What is this? The Money Flow Line (MFL) indicator is at its core a more even-tempered version of the Price-Volume-Trend (PVT). The primary difference is the usage of `hlc3` ((high + low + close) / 3) rather than `close` to use the "typical price" that it critical to the calculation of the Money Flow Index (MFI). Other similar indicators include the Accumulation...
Trend Identifier for 1D BTC.USD It smoothens a closely following moving average into a polynomial like plot. And assumes 4 stage cycles based on the first and second derivatives. Green: Bull / Exponential Rise Yellow: Distribution Red: Bear / Exponential Drop Blue: Accumulation Red --> Blue --> Green: indicates the start of a bull market Green --> Yellow -->...
a basic tool to retrieve statistics of the distribution of price range sequences.
Basic modification of my SFP Momentum Indicator showing accumulation/distribution patterns based on breakouts above previous anchor points. Candles are colored based on whether accumulation or distribution was last. Best if used at HTF then confirmed at LTF.
Custom swing fail detector with levels and breakouts both major and minor plus colored candles based on SFP momentum.
A probability cone is an indicator that forecasts a statistical distribution from a set point in time into the future. Features Forecast a Standard or Laplace distribution. Change the how many bars the cones will lookback and sample in their calculations. Set how many bars to forecast the cones. Let the cones follow price from a set number of bars back. ...
Library "FunctionProbabilityDistributionSampling" Methods for probability distribution sampling selection. sample(probabilities) Computes a random selected index from a probability distribution. Parameters: probabilities : float array, probabilities of sample. Returns: int.
function to calculate Chebyshev Inequality. wich can be used to compute the probability that we will diverge from what we expect to obtain. reference: - www.omnicalculator.com - github.com - statisticstopics.wordpress.com - en.wikipedia.org
A detrended series that oscilates around zero is obtained after first differencing a time series (i.e. subtracting the closing price for a candle from the one immediately before, for example). Hypothetically, assuming that every detrended closing price is independent of each other (what might not be true!), these values will follow a normal distribution with mean...
function to retrieve Gini Impurity / Gini Index. reference: - victorzhou.com - en.wikipedia.org
displays the distribution of the outcome of a event over the last event. similar to this script:
Dollar volume is simply the volume traded multiplied times the cost of the stock. Dollar volume is an extremely important metric for finding stocks with enough liquidity for market makers to position themselves in. Market Liquidity is defined as market's feature whereby an individual or firm can quickly purchase or sell an asset without causing a drastic change...
Up/Down Volume Ratio is calculated by summing volume on days when it closes up and divide that total by the volume on days when the stock closed down. High volume up days are typically a sign of accumulation(buying) by big players, while down days are signs of distribution(selling) by big market players. The Up Down volume ratio takes this assumption and turns...
Volume Buzz/Volume Run Rate as seen on TC2000 and MarketSmith respectively. Basically, the volume buzz tells you what percentage over average(100 time period moving average) the volume traded was. You can use this indicator to more readily identify above-average trading volume and accumulation days on charts. The percentage will show up in the top left corner,...
This applies Chande Momentum to Accumulation and Distribution index as a means to changes. Experimental oscillator. Compare it to both Money Flows, Acc/Dis and Chande and you notice it has elements of all of them. Could potentially replace other volume based momentum indicators in your strategy. It is a little more volatile, reaching from side to side, while...
A function to build random decision tree's paths using a bias distribution.
It is possible to approximate the underlying distribution of a random variable by using what is called an "Histogram". In order to construct an histogram one must first split the data into several intervals (also called bins) often of the same size and count the number of values falling within each intervals, the histogram plot is then constructed with the X axis...
Simple Accumulation & Distribution indicator with the 21 and 200EMA plotted on it. Might be a useful tool in your arsenal.