Trend Artificial Intelligence Hello Everybody,
One thing that is important to understand is that every strategy needs to be tuned: for underlying, exchange, time frame etc.
There are so many indicators and tools ( moving average, Renko, RSI etc etc...) well proven and accepted by traders but you pick any of them and apply to any underlying it will not work. Why because they need to be tuned to specific factors.
This strategy is tuned using Artificial Intelligence models for Oanda Exchange for Euro/USD currency with time frame of 1 min ( this is very important)
Don't trust me check out its performance and you will know. Getting 10-20% return per month is not impossible.
Artificial_neural_networks
Blockchain Artificial Neural NetworksI found a very high correlation in a research-based Artificial Neural Networks.(ANN)
Trained only on daily bars with blockchain data and Bitcoin closing price.
NOTE: It does not repaint strictly during the weekly time frame. (TF = 1W)
Use only for Bitcoin .
Blockchain data can be repainted in the daily time zone according to the description time.
Alarms are available.
And you can also paint bar colors from the menu by region.
After making reminders, let's share the details of this interesting research:
INPUTS :
1. Average Block Size
2. Api Blockchain Size
3. Miners Revenue
4. Hash Rate
5. Bitcoin Cost Per Transaction
6. Bitcoin USD Exchange Trade Volume
7. Bitcoin Total Number of Transactions
OUTPUTS :
1. One day next price close (Historical)
TRAINING DETAILS :
Learning cycles: 1096436
AutoSave cycles: 100
Grid :
Input columns: 7
Output columns: 1
Excluded columns: 0
Training example rows: 446
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network :
Input nodes connected: 7
Hidden layer 1 nodes: 5
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Controls :
Learning rate: 0.1000
Momentum: 0.8000
Target error: 0.0100
Training error: 0.010571
The average training error is really low, almost worth the target.
Without using technical analysis data, we established Artificial Neural Networks with blockchain data.
Interesting!
ANN Forecast Dependent Variable Odd GeneratorHello , this script is the ANN Forecast version of my "Dependent Variable Odd Generator " script.
I went to simplify a bit because the deep learning calculations are too much for this command.
The latest instruments included:
WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average error : 0.007593
BRENT : Brent Crude Oil ( BCOUSD , UKOIL , BB1! ) Average error : 0.006591
GOLD : XAUUSD , GOLD , GC1! Average error : 0.012767
SP500 : S&P 500 Index ( SPX500USD , SP1! ) Average error : 0.011650
EURUSD : Eurodollar ( EURUSD , 6E1! , FCEU1!) Average error : 0.005500
ETHUSD : Ethereum ( ETHUSD , ETHUSDT ) Average error : 0.009378
BTCUSD : Bitcoin ( BTCUSD , BTCUSDT , XBTUSD , BTC1! ) Average error : 0.01050
GBPUSD : British Pound ( GBPUSD , 6B1! , GBP1!) Average error : 0.009999
USDJPY : US Dollar / Japanese Yen ( USDJPY , FCUY1!) Average error : 0.009198
USDCHF : US Dollar / Swiss Franc ( USDCHF , FCUF1! ) Average error : 0.009999
USDCAD : Us Dollar / Canadian Dollar ( USDCAD ) Average error : 0.012162
VIX : S & P 500 Volatility Index (VX1! , VIX ) Average error : 0.009999
ES : S&P 500 E-Mini Futures ( ES1! ) Average error : 0.010709
SSE : Shangai Stock Exchange Composite (Index ) ( 000001 ) Average error : 0.011287
XRPUSD : Ripple (XRPUSD , XRPUSDT ) Average error : 0.009803
Simply select the required instrument from the tradingview analysis screen, then add this command and select the same instrument from the settings section.
The codes are not open-source because they contain forecast algorithm codes a little that I will use commercially in the future.
However, I will never remove this script, and you can use it for free unlimitedly.
For more information about my artificial neural network forecast series:
For more information about my dependent variable odd generator :
For more information about simple artificial neural networks :
(detailed information about ANN )
(25 in 1 version )
I hope it helps in your analysis. Regards , Noldo .
NOTE : In the first pass bar of the definite positive and negative zone, alerts are added for both conditions.
ANN Forecast Stochastic Oscillator [Noldo] In this script, I tried to integrate ANN Forecast Algorithm on Stochastic Oscillator.
It took me quite a while, but i guess it worth.
After selecting the ticker, select the instrument from the menu and the system will automatically turn on the appropriate Forecast Stoch system.
The system is trained with ANN values of ANN MACD 25 in 1.
The Forecast algorithm is not open-source.
But I'm never remove this script.
You can use it forever for free.
As you can see in the presentation, although it is in the same period, it is more accurate and agile than standard Stochastic Oscillator .
I think even a bar is important in trade.
For those who don't see that command,listed instruments with alternative tickers and error rates:
WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average error : 0.007593
BRENT : Brent Crude Oil ( BCOUSD , UKOIL , BB1! ) Average error : 0.006591
GOLD : XAUUSD , GOLD , GC1! Average error : 0.012767
SP500 : S&P 500 Index ( SPX500USD , SP1! ) Average error : 0.011650
EURUSD : Eurodollar ( EURUSD , 6E1! , FCEU1!) Average error : 0.005500
ETHUSD : Ethereum ( ETHUSD , ETHUSDT ) Average error : 0.009378
BTCUSD : Bitcoin ( BTCUSD , BTCUSDT , XBTUSD , BTC1! ) Average error : 0.01050
GBPUSD : British Pound ( GBPUSD , 6B1! , GBP1!) Average error : 0.009999
USDJPY : US Dollar / Japanese Yen ( USDJPY , FCUY1!) Average error : 0.009198
USDCHF : US Dollar / Swiss Franc ( USDCHF , FCUF1! ) Average error : 0.009999
USDCAD : Us Dollar / Canadian Dollar ( USDCAD ) Average error : 0.012162
SOYBNUSD : Soybean ( SOYBNUSD , ZS1! ) Average error : 0.010000
CORNUSD : Corn ( ZC1! ) Average error : 0.007574
NATGASUSD : Natural Gas ( NATGASUSD , NG1! ) Average error : 0.010000
SUGARUSD : Sugar ( SUGARUSD , SB1! ) Average error : 0.011081
WHEATUSD : Wheat ( WHEATUSD , ZW1! ) Average error : 0.009980
XPTUSD : Platinum ( XPTUSD , PL1! ) Average error : 0.009964
XU030 : Borsa Istanbul 30 Futures ( XU030 , XU030D1! ) Average error : 0.010727
VIX : S & P 500 Volatility Index (VX1! , VIX ) Average error : 0.009999
ES : S&P 500 E-Mini Futures ( ES1! ) Average error : 0.010709
SSE : Shangai Stock Exchange Composite (Index ) ( 000001 ) Average error : 0.011287
XRPUSD : Ripple (XRPUSD , XRPUSDT ) Average error : 0.009803
Extras :
- Crossover and crossunder alerts
- Switchable barcolor
NOTE :
Australian Dollar / US Dollar ( AUDUSD ) removed due to high average error. (Average error > 0.013 )
Timeframe advice :
I suggest you to use that system TF >= 1D
My favorite is 1 week bars. (1W)
More info about forecast series (My last forecast example ) :
Special thanks :
Special thanks to dear wroclai for his great effort .
NOTE : I decided to build Autonomous LSTM on Stochastic Oscillator , i think Stochastic Oscillator one of the best and it contains naturally high-lows.
ANN GOLD WORLDWIDE This script consists of converting the value of 1 gram and / or 1 ounce of gold according to the national currencies into a system with artificial neural networks.
Why did I feel such a need?
Even though the printed products in the market are digitally circulated, only precious metals are available in full or near full.
Silver is difficult to carry because you have to buy too much because the unit price is low.
Platinum is very difficult to find and used in industry.
Gold is both practical and has less volatile movements, even more balanced than dollars, to preserve the value of money.
Uncertainty and tensions benefit gold.
Obviously this is my own opinion and is not worth the investment advice:
If there is to be an economic crisis, it is obvious that the dollar will rise against the emerging currencies, but I expect a crisis where gold and the dollar will rise together.
The world has been on a mercantilist line more than ever!
Spot gold can be bought from goldsmiths and banks.
I think this command will benefit people everywhere but in economies that are subject to developing currencies.
Now we can look at the details:
All you have to do is load the appropriate chart and select it from the menu.
Thus, the system will adjust itself to that instrument.
MENU and Tickers :
"GOLD" : XAUUSD or GC1! or GOLD (Average error = 0.0128)
"GOLDSILVER" : XAUXAG or GOLDSILVER (Gold Silver Ratio ) ( Average error : 0.01 )
"GOLD CZK " : XAUUSD/USDCZK ( 1 Ounce Gold Czech Koruna) ( Average error = 0.010879 )
"GOLD NZD " : XAUUSD/USDNZD ( 1 Ounce Gold New Zealand Dollar ) (Average error = 0.010736 )
"GOLD EURO" : XAUUSD/USDEUR ( 1 Ounce Gold Euro) ( Average error = 0.010000 )
"GOLD HUF " : XAUUSD/USDHUF ( 1 Ounce Gold Hungarian Forint ) ( Average error = 0.010000 )
"GOLD INR " : XAUUSD/USDINR (1 Ounce Gold Indian Rupee ) (Average error = 0.010458 )
"GOLD DKK" : XAUUSD/USDDKK (1 Ounce Gold Danish Krone) (Average error = 0.010671 )
"GOLD CHF" : XAUUSD/USDCHF (1 Ounce Gold Swiss Franc ) (Average error = 0.010967 )
"GOLD CNH" : XAUUSD/USDCNH(1 Ounce Gold Offshore RMB) (Average error = 0.012017 )
"GOLD MXN" : XAUUSD/USDMXN(1 Ounce Gold Mexican Peso) (Average error = 0.010000 )
"GOLD PLN" : XAUUSD/USDPLN (1 Ounce Gold Polish Zloty ) (Average error = 0.010173 )
"GOLD ZAR" : XAUUSD/USDZAR (1 Ounce Gold South African Rand (Average error = 0.010484 )
"GOLD NOK" : XAUUSD/USDNOK (1 Ounce Gold Norwegian Krone ) (Average error = 0.010842 )
"GOLD TRY" : XAUUSD/USDTRY (1 Ounce Gold Turkish Lira ) (Average error = 0.010000 )
"GOLD THB" : XAUUSD/USDTHB (1 Ounce Gold Thai Baht ) (Average error = 0.011747 )
Important note : XAUUSD/USDCUR = 1 Ounce Gold , XAUUSD/31.1*USDCUR = 1 gram Gold (CUR = Currency )
If you want to physically hold it, look gram value, because as far as I know, all goldsmiths and jewelleries in the world are selling gram gold.
I think that this command is the most useful and the concrete one that I have ever written.
I end my sentences with this anonymous proverb :
"Even if gold falls into the mud, it's still gold ! "
ANN MACD : 25 IN 1 SCRIPTIn this script, I tried to fit deep learning series to 1 command system up to the maximum point.
After selecting the ticker, select the instrument from the menu and the system will automatically turn on the appropriate ann system.
Listed instruments with alternative tickers and error rates:
WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average error : 0.007593
BRENT : Brent Crude Oil (BCOUSD , UKOIL , BB1! ) Average error : 0.006591
GOLD : XAUUSD , GOLD , GC1! Average error : 0.012767
SP500 : S&P 500 Index (SPX500USD , SP1!) Average error : 0.011650
EURUSD : Eurodollar (EURUSD , 6E1! , FCEU1!) Average error : 0.005500
ETHUSD : Ethereum (ETHUSD , ETHUSDT ) Average error : 0.009378
BTCUSD : Bitcoin (BTCUSD , BTCUSDT , XBTUSD , BTC1!) Average error : 0.01050
GBPUSD : British Pound (GBPUSD,6B1! , GBP1!) Average error : 0.009999
USDJPY : US Dollar / Japanese Yen (USDJPY , FCUY1!) Average error : 0.009198
USDCHF : US Dollar / Swiss Franc (USDCHF , FCUF1! ) Average error : 0.009999
USDCAD : Us Dollar / Canadian Dollar (USDCAD) Average error : 0.012162
SOYBNUSD : Soybean (SOYBNUSD , ZS1!) Average error : 0.010000
CORNUSD : Corn (ZC1! ) Average error : 0.007574
NATGASUSD : Natural Gas (NATGASUSD , NG1!) Average error : 0.010000
SUGARUSD : Sugar (SUGARUSD , SB1! ) Average error : 0.011081
WHEATUSD : Wheat (WHEATUSD , ZW1!) Average error : 0.009980
XPTUSD : Platinum (XPTUSD , PL1! ) Average error : 0.009964
XU030 : Borsa Istanbul 30 Futures ( XU030 , XU030D1! ) Average error : 0.010727
VIX : S & P 500 Volatility Index (VX1! , VIX ) Average error : 0.009999
YM : E - Mini Dow Futures (YM1! ) Average error : 0.010819
ES : S&P 500 E-Mini Futures (ES1! ) Average error : 0.010709
GAZP : Gazprom Futures (GAZP , GZ1! ) Average error : 0.008442
SSE : Shangai Stock Exchange Composite (Index ) ( 000001 ) Average error : 0.011287
XRPUSD : Ripple (XRPUSD , XRPUSDT ) Average error : 0.009803
Note 1 : Australian Dollar (AUDUSD , AUD1! , FCAU1! ) : Instrument has been removed because it has an average error rate of over 0.13.
The average error rate is 0.1850.
I didn't delete it from the menu just because there was so much request,
You can use.
Note 2 : Friends have too many requests, it took me a week in total and 1 other script that I'll share in 2 days.
Reaching these error rates is a very difficult task, and when I keep at a low learning rate, they are trained for a very long time.
If I don't see the error rate at an average low, I increase the layers and go back into a longer process.
It takes me 45 minutes per instrument to command artificial neural networks, so I'll release one more open source, and then we'll be laying 70-80 percent of the world trade volume with artificial neural networks.
Note 3 :
I would like to thank wroclai for helping me with this script.
This script is subject to MIT License on behalf of both of us.
You can review my original idea scripts from my Github page.
You can use it free but if you are going to modify it, just quote this script .
I hope it will help everyone, after 1-2 days I will share another ann script that I think is of the same importance as this, stay tuned.
Regards , Noldo .
ANN MACD WTI (West Texas Intermediate) This script created by training WTI 4 hour data , 7 indicators and 12 Guppy Exponential Moving Averages.
Details :
Learning cycles: 1
AutoSave cycles: 100
Training error: 0.007593 ( Smaller than average target ! )
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 300
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 6
Hidden layer 3 nodes: 0
Output nodes: 1
Learning rate: 0.7000
Momentum: 0.8000
Target error: 0.0100
Special thanks to wroclai for his great effort.
Deep learning series will continue. But I need to rest my eyes a little :)
Stay tuned ! Regards.
ANN MACD S&P 500 This script is formed by training the S & P 500 Index with various indicators. Details :
Learning cycles: 78089
AutoSave cycles: 100
Training error: 0.011650 (Far less than the target, but acceptable.)
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 300
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 1
Hidden layer 3 nodes: 0
Output nodes: 1
Learning rate: 0.7000
Momentum: 0.8000
Target error: 0.0100
Note : Thanks for dear wroclai for his great effort .
Deep learning series will continue . Stay tuned! Regards.
ANN MACD EURUSD (FX) Hello , this script is trained with eurusd 4-hour data. (550 columns) Details :
Learning cycles: 8327
AutoSave cycles: 100
Training error: 0.005500 ( That's a very good error coefficient.)
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 550
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 5
Hidden layer 3 nodes: 0
Output nodes: 1
Learning rate: 0.6000
Momentum: 0.8000
Target error: 0.0055
NOTE : Use with EURUSD only.
Alarms added.
Thanks dear wroclai for his great effort.
Deep learning series will continue ! Stay tuned.
Regards , Noldo .
ANN MACD ETHEREUM
This script is trained with Ethereum (Timeframe : 4 hours ).
Details :
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 300
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Input nodes connected: 19
Hidden layer 1 nodes: 8
Hidden layer 2 nodes: 1
Hidden layer 3 nodes: 0
Output nodes: 1
Learning rate: 0.7000
Momentum: 0.8000
Training error: 0.009378 ( That's a very good error coefficient. )
Many thanks to wroclai for help.
Deep learning series will continue!
ANN MACD BTC v2.0 This script is the 2nd version of the BTC Deep Learning (ANN) system.
Created with the following indicators and tools:
RSI
MACD
MOM
Bollinger Bands
Guppy Exponential Moving Averages:
(3,5,8,10,12,15,30,35,40,45,50,60)
Note: I was inspired by the CM Guppy Ema script.
Thank you very much to dear wroclai for his great help.
He has been a big help in the deep learning series.
That's why the licenses in this series are for both of us.
I'm sharing these series and thats the first. Stay tuned and regards!
Note : Alerts added.
ANN MACD Future Forecast (SPY 1D) NOTE : Deep learning was conducted in a narrow sample set for testing purposes. So this script is Experimental .
This system is based on the following article and is inspired by an external program:
hackernoon.com
None of the artificial neural networks in Tradingview work and are not based on completely correct logic. Unlike others in this system:
IMPORTANT NOTE: If the tangent activation function is used, the input data must also have tangent values (compared to the previous values of 1 bar).
Inputs were prepared according to this judgment.
1. The tangent function which is the activation function is written correctly. (The tangent function in the article: ActivationFunctionTanh (v) => (1 - exp (-2 * v)) / (1 + exp (-2 * v)))
2. Missing bias parts in the formulas were added.
3. The output function is taken from the next day (historical), so that the next bar can be predicted, which is the truth.
4.The forecast value of the next bar is subtracted from the current bar change and the market direction is determined.
5.When the future forecast and the current close are added together, the resulting data is called seed.
The seed carries data both from the present and from yesterday and from the future.
6.And this seed was subjected to the MACD method.
Thus, due to exponential averages, more importance will be given to recent developments and
The acceleration situations will show us the direction.
However, a short position should be taken for crossover and a long position for crossunder .
Because the predicted values work in reverse.Even though we use the same period (9,12,26) it is much faster!
7. There is no future code that can cause Repaint.
However, the color after closing should be checked.
The system is completely correct.
However, a very narrow sample was selected.
100 data: Tangent diffs ; volume change, bollinger bands values changes (Upband , Midband , Lowband) and LazyBear's Squeeze Momentum Indicator (SQZMOM_LB) change and the next bar data (historical) price change were put into the deep learning test.
IMPORTANT NOTE : The larger the sample set and the more effective dependent variables, the higher the hit rate of the deep learning test!
EDIT : 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
Stay tuned. Best regards!
Megalodon Pro Automated Trader BackTester
Why Megalodon?
We believe that enlightening others is an incredible way to make this world a better place. That's why we created the tools you need to stop worrying about your investments and focus on what really matters in your life.
What is Megalodon?
Megalodon uses Artificial Intelligence that combines 574 back-tested indicators and 2674 back-tested setups, simultaneously.
Megalodon works with any kind of asset , market state and time frame .
What is the win rate?
Megalodon is extremely accurate and offers insane profits as long as the fundamental analysis is done right .
Backtesting results can be found on our social media or down below .
How to use Megalodon Pro Automated Trader?
Simply, orange rectangles are buy signals and purple rectangles are sell signals .
Green clouds show buy signals and red clouds show sell signals.
Yellow line shows the difference between buy and sell counts.
How to set alarms on Megalodon Pro Automated Trader?
Click on Alert, select Megalodon Pro Automated Trader and click on Buy-Signal or Sell-Signal. More details can be found on our social media.
You may also watch our Megalodon Investing Tutorials on Youtube for more information.
How to purchase?
Megalodon is totally FREE .
You may upgrade to Megalodon Pro for the most important features , including automizing your trading on any asset profitably, setting up alarms to get notified , joining to our VIP telegram channel to get daily updates and our VIP telegram group to interact with the community. Simply go to our website on our TradingView page for learning more and joining us for free.
Some of the backtesting results are:
BTC/USD for longer time frame trading in the bear market for the last year.
APPLE for longer time frame trading in the bull market for the last 10 years.
EURO/USD for day trading in the neutral market for the last month.
BTC/USD for day trading in the bull market for the last 15 days.
APPLE for day trading in the neutral market for the last 2 days and 6 hours.
Megalodon Pro Automated Trader
Why Megalodon?
We believe that enlightening others is an incredible way to make this world a better place. That's why we created the tools you need to stop worrying about your investments and focus on what really matters in your life.
What is Megalodon?
Megalodon uses Artificial Intelligence that combines 574 back-tested indicators and 2674 back-tested setups, simultaneously.
Megalodon works with any kind of asset , market state and time frame .
What is the win rate?
Megalodon is extremely accurate and offers insane profits as long as the fundamental analysis is done right .
Backtesting results can be found on our social media or down below .
How to use Megalodon Pro Automated Trader?
Simply, orange rectangles are buy signals and purple rectangles are sell signals .
Green clouds show buy signals and red clouds show sell signals.
Yellow line shows the difference between buy and sell counts.
How to set alarms on Megalodon Pro Automated Trader?
Click on Alert, select Megalodon Pro Automated Trader and click on Buy-Signal or Sell-Signal. More details can be found on our social media.
You may also watch our Megalodon Investing Tutorials on Youtube for more information.
How to purchase?
Megalodon is totally FREE .
You may upgrade to Megalodon Pro for the most important features , including automizing your trading on any asset profitably, setting up alarms to get notified , joining to our VIP telegram channel to get daily updates and our VIP telegram group to interact with the community. Simply go to our website on our TradingView page for learning more and joining us for free.
Some of the backtesting results are:
BTC/USD for longer time frame trading in the bear market for the last year.
APPLE for longer time frame trading in the bull market for the last 10 years.
EURO/USD for day trading in the neutral market for the last month.
BTC/USD for day trading in the bull market for the last 15 days.
APPLE for day trading in the neutral market for the last 2 days and 6 hours.
Intelligent Volume-weighted Moving Average (AI)Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The volume-weighted moving average (VWMA) is one of the most used indicators on the planet, yet no one really knows what pair of volume-weighted moving average lengths works best in combination with each other. A reason for this is because no two VWMA lengths are always going to be the best on every instrument, time-frame, and at any given point in time.
The "Intelligent Volume-weighted Moving Average" solves the moving average problem by adapting the period length to match the most profitable combination of volume-weighted moving averages in real time.
How does the Intelligent Volume-weighted Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these volume-weighted moving averages will be the most profitable.
Can we learn from the Intelligent Volume-weighted Moving Average?
There are many lessons to be learned from the Intelligent VWMA. Most will come with time as it is still a new concept. Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
This indicator does not change what has already been plotted and does not repaint in any way shape or form which means it is excellent for trading in real-time!
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The volume-weighted moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of VWMA lengths is between 5 to 40.
The black crosses can be turned off in the settings panel.
Test this indicator!
I am also publishing tools that can be used to back-test this indicator and understand what period length is currently being used.
There will be many more updates to come so stay tuned!
Updated documentation and access to this indicator can be found at www.kenzing.com
Intelligent Exponential Moving Average (AI)Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Exponential Moving Average (EMA) is one of the most used indicators on the planet, yet no one really knows what pair of exponential moving average lengths works best in combination with each other.
A reason for this is because no two EMA lengths are always going to be the best on every instrument, time-frame, and at any given point in time.
The "Intelligent Exponential Moving Average" solves the moving average problem by adapting the period length to match the most profitable combination of exponential moving averages in real time.
How does the Intelligent Exponential Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these exponential moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent EMA. Most will come with time as it is still a new concept. Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The exponential moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of exponential moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
Intelligent Moving Average (AI)
Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Moving Average is the most used indicator on the planet, yet no one really knows what pair of moving average lengths works best in combination with each other.
A reason for this is because no two moving averages are always going to be the best on every instrument, time-frame, and at any given point in time.
The " Intelligent Moving Average " solves the moving average problem by adapting the period length to match the most profitable combination of moving averages in real time.
How does the Intelligent Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent Moving Average. Most will come with time as it is still a new concept.
Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
