Dependent Variable Odd Generator For Machine Learning TechniquesCAUTION : Not suitable for strategy, open to development.
If can we separate the stagnant market from other markets, can we be so much more accurate?
This project was written to research it. It is just the tiny part of the begining.
And this is a very necessary but very small side function in the main function. Lets start :
Hi users, I had this idea in my mind for a long time but I had a hard time finding the parameters that would make the market stagnant. This idea is my first original command system. Although it is very difficult to make sense of the stagnant market, I think that this command system can achieve realistic proportions. With 's money flow index, I opened the track to determine the level. On the other hand, the prices were also using a money flow index, and it forced me to make the limitations between the levels in a logical way. But the good thing is that since the bollinger bandwidth uses a larger period, we are able to print normal values at extreme buy and sell values.
In terms of price, we can define excessive purchase and sale values as the period is smaller. I have repeatedly looked at the limit values that determine the bull, bear, and bollinger bandwidth (mfi), and I think this is the right one. Then I have included these values in the probability set.
The bull and bear market did not form the intersection of the cluster, and because there are connected events, the stagnant market, which is the intersection, will be added to the other markets with the same venn diagram logic and the sum of the probability set will be 1. is equal to. I hope that we can renew the number generators in the very important parameters of machine learning such as Markov Process with generators dependent on dependent variables, which bring us closer to reality. This function is open to development and can be made of various ideas on machine learning. Best wishes.
This code is open source under the MIT license. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com
Marketprofile
Crypto Market Change in BTC [Fingers]Crypto Market Change provides an indication of whether the value of a basket of 19 coins traded in BTC on Binance (as of July 12, 2018) are headed up or down. A simple moving average of the percentage change in BTC price for each coin is calculated. The moving averages are then summed and displayed. A measure of price volatility is indicated by standard deviation bands. Period, moving average length, and number of standard deviations are adjustable.
Crypto Market Change in BTC [Fingers]Crypto Market Change provides an indication of whether the value of a basket of 19 coins traded in BTC on Binance (as of July 12, 2018) are headed up or down. A simple moving average of the percentage change in BTC price for each coin is calculated. The moving averages are then summed and displayed. A measure of price volatility of indicated by standard deviation bands. Period, moving average length, and number of standard deviations are adjustable.
Crypto Market Change in USDT [Fingers]Crypto Market Change provides an indication of whether the value of a basket of 16 coins traded in USDT on Binance (as of July 12, 2018) are headed up or down. A simple moving average of the percentage change in USDT price for each coin is calculated. The moving averages are then summed and displayed. A measure of price volatility of indicated by standard deviation bands. Period, moving average length, and number of standard deviations are adjustable.
[RS]Market ProfileEXPERIMENTAL: this script is very crude and prone to errors..
Request for: FibTrader
instead of a POC line theres a POC area instead, since the script is checking a price area range for the frequency, its possible to average the values but this works as well.
