AMC Dividend Shift Variance [Joshlo]This indicator displays the price ranges supplied by various data sources for the historical price of AMC Entertainment Holdings, NYSE:AMC .
This indicator can be used to aid in technical analysis, historical trend line creation, Fibonacci placement etc. in the current environment where different data providers for the historical price of AMC differs and there is no answer on the 'correct' post dividend split percentage.
The use of this indicator on tickers other than AMC will result in meaningless data.
The standard pre split price range is shown in purple, with the upper limit of the range showing the highs and the lower limit of the range showing the lows.
The new high and low ranges for 3 different data sources/brokerages are shown in 3 different colours, with the multiplication values shown within the indicator settings for transparency. These settings should ideally not be adjusted and are calculated via the data gathered by Mr Books and distributed via his YouTube video, " My anger. Our charts. Your choice. ".
Each of the data sources can be shown or hidden via the indicator settings as well as having their colours adjusted via the indicator settings.
The projection of the adjusted historical prices stops at the ex-dividend date for the AMC APE offering. The time set in the indicator is based on my time zone in the UK and should be adjusted by you to suit the time zone you view your charts in.
Cerca negli script per "AMC+股票推荐"
741 GME vs AMCA very simple script to compare 7 shares of $AMC versus 1 share of $GME.
The script uses the closing price of the given securities.
Cumulative Distribution of a Dataset [SS]This is the Cumulative Distribution of a Dataset indicator that also calculates the Kurtosis and Skewness for a selected dataset and determines the normality and distribution type.
What it does, in pragmatic terms?
In the most simplest terms, it calculates the cumulative distribution function (or CDF) of user-defined dataset.
The cumulative distribution function (CDF) is a concept used in statistics and probability to describe how the probability of a random variable taking on a certain value or less is distributed across the entire range of possible values. In simpler terms, you can conceptualize the CDF as this:
Imagine you have a list of data, such as test scores of students in a class. The CDF helps you answer questions like, "What's the probability that a randomly chosen student scored 80 or less on the test?"
Or in our case, say we are in a strong up or downtrend on a stock. The CDF can help us answer questions like "Based on this current xyz trend, what is the probability that a ticker will fall above X price or below Y price".
Within the indicator, you can manually assess a price of interest. Let's say, for NVDA, we want to know the probability NVDA goes above or below $450. We can enter $450 into the indicator and get this result:
Other functions:
Kurtosis and Skewness Functions:
In addition to calculating and plotting the CDF, we can also plot the kurtosis & Skewness.
This can help you look for outlier periods where the distribution of your dataset changed. It can potentially alert you to when a stock is behaving abnormally and when it is more stable and evenly distributed.
Tests of normality
The indicator will use the kurtosis and skewness to determine the normality of the dataset. The indicator is programmed to recognize up to 7 different distribution types and alert you to them and the implications they have in your overall assessment.
e.g. #1 AMC during short squeeze:
e.g. #2: BA during the COVID crash:
Plotting the standardized Z-Score of the Distribution Dataset
You can also standardize the dataset by converting it into Z-Score format:
Plot the raw, CDF results
Two values are plotting, the green and the red. The green represents the probability of a ticker going higher than the current value. The red represents the probability of a ticker going lower than the current value.
Limitations
There are some limitations of the indicator which I think are important to point out. They are:
The indicator cannot tell you timelines, it can only tell you the general probability that data within the dataset will fall above or below a certain value.
The indicator cannot take into account projected periods of consolidation. It is possible a ticker can remain in a consolidation phase for a very long time. This would have the effect of stabilizing the probability in one direction (if there was a lot of downside room, it can normalize the data out so that the extent of the downside probability is mitigated). Thus, its important to use judgement and other methods to assess the likelihood that a stock will pullback or continue up, based on the overall probability.
The indicator is only looking at an individual dataset.
Using this indicator, you have to omit a large amount of data and look at solely a confined dataset. In a way, this actually improves the accuracy, but can also be misleading, depending on the size and strength of the dataset being chosen. It is important to balance your choice of dataset time with such things as:
a) The strength of the uptrend or downtrend.
b) The length of the uptrend or downtrend.
c) The overall performance of the stock leading into the dataset time period
And that is the indicator in a nutshell.
Hopefully you find it helpful and interesting. Feel free to leave questions, comments and suggestions below.
Safe trades everyone and take care!
Relative Volume & RSI PopThis is a basic idea/script designed to take a breakout trade by taking advantage of volume spikes when price/strength is extended (either long or short).
The script only utilises two indicators, the Relative Volume (RV) and the Relative Strength Index (RSI). The script allows the user to select a RSI value between 69 up to 100 for a long trade and between 35 down to 0 for short trade and then pair this with RV from 0 - 10. The period for both the RSI and RV can also be amended by the user but I found in most cases there was no benefit gained by changing away from normal "14" period lookback. The script typically only has small draw downs as the script is designed to exit the trade when the RSI returns back to "normalised" level, therefore the trades are generally quite short. The exit condition for a long trade is when RSI crosses back below 69 (which is why you cannot enter a long below this value) and for a short the, trade will close when RSI crosses back above 35 (which is why you cannot enter a short above this value). These exit values are locked.
By allowing RSI value to go all the way up to "100" on the long side and "0" on the short side this in effect is a way of eliminating the script from taking either longs or shorts if lets say you wanted to back test the script for long only spikes or short only spike. E.G. By setting RSI upper value to "75" the RV to "1" and RSI lower value to "0" then no short trades will not be taken in your back test as the RSI never really gets down to zero.
I put this together with meme stocks in mind and back tested it on day charts for AMC and then a few trending style stocks too. It typically worked best as long only and with RSI settings between 71 - 75 and RV at 1 or 1.5. I also found it had okay results on some lower 1hr timeframe futures markets and weekly time frames too (albeit trades were few and far between on weekly timeframe).
The beauty of such a basic script you could easily set up a trading view screener to look for these opportunities everyday and perhaps even add in an ADX filter on the screener to see if the trend is increasing. Then use this script to run a back test on the stocks that you've selected from the screener.
