMA but better (in responsiveness) than a WMA.
- the smoothing is built-in for now, and will adjust based on the length, in a way similar to how HMA smoothing works (see my previous post on Evolving the Zero Lag MA for details on that) - in future versions, i may make it a manual entry or a selection between manual/automatic
Usage:
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Use the V_Wave as you use other moving averages - once you get to know how it behaves and adapts to underlying data changes.
you can use it as a filter to generate signals once it crosses other MAs, or another V_Wave of a different length / acceleration.
will be great if you share your test results and your use cases to help me improve how the V_Wave works.
best of luck!
Hull Moving Average Swing Trader (Alerts)Hull Moving Average Strategy (Study version for ALERTS)
2 X HMA's,
1st HMA on current price (recommended source OPEN)
2nd HMA on previous candle. signal on crossover.
Buy and Sell signals on chart, red & green view pane (Green Buy, Red Sell) (RED & GREEN DOTS)
Hull Moving Average Swing TraderHull Moving Average Strategy
2 X HMA's,
1st HMA on current price (recommended source OPEN)
2nd HMA on previous candle. signal on crossover.
Buy and Sell signals on chart, red & green view pane (Green Buy, Red Sell)
Hull MA and rate of changeUse of hull moving average and rate of change to get buy and sell signals.
Feedback is most welcomed.
HMA-Crossover AlertsThis simple script plots bullish and bearish Hull Moving Average Crossovers and fires Alerts when long or short conditions are met.
Smooth HA / Hull MA / MTF===========
Smooth HA / Hull MA / MTF
===========
A combination of a Smoothed Heikin Ashi Chart Line and a Hull MA Line, paints a "Long" or "Short" alert when the Hull MA changes color - editable settings for the smoothing of HA data and Hull MA Length; you can also change the time frame used (must be the same or longer as the chart).
-----------
This indicator does a real good job at finding highs and lows (otherwise known as entry and exit points!) picking up on just about every large, decent swing and making the most from those big moves! The disadvantage of all Smoothed HA strategies are when times are choppy or ranging - given the natural lag of the indicator you can be sure in choppy times you'd be buying at the top and selling at the bottom almost every time ~ No indicator is perfect!
This Smooth HA/Hull MA indicator also has a built in MTF function (Multi-Time-Frame). This means you can be using a 1hr chart and set the indicator to a 4hr chart - generally any movements on a greater time frame will overcome any movements of the smaller time frame, so this is where you should be gathering data about which direction the market is moving - as always, follow the trend.
Hope (like always) this is of at least some use to some people.
Good Luck and Happy Trading!
Hull Strategy [Bitduke]Description
The Hull Moving Average (HMA) was developed by Alan Hull for the purpose of reducing lag, increasing responsiveness while at the same time eliminating noise. Its calculation is elaborate and makes use of the Weighted Moving Average (WMA).
It uses two lagged hull moving averages at the intersection of which a change in trend is determined.
Risk Management
Risk is managed by limiting the loss per trade (in%) using stop loss variable.
Improvements
Can be improved by experiments with stop loss and take profit.
Backtesting
Bitmex XBTUSD
Timeframe 3H
Stop 2%, take profit : n/a
193.5% profit
22.42% drawdown
FTX BTC-PERP
Timeframe 3H
Stop 2%, take profit : n/a
187.5% profit
14.79% (!) drawdown
FTX SHIT-PERP
Timeframe 3H
Stop 2%, take profit : n/a
112.5% profit
13.79% (!) drawdown
RSI and Smoothed RSI Bull Div Strategy [BigBitsIO]This strategy focuses on finding a low RSI value, then targeting a low Smoothed RSI value while the price is below the low RSI in the lookback period to trigger a buy signal.
Features Take Profit, Stop Loss, and Plot Target inputs. As well as many inputs to manage how the RSI and Smoothed RSI are configured within the strategy.
Explanation of all the inputs
Take Profit %: % change in price from position entry where strategy takes profit
Stop Loss %: % change in price from position entry where strategy stops losses
RSI Lookback Period: # of candles used to calculate RSI
Buy Below Lowest Low In RSI Divergence Lookback Target %: % change in price from lowest RSI candle in divergence lookback if set
Source of Buy Below Target Price: Source of price (close, open, high, low, etc..) used to calculated buy below %
Smoothed RSI Lookback Period: # of candles used to calculate RSI
RSI Currently Below: Value the current RSI must be below to trigger a buy
RSI Divergence Lookback Period: # of candles used to lookback for lowest RSI in the divergence lookback period
RSI Lowest In Divergence Lookback Currently Below: Require the lowest RSI in the divergence lookback to be below this value
RSI Sell Above: If take profit or stop loss is not hit, the position will sell when RSI rises above this value
Minimum SRSI Downtrend Length: Require that the downtrend length of the SRSI be this value or higher to trigger a buy
Smoothed RSI Currently Below: Value the current SRSI must be below to trigger a buy
Hull Signal and Auto Fib 30 secThis script will not be given away for free. Been months of developing and the effort is paying off.
The code uses a 40 HULL MA on the 30 second chart to identify up/down changes in trend. It ensures the equity is positive on the day to go long, or negative on the day to go short.
It draws the stop and fib lines according to the current 3 min ATR over the last 4 periods (12 minutes) : x1 x2 x3 x4 x6
Candles are highlighted upon entries. Grid begins.
Code resets upon one of the following:
- 4x target achieved and the trade has been active for 30 minutes
- 6x target achieved
- Stop hits
- 30 minutes have lapsed and the close is less than target x2
I have performed simple strategy analyses and have determined:
(Approximately)
34% lose x1
66% achieve 1:1, manually stop out at B/E after first target hits
48% achieve 2:1, manually stop out above B/E after x2 target hits
38% achieve 3:1, manually stop out above x1 after x3 target hits (will reset fib grid without change in trend)
13% achieve 4:1, manually stop out above x3 after x4 target hits (will reset fib grid without change in trend)
I have not evaluated for x6 though it expected to be around 5% of the winning trades. (will reset fib grid without change in trend)
Message me if your interested further.
HEMA - A Fast And Efficient Estimate Of The Hull Moving AverageIntroduction
The Hull moving average (HMA) developed by Alan Hull is one of the many moving averages that aim to reduce lag while providing effective smoothing. The HMA make use of 3 linearly weighted (WMA) moving averages, with respective periods p/2 , p and √p , this involve three convolutions, which affect computation time, a more efficient version exist under the name of exponential Hull moving average (EHMA), this version make use of exponential moving averages instead of linearly weighted ones, which dramatically decrease the computation time, however the difference with the original version is clearly noticeable.
In this post an efficient and simple estimate is proposed, the estimation process will be fully described and some comparison with the original HMA will be presented.
This post and indicator is dedicated to LucF
Estimation Process
Estimating a moving average is easier when we look at its weights (represented by the impulse response), we basically want to find a similar set of weights via more efficient calculations, the estimation process is therefore based on fully understanding the weighting architecture of the moving average we want to estimate.
The impulse response of an HMA of period 20 is as follows :
We can see that the first weights increases a bit before decaying, the weights then decay, cross under 0 and increase again. More recent closing price values benefits of the highest weights, while the oldest values have negatives ones, negative weighting is what allow to drastically reduce the lag of the HMA. Based on this information we know that our estimate will be a linear combination of two moving averages with unknown coefficients :
a × MA1 + b × MA2
With a > 0 and b < 0 , the lag of MA1 is lower than the lag of MA2 . We first need to capture the general envelope of the weights, which has an overall non-linearly decaying shape, therefore the use of an exponential moving average might seem appropriate.
In orange the impulse response of an exponential moving average of period p/2 , that is 10. We can see that such impulse response is not a bad estimate of the overall shape of the HMA impulse response, based on this information we might perform our linear combination with a simple moving average :
2EMA(p/2) + -1SMA(p)
this gives the following impulse response :
As we can see there is a clear lack of accuracy, but because the impulse response of a simple moving is a constant we can't have the short increasing weights of the HMA, we therefore need a non-constant impulse response for our linear combination, a WMA might be appropriate. Therefore we will use :
2WMA(p/2) + -1EMA(p/2)
Note that the lag a WMA is inferior to the lag of an EMA of same period, this is why the period of the WMA is p/2 . We obtain :
The shape has improved, but the fit is poor, which mean we should change our coefficients, more precisely increasing the coefficient of the WMA (thus decreasing the one of the EMA). We will try :
3WMA(p/2) + -2EMA(p/2)
We then obtain :
This estimate seems to have a decent fit, and this linear combination is therefore used.
Comparison
HMA in blue and the estimate in fuchsia with both period 50, the difference can be noted, however the estimate is relatively accurate.
In the image above the period has been set to 200.
Conclusion
In this post an efficient estimate of the HMA has been proposed, we have seen that the HMA can be estimated via the linear combinations of a WMA and an EMA of each period p/2 , this isn't important for the EMA who is based on recursion but is however a big deal for the WMA who use recursion, and therefore p indicate the number of data points to be used in the convolution, knowing that we use only convolution and that this convolution use twice less data points then one of the WMA used in the HMA is a pretty great thing.
Subtle tweaking of the coefficients/moving averages length's might help have an even more accurate estimate, the fact that the WMA make use of a period of √p is certainly the most disturbing aspect when it comes to estimating the HMA. I also described more in depth the process of estimating a moving average.
I hope you learned something in this post, it took me quite a lot of time to prepare, maybe 2 hours, some pinescripters pass an enormous amount of time providing content and helping the community, one of them being LucF, without him i don't think you'll be seeing this indicator as well as many ones i previously posted, I encourage you to thank him and check his work for Pinecoders as well as following him.
Thanks for reading !
Colored Moving Averages Can Help You Spot TrendsMoving averages are perhaps the most popular indicator in technical analysis. But sometimes they're not the easiest to interpret.
This indicator helps you see the trend by coloring the MA based on its direction. It's green when rising and red when falling. Of course, you can easily change that in the Style tab under Settings.
Color MA also lets you select from five different types of moving averages, including simple, exponential and Hull. We've included a list for easy reference below. Just change the "AvgType" on the Input tab under Settings.
This chart of Facebook shows the 20-day simple moving average. Notice how swings often marked turns in the stock price.
AvgType codes:
1 - Simple Moving Average
2 - Exponential Moving Average
3 - Hull Moving Average
4 - Weighted Moving Average
5 - Volume Weighted Moving Average