BACKGROUND McMillan Volatility Bands are an alternative approach to John Bollinger's "Bollinger Band" study and developed by world-renowned options trader and author Lawrence G. McMillan. Given his background in options trading, it was natural for Lawrence to approach any volatility-based study in the same manner options are priced --using Black-Scholes model....
This moving average was originally developed by professor Andreas Uhl in 2005 (The paper in German: www.buero-uhl.de). Here is the guy himself: wavelab.at The strength of the CMA is that the current value of the time series must exceed the current volatility-dependent threshold, so that the filter increases or falls, avoiding false signals in weak phases. The...
This indicator shows a Key Level Support & Resistance level and VWAP that reset on your choice of the Bitcoin's halving date. Optional Key Calculation Mode: - Start with first (2012) or second (2016) halving date. - Start with first and reset on the second (Halving to halving mode) - Start with every next halving simultaneously (Halving + halving mode) Labels...
This indicator shows a Key Level Support & Resistance level and VWAP that resets on your choice of the stock's Earnings , Dividends or Splits release date. A maximum of 8 bands calculated using a factor of the anchored VWAP's standard deviation can be displayed. Note The script is designed for stock-trading only. Credits Inspired by timwest , LazyBear 's ...
This script creates a STDEV in a candle format so you can see the Change in a candle format and compare it with the actual price candle. Is very similar to SMU RSI and SMU ROC. The interesting part is to see the full effect of traditional indicators in a candle format rather than a simple plot format. Very interesting view in SPX. There is a very big clue in the...
This is a fun little project that allows you to anchor the Volume Weighed Average Price (VWAP) to a specific day and plot up to 4 standard deviations up or down. I've also added a Volume Weighted Moving Average (VWMA) plot and accompanying cloud to more easily visualize how volume-based momentum affects trends. Typically, you'll see price respecting the VWMA...
█ WARNING Improvements to the following Pine built-ins have deprecated the vast majority of this publication's functions, as the built-ins now accept "series int" `length` arguments: ta.wma() ta.linreg() ta.variance() ta.stdev() ta.correlation() NOTE For an EMA function that allows a "series int" argument for `length`, please see `ema2()` in...
Has alerts for the TD 9 function, also the black is Z score and blue is STD Dev Also the moon functionality of Ichimoonku is built into this as well because sometimes I just want to see the cycles of moon with TD9 ; see that script (Ichimoonku) for more info on moon functionality. Much love Enjoy GL HF xoxo Snoop
Expected Ranges base on AEONDRIFT implementation of Standard Deviation bands. Note: In no way is this intended as a financial/investment/trading advice. You are responsible for your own investment/trade decisions. Please PM me for access information.
This script shows Bollinger Bands function and want to detect Bollinger Band Width Squeeze with a successful, different perspective . Bollinger Bands : You can specify the Bollinger Bands periods as mutable variables . Bollinger Band Width Squeeze : First the Bollinger bands width was calculated.The width was then divided into levels using the money flow...
Introduction The standard deviation measure the dispersion of a data set, in short this metric will tell you if your data is on average closer or farther away from the mean. Its one of the most important tools in statistics and living without it is pretty much impossible, without it you can forget about Bollinger-bands, CCI, and even the LSMA (ouch this hurt)...
AEONDRIFT with {EMA} implementation of FUSIONGAPS (FG) and DIFFERENTIAL FUSIONGAPS (DFG) derived indicators. ~JuniAiko (=^~^=)v~ Check out the other analytical tools that I had published. AEONDRIFT:
Auto trend channel based on donchian or standard deviation.
This indicator was originally developed by David Sepiashvili (Stocks & Commodities V. 24:2 (February, 2006): The Self-Adjusting RSI ). The author presented a technique to adjust the traditional RSI overbought and oversold thresholds so as to ensure that 70-80% of RSI values lie between the two thresholds. He used two algorithms for adjusting: Standard...