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
Description : This is a renovated version of my previous mod that was based on the original script from fhenry0331.
Added are:
a data cleaning function
a seasonal random index function
an updated scaler and
a signalling procedure.
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The following description is moved here from the old script.
The purpose of this script is to decipher chop zones from...
In Finance, people usually assume the price follows a random walk or more precisely geometric Brownian motion. In 1988, Lo and MacKinlay came up with the variance ratio test to refute the random walk hypothesis and efficient market hypothesis. The variance ratio test is a simple test for market efficiency, autocorrelation, and whether price follows a random walk....
Experimental:
Example execution of Monte Carlo Simulation applied to the markets(this is my interpretation of the algo so inconsistencys may appear).
note:
the algorithm is very demanding so performance is limited.
This script generates pseudo-random asset data . Due to the nature of the random generator, it is impossible to use this indicator as input for other indicators because the instance of the script that the indicator is applied to will automatically be different from the instance that is plotted on the chart. Therefore, the idea is to use this script in other...
Have you ever wondered how your win rate compares with flipping a coin? Well now you can check with Coin Flipper Pro!
This script produces a random position direction like flipping a coin and sets up a long or short trade based on you desired risk % and target ratio.
Have fun!
Converted the script "Coin Flipper Pro" into a Strategy. The same random "Coin Flip" trading fun with new features. Now users can run back test on the random trades and see how adjusting the risk to reward ratio affects the over all win rate and the profit of each trade. The Back test can be enabled or disabled in the settings along with the option to choose...
" tHe MaRkEtS aRe RaNdOm ", say moron academics.
The purpose of this study is to show that most markets are NOT random! Most markets show a clear bias where we can make such easy money, that a random number generator can do it.
=== HOW THE INDICATOR WORKS ===
The study will randomly enter the market
The study will randomly exit the market if in a trade
...
This is a moving average with a customizable random kernel. You can shape your kernel by selecting your parameters in the settings window. This is not something that is immediately ready to mess with by just applying it on the chart, it is very useful for people who are researching indicators and developing new tools. To see the shape of your kernel you can plug...
This script lets you separate alerts into batches, and trigger each batch in either sequential order or (pseudo)random order. You can also specify the number of batches being used.
This is helpful when you have alerts to be triggered on every candle, but the number of alerts causes API errors if they are all executed at once.
EXPERIMENTAL:
Function to generate a normally distributed pseudo random value.
if you find that something doesn't add up, please leave a message bellow.
Library "FunctionSMCMC"
Methods to implement Markov Chain Monte Carlo Simulation (MCMC)
markov_chain(weights, actions, target_path, position, last_value) a basic implementation of the markov chain algorithm
Parameters:
weights : float array, weights of the Markov Chain.
actions : float array, actions of the Markov Chain.
target_path : float...
Library "FunctionDecisionTree"
Method to generate decision tree based on weights.
decision_tree(weights, depth) Method to generate decision tree based on weights.
Parameters:
weights : float array, weights for decision consideration.
depth : int, depth of the tree.
Returns: int array
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.
![SPX500USD: Variance Ratio Test [pig]](https://s3.tradingview.com/y/yLmf8U9b_mid.png "Variance Ratio Test [pig]")
![USDRUB: [RS]Function - Functions to generate Random values](https://s3.tradingview.com/e/EgKBHFnb_mid.png "[RS]Function - Functions to generate Random values")
![USDCAD: [RS]Function - Normaly Distributed Pseudo Random Generator](https://s3.tradingview.com/c/C99iz4Vr_mid.png "[RS]Function - Normaly Distributed Pseudo Random Generator")
