Rug Pull DetectorOverview
Have you ever wondered why tickers have such erratic movements that seemingly come from nowhere? These "rug pull" events happen quite often and can catch even the most seasoned traders off-guard.
Unlike most other indicators which rely on historical data to make inferences about future price movements, the Rug Pull Detector (RPD) enables you to take a glimpse into market makers' delta-neutral hedging in real-time.
Market makers by nature must be delta-neutral which means that they cannot position themselves to profit from providing liquidity (either long or short). Liquidity provided to the short or long side must end up in a stock purchase or sale to neutralize the trade.
Volatile movements in a ticker's price movement most often result directly after a period of extremely low volatility. These volatile movements are very often "rug pulled" which ends up reverting the ticker back to the price at which the event first occurred. RPD shows these events in real-time. This knowledge can be used to help determine the most probable near-future direction a ticker will gravitate towards after a rug pull event occurs.
Usage
RPD works on any ticker and on any timeframe and can be used as a tool in determining an exit price for a trade. Vertical shading on the chart indicates a warning signal that a rug pull event may be about to kick-off. Once a rug pull event has occurred and is confirmed, a blue label will appear on the chart with a price. A line is then drawn from the bar at which the event occurred and is extended to each subsequent bar until the price is reached once more; thus concluding the event. Furthermore, red or green shading will be present to easily visually identify rug pull events on the chart and whether they are risks to the downside (red) or upside (green). RPD is broken down into 2 main types of events:
Active Event - These events are characterized by a red or green shading and a blue price line.
Dormant Event - These events do not have shading but are still identifiable via a blue price line. Active events that are superseded by newer events will become dormant.
Active events tend to have a higher chance to return to the initial price point and tend to arrive there quicker.
Dormant events have a slightly lower chance to return to the initial price point and may take longer to arrive there.
Please note:
This indicator has no way of telling the exact amount of time that will pass before the ticker returns to the identified price; however, in more cases than not - the ticker will return to that price within a reasonable amount of time relative to the timeframe you are viewing.
There is a small chance any single event will never conclude. These are anomalies and do occur on occasion.
Using RPD alongside tools such as the RSI, Anchored VWAP, or other trend-based indicators will help determine when the ticker's price might be about to pivot and head back towards the identified price point.
Seeing is Believing:
SPY 1D downside rug-pull
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AAPL 15s downside and upside rug-pulls
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AMD 2D downside rug-pull
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VIX 1h downside and upside rug-pulls
Want to see more? Check out my recent Ideas for more examples of the Rug Pull Detector in action.
Disclaimer:
Any information in relation to the Rug Pull Detector does not constitute any financial, investment, or trading advice. Trade or invest at your own risk.
Beyondtechnicalanalysis
MACD 50x Leveraged Long Strategy Results with Real Equity Hello there.
I was looking for a way to simulate leveraged transactions in Tradingview and this script came out.
You can examine the equity graph without looking at the strategy results.
Thus, the facts will come to light.
Strategy parameters:
Adding margin: Forbidden or not specified. (Add Margin : No)
Position size: (for each trade) 1%
Stop-Loss: (2%)
Long: macd crossover
Exit: macd crossunder
Or ofc touching the stop-Loss value as predicted.
Warning: This strategy simulation is for Long direction only.
Regards.
Noldo Blockchain Cryptocurrency Indicator
Hello, this script has the same logic as Noldo CFTC COT Forex Indicator :
And Noldo CFTC COT Commodities Indicator :
*
Script briefly calculates the period length between two signals of Pivot Reversal Strategy when new signal arrives and allows us to see relative Blockchain data and price changes of Major Cryptocurrencies over that automatic length.
This saves us from the hassle and time wasting of searching for a reference point.
Usage
This script works only on all Bitcoin / U.S Dollar pairs and futures.
It only works on 1W graphics.
ICOT data are pulled via Quandl
NOTE :
Since blockchain data is very votalile, 7-day ema values are adjusted to take into account.
Regards.
Noldo CFTC COT Commodities IndicatorHi.
Hello, this script has the same logic as Noldo CFTC COT Forex indicator :
It is the version for the future markets.
Major future assets are the subject.
Usage
This script works only on SPGSCI (S&P Goldman Sachs Commodity Index).
You must open SPGSCI :
www.tradingview.com
It only works on 1W graphics.
Because COT data is announced on Tuesday, it will cause repaint every Tuesday.
However, since it is a terminal, this factor is not strong enough to affect your decisions.
For use, you should open the bottom panel, go a little to the right in the history section and enlarge the panel you have opened.
The terminal will take its form in the presentation and provide analysis on the big screen.
COT data are pulled via Quandl.
Regards.
Funamental and financialsEarnings and Quarterly reporting and fundamental data at a glance.
A study of the financial data available by the "financial" functions in pinescript/tradingview
As far as I know, this script is unique. I found very few public examples of scripts using the fundamental data. and none that attempt to make the data available in a useful form
as an indicator / chart data. The only fitting category when publishing would be "trend analysis" We are going to look at the trend of the quarterly reports.
The intent is to create an indicator that instantly show the financial health of a company, and the trends in debt, cash and earnings
Normal settings displays all information on a per share basis, and should be viewed on a Daily chart
Percentage of market valuation can be used to compare fundamentals to current share price.
And actual to show the full numbers for verification with quarterly reporting and debuggging (actual is divided by 1.000.000 to keep numbers readable)
Credits to research study by Alex Orekhov (everget) for the Symbol Info Helper script
without it this would still be an unpublished mess, the use of textboxes allow me to remove many squiggly plot lines of fundamental data
Known problems and annoyances
1. Takes a long time to load. probably the amount of financial calls is the culprit. AFAIK not something i can to anything about in the script.
2. Textboxes crowd each other. dirty fix with hardcoded offsets. perhaps a few label offset options in the settings would do?
3. Only a faint idea of how to put text boxes on every quarter. Need time... (pun intended)
Have fun, and if you make significant improvements on this, please publish, or atleast leave a comment or message so I can consider adding it to this script.
© sjakk 2020-june-08
Autonomouscript
Hello friends, in this script, hand drawing and loyalty to terminals are minimized.
***FEATURES
1 - Rational Auto Support and Resistance Levels
NOTE : For 1W TF , you can take 0.000 - 1.000 for 1 area , i didn't find to necessary to autoplot this condition because of between levels are so large and for long term.
Multi time-frame
In small time frames, unreasonable support eliminates resistance levels.
Suitable for every pair.
If the prices change by region, automatic drawing is made in the new region and given to the screen.
Automatic Plotting Feature
Rational Levels
2 - Auto Risk/Reward Ratio Calculator
Calculations are made according to support and resistance in less than 4 hours TF.
The opposite is true for Short.
2 methods in 4 hours and larger time frames and two zones specified:
1. Price < 0.618 Level :
Long Position Calculation : From Current Support to 0.618 Level
Short Position Calculation: From Current Resistance to 0.000 Level
2. Price > 0.618 Level
Long Position Calculation :Support and 1.000 Level .
Short Position Calculation : Resistance and 0.000 Level
Risk/Reward Ratio Calculation Examples (TF = Timeframe) :
1 - TF < 4H and Long - Short Risk/Reward Ratio Calculation :
For Long Position :
For Short Position :
2 - TF > 4H and Long-Short Risk/Reward Ratio Calculation :
For Long Position :
For Short Position :
NOTE :
Some algorithms have been added to make this formulation accurate and safe.
Therefore, Stop-Loss can be flexed slightly under the support or on the resistance in short position.
The target does not change.
Staying on the safe side calculates the risk / reward ratio for the worst possible odds.
*** Since stop-loss levels are chosen close to support and resistance and determine financial leverage, there is absolutely no need for stop-loss, the investor can determine himself according to the risk / reward ratio.
Generally, the support is slightly lower for long and the resistance slightly reasonable for short.
3 - Moving Averages and Cloud
a-) Slow Moving Average (Fuchsia)
Uses Autonomous LSTM moving average for external timeframes of 1W, Relativity moving average for timeframes 1W and above.
NOTE : They are built on price instead of Stochastic Money Flow Index.
And because they are price based
The High-Low Selection Algorithm has been removed.
For more information :
Autonomous LSTM =>
Relativity =>
b-) Signal Moving Average (Blue)
I just added this average after long tests.
It was created based on the relative states of the Relativity and Autonomous LSTM and candle states.
It is very fast and adaptive but, you should definitely use the risk / reward ratio if you are going to trade just by looking at it.
c_) Cloud :
It is the region between fast and slow moving average.
Cloud Color : Red for : crossunder(price , signal ma) and Green for : crossover(price,signal ma)
d-) Plotarrows :
Plotted after crossover and crossunder closings to inform the intersection of the two adaptive moving averages.
e*) Triangle Shapes :
They only reports when the moving average of the signal is long and short. And cloud color is same but without risk/reward radio rule.Rules :
Blue : Long Condition with Long Risk/Reward Ratio < 2.5
Orange : Short Condition with Short Risk/Reward Ratio < 2.5
Green : Long Condition with Long Risk/Reward Ratio >= 2.5
Red : Short Condition with Short Risk/Reward Ratio >= 2.5
4 - INFOPANEL - Trader Panel
- Calculation results of Risk / Reward Ratios for each bar for Long and Short Position
- Current Support and Resistance Levels
- Percentage change of the price moving average (period = signal period) only in the signal period
* Percentage change of the volume moving average (period = signal period) only in the signal period
* Supply and Demand Bias :
They are given separately for both long and short (Bull - Bear).
It is the reflection of the quantum formulas that form the core of relativity.
Nevertheless, the signal moving averages data price and volume are also above in InfoPanel.
Important Note : Two starred rules are given to investors and traders to choose between the following facts :
Increasing Volume __ Increasing Price = > Healthy Bear Session
Increasing Price __ Increasing Volume = > Healthy Bull Session
Decreasing Volume __ Increasing Price = > Bulls are weakening
Decreasing Volume __ Decreasing Price = > Bears are weakening
*** SUMMARY AND USAGE :
NOTES
It's definitely not just for signals,
all data in the system
evaluating according to the current economic agenda,
carry out your trade like that.
You can zoom in using the zoom in zoom out feature (+) of Tradingview, especially in small timeframes.
And according to the signal average of the price, cloud coloring was made in green and red.
Because in some cases, infopanel can intervene and block small triangles.
Alerts :
There is no need for any precise alert.
In case of need, users can set alarms at support and resistance levels.
NOTE :
In the design and basic cases of support and resistance levels,inspired by borserman's this script:
Special thanks to him.
Last Note and Reminder
This script may will be updated in terms of design and simplification if deemed necessary.
Best regards.
Live Mini Terminal 5 : MSCI Emerging Countries Change DataThis script displays relative data changes occurring in the adjustable period and/or adaptive automatic period in MSCI Emerging Countries against U.S Dollar.
Concept and design were inspired by the data terminals used by commercial traders.
Period selection can be set in the menu.
This script uses the adaptive period algorithm used by Autonomous LSTM and Relativity scripts.
Or you can set the period manually from the menu.
For more information about adaptive period:
This script works only for 1 day (1D) and 1 week (1W) time frames.
The most efficient time frame is 1 week (1W) because of countries' different time-zones .
Features
Value changes on a percentage basis (%) .
10-year government bond yields of the countries are given in the information panel.
In the information panel, the percentage values of the 10-year interest rates of the countries according to the adaptive period or the standard adjustable period are given.
INSTRUMENTS
DXY : U.S Dollar Index
BRL : Brazilian Real
CNH : Off-Shore Chineese Yuan (RMB)
INR : Indian Rupee
IDR : Indonesian Rupiah
RUB : Russian Ruble
TRY : Turkish Lira
MXN : Mexican Peso
ZAR : South African Rand
TWD : Taiwan New Dollar
PLN : Polish Zloty
Info Panel
NOTE :
* In Mexico and Russia, 10-year bond yields were not taken into account as there was no correct provision.
If data added to the site, it will be added to the system and updated.
Info Panel List
US10Y : US Government Bonds 10 Year Yield (%) and percentage change over the specified period.
BR10Y : Brazil Government Bonds 10 Year Yield (%) and percentage change over the specified period.
CN10Y : China Government Bonds 10 Year Yield (%) and percentage change over the specified period.
IN10Y : India Government Bonds 10 Year Yield (%) and percentage change over the specified period.
ID10Y : Indonesia Government Bonds 10 Year Yield (%) and percentage change over the specified period.
NZ10Y : New Zealand Government Bonds 10 Year Yield (%) and percentage change over the specified period.
TR10Y : Turkey Government Bonds 10 Year Yield (%) and percentage change over the specified period.
SA10Y : South Africa Government Bonds 10 Year Yield (%) and percentage change over the specified period.
TW10Y :Taiwan Government Bonds 10 Year Yield (%) and percentage change over the specified period.
PL10Y :Poland Government Bonds 10 Year Yield (%) and percentage change over the specified period.
USAGE
The script can be used as an indicator by putting it under the chart as shown above.
It is necessary to enlarge to see clearly.
Since it is not often looked at,such use is the best method for healthy interpretation.
Regards.
Live Mini Terminal 2 : Relative USD Based Stock Markets Change This script displays relative data changes occurring in the adjustable period and/or adaptive automatic period in various stock markets.
It was inspired by the data terminals used by commercial traders.
Period selection can be set in the menu.
This script uses the adaptive period algorithm used by Autonomous LSTM and Relativity scripts.
Or you can set the period manually from the menu.
For more information about adaptive period this script uses:
This script works only for 1 day (1D) and 1 week (1W) time frames.
The most efficient time frame is 1 week because of different time-zones (1W) .
Features
Value changes on a percentage basis (%)
Stock exchange values are calculated in dollar terms.
Due to the advantage of movement, future data were chosen instead of spot values on the required instruments.
INSTRUMENTS
Usa : S&P 500 Futures
Japan: Nikkei 225 Futures
England: United Kingdom (FTSE) 100
Australia: Australia 200
Canada: S&P / TSX Composite
Switzerland: Swiss Market Index
New Zealand: NZX 50 Index
China: SSE Composite (000001)
Denmark: OMX Copenhagen 25 Index
Hong-Kong: Hang Seng Index Futures
India: Nifty 50
Norway: Oslo Bors All Share Index
Russia: MOEX Russia Index
Sweden: OMX Stockholm Index
Singapore: Singapore 30
Turkey: BIST 100
South Africa: South Africa Top 40 Index
Spain: IBEX 35
France: CAC 40
Italy: FTSE MIB Index
Netherlands: Netherlands 25
Germany : DAX
USAGE
The script can be used as an indicator by putting it under the chart as shown above.
It is necessary to enlarge to see clearly.
Since it is not often looked at,such use is the best method for healthy interpretation.
Live Mini Terminal 1 : Relative General Data ChangeThis script displays relative data changes occurring in the adjustable period and/or adaptive automatic period in various markets.
It was inspired by the data terminals used by commercial traders.
Period selection can be set in the menu.
This script uses the adaptive period algorithm used by Autonomous LSTM and Relativity scripts.
Or you can set the period manually from the menu.
For more information about adaptive period this script uses:
This script works only for 1 day (1D) and 1 week (1W) time frames.
Since COT data is used, the most efficient time frame is 1 week (1W) .
Features
Value changes on a percentage basis (%)
Commitment of Traders position changes on a percentage basis :
Net position percentage is calculated as Short - Long and there is no inverse relationship.
Direct relationship is provided.
Due to the advantage of movement, future data were drawn instead of spot values on the required instruments.
INSTRUMENTS
US10Y : U.S Government Bonds 10 Year Yields
VIX : CBOE Volatility Index (S&P 500 VIX )
GOLD : XAUUSD : Gold
WTI : West Texas Intermediate : USOIL , Crude Oil
BCO : Brent Crude Oil : UKOIL , Light Crude Oil
SP500 : S&P 500 Index
DXY : US Dollar Index
TIO : Iron Ore : Iron Ore %62 Fe CFR China Futures
XAG : SI : Silver
NG : Natural Gas
JPYUSD : Japanese Yen
EURUSD : Euro/Dollar
Position Change InfoPanel
10 US T-Bond positions are used because there is no position equivalent in US10Y.
In other instruments, the corresponding position provisions are written and their changes are calculated.
USAGE
The script can be used as an indicator by putting it under the chart as shown above.
It is necessary to enlarge to see clearly.
Since it is not often looked at,
such use is the best method for healthy interpretation.
Macroeconomic Artificial Neural Networks
This script was created by training 20 selected macroeconomic data to construct artificial neural networks on the S&P 500 index.
No technical analysis data were used.
The average error rate is 0.01.
In this respect, there is a strong relationship between the index and macroeconomic data.
Although it affects the whole world,I personally recommend using it under the following conditions: S&P 500 and related ETFs in 1W time-frame (TF = 1W SPX500USD, SP1!, SPY, SPX etc. )
Macroeconomic Parameters
Effective Federal Funds Rate (FEDFUNDS)
Initial Claims (ICSA)
Civilian Unemployment Rate (UNRATE)
10 Year Treasury Constant Maturity Rate (DGS10)
Gross Domestic Product , 1 Decimal (GDP)
Trade Weighted US Dollar Index : Major Currencies (DTWEXM)
Consumer Price Index For All Urban Consumers (CPIAUCSL)
M1 Money Stock (M1)
M2 Money Stock (M2)
2 - Year Treasury Constant Maturity Rate (DGS2)
30 Year Treasury Constant Maturity Rate (DGS30)
Industrial Production Index (INDPRO)
5-Year Treasury Constant Maturity Rate (FRED : DGS5)
Light Weight Vehicle Sales: Autos and Light Trucks (ALTSALES)
Civilian Employment Population Ratio (EMRATIO)
Capacity Utilization (TOTAL INDUSTRY) (TCU)
Average (Mean) Duration Of Unemployment (UEMPMEAN)
Manufacturing Employment Index (MAN_EMPL)
Manufacturers' New Orders (NEWORDER)
ISM Manufacturing Index (MAN : PMI)
Artificial Neural Network (ANN) Training Details :
Learning cycles: 16231
AutoSave cycles: 100
Grid
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 998
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Controls
Learning rate: 0.1000
Momentum: 0.8000 (Optimized)
Target error: 0.0100
Training error: 0.010000
NOTE : Alerts added . The red histogram represents the bear market and the green histogram represents the bull market.
Bars subject to region changes are shown as background colors. (Teal = Bull , Maroon = Bear Market )
I hope it will be useful in your studies and analysis, regards.
Whale Trading SystemThis script is an advanced version of the distributional blocks script.
In distributional buys and sells:
I used a high - low cloud filter, which makes it more prudent to sell the next sell higher for sells and to buy the next purchase lower for buys.
I also used the Stochastic Money Flow Index function because it also uses volume to separate regions.
The long period is 52 weeks, which is equal to one year,
The short period is one-fourth of its value, which is equal to a financial quarter.
Then the values calculated with these periods are calculated by stochastic - rsi logic within the function, giving us two averages and separating the regions according to crossovers and crossunders .
In buys and sales, the higher your next distributional position size makes your profit more .
In the old system, there was a confusion as it was not divided into zones.
Because we divide into zones here, zone changes are the last stop to free up existing positions, and you must reopen each time you change zones.
And I changed standard distribution days, depending on the price change and the histogram, as StochMFI also took into account the volume.
In this way, there is sustainability.
I am also sharing my educational idea that explains the logic of this system in more detail :
Now that we have been divided into regions, a maximum of 10 pieces will suffice us.
And the regional shifts will allow us to sell and buy all of our position size, and now we will feel much more comfortable.
The most timeframe I find most accurate are the weekly bars.
Even in the example, we see how we have benefited from the sharp drop in bitcoin, while the price is falling, and we have lowered the average with higher-weight purchases than the previous one.
In both buys and sales here, both the histogram intensities and the average of the purchases you have reduced with the transactions, or the earnings you have increased with the sales, guide you.
In areas with high volatility ,if we adjust our positions properly, even if we follow the changes in the region, we will get rid of those situations with few wounds and we will surely catch the trend!
NOTE : Crossover/crossunder and distributional buy/sell alerts added.
Best regards , Noldo.
Customizable MACD (how to detect a strong convergence)Helloooo traders
I wondered once if a MACD was based on an EMA/EMA/SMA or SMA/SMA/EMA (or WHATEVA/WHATEVA/WHATEVA).
Seems they're so many alternatives out there.
I decided to empower my audience more by choosing the type of moving averages you want for your MACD.
More options doesn't always mean better performance - but who knows - some might find a config that they like with it for their favorite asset/timeframe.
I added also a multi-timeframe component because I'm a nice guy ^^
Convergence is my BEST friend
An oscillator (like MACD) is to measure how strong a momentum is - generally, traders use those indicators to confirm a trend.
So understand that a MACD (or any other indicator not based on convergence ) won't likely be sufficient for doing great on the market.
Combined with your favorite indicator, however, you may get great results.
My indicators fav cocktail is mixing :
1) an oscillator (momentum confirmation)
2) a trendline/key level break (momentum confirmation)
3) adding-up on a different trading method but still converging with the first entry.
The reason I'm deep with convergence detection is because I'm obsessed with removing those fakeout signals. You know which ones I'm talking about :)
Those trades when the market goes sideways but our capital goes South (pun 100% intended) - 2 days later, the price hasn't changed much but some lost some capital due to fees, being overexposed, buying the top/selling the bottom of a range they didn't identify.
It's publicly known that ranges are the worst traders' enemy. It's boring, not fun, and .... end up moving in the direction we expected when we go to sleep or outside.
NO ONE/BROKER/EX-GF is tracking your computer - I checked also for mine as it happened for me way too often in the past.
I surely preferred blaming a few external unknown conditions than improving my TA back in the days #bad #dave
But my backtest sir...
Our backtests show what they're being told to show . A backtest without a stop-loss/hard exit logic will show incredible results.
Then trying that backtest with live trading is like in the Matrix movie - discovering the real world is tough and we must choose between the blue pill (learning how to evaluate properly risk/opportunity caught) and the red pill (increasing the position sizing, not setting a stop loss, holding the positions hoping for the best)
Last few words
Convergences aren't invented because it's cool to mix indicators with others. (it is actually and even fun)
They're created to remove most of the fakeouts . For those that can't be removed - a strong risk management would cut most of the remaining potential big losses.
No system works 100% of the time - so a convergence system needs a back-up plan in case the converged signal is wrong (could be stop-loss, hard exit, reducing position sizing, ...)
Wishing you the BEST and happy beginning of your week
Daveatt
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 ! "
Distribution Position Size Panel
This panel is an example position size panel that I prepared and I consider the rates reasonable.
I have prepared this panel so that the money allocated to the investment ends 14 consecutive signals.
The sum of the ratios is 100 units.
You can adjust your positions according to this panel.
The first steps are low rates.
If the phrases are strong, you can specify a position size from the lower digits.
Likewise, when you make a big profit, you can empty your profits in the lower steps.
In the event of a color change, you can return to the beginning or lower limit.
NOTE: This script is an auxiliary command to the distribution blocks script,
if you want to use another script, you can add distribution days to yours.
14 th stake does not appear in the preview, you need to reduce the size of the distribution blocks indicator slightly.
Rafael Zioni's examples of the panels helped a lot, thanks to him.
Stay tuned ! Regards , Noldo.
Distribution BlocksThis idea has been created by the combination of the two existing systems as a result of my efforts to create a distributional buying and selling guide that has plagued my head for a long time.
1st idea is Accumulation / Distribution Line :
2nd idea is Distribution Day :
These two ideas, the intellectual assistance of professional brokers, and my observations of cot data played a role in the formation of this idea.
Let's start.
No matter how often we divide our risk, both our minds are not comfortable and our capital may end at any moment, and if we do not use professional systems, our chances of success are 50 percent.
If we take this system as an aid to our classic systems, we can determine the amount of risk with those predictions and gradually trade.
If we don't use leverage and we have a little predictive ability, our chances of success go above 50 percent.
But for the first time, we can keep our first lot very low and increase the number of positions in the same order of orders (example: buy and buy and buy).
If we keep the first amount low, the folds won't hurt us.
When we catch up with the trend, purchases with larger position sizes than lower prices lower our average price, so that we can make a good profit when the rising trend starts.
By accepting the zone changes as the reset point just like in the martingale system, we enter the folds in the new zone with our first lot weight.
Although we cannot catch the trend, we determine the stoploss level by adding the first point we entered or the first point we entered and the commission cost.
In fact, this method is the method of buying and selling very large traders and producers, banks, pro-brokers, hedge funds and in other words the new popular phrase "whales".
Because if he trades otherwise, he cannot find buyers because his goods are too big.
I like the comfort of mind in this way.
Finally, your methods separating the negative and positive regions (macd, rsi, interpretation observation etc.)
the stronger you are, the higher your success rate.
I think the Accumulation Distribution method is very successful, but it can be adjusted for the period.
I can't wait to integrate my relativity system on this.
And when my deep learning series is over, I will integrate them on ANN series and share them publicly.
To start with, I can say briefly.
If your capital is 100:
(first lot + (increase multiplier * first lot) + (increase multiplier * increase multiplier * first lot) + .....) = 100
I tell you that you can have the same position in this series 10 - 15 times,
this will help you decide how small a position size is to be used as the starting rate and choose a low increment multiplier!
I think that this idea cannot be converted into strategy, because when our expectations come true, we may want to free all positions and start again.And I think that's better.
And in sudden movements and developments we take action with different expectations.
I'm going to talk about this script's calculations and profits on educational ideas.
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 BRENT CRUDE OIL (UKOIL) This script trained with Brent Crude Oil data including 7 basic indicators and 12 Guppy Exponential Moving Averages .
Details :
Learning cycles: 1
Training error: 0.006591 ( Smaller than 0.01 ! )
AutoSave cycles: 100
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
Note : Alerts added .
Special thanks to wroclai for his great effort.
Deep learning series will continue , stay tuned ! Regards.
ANN MACD GOLD (XAUUSD)This script aims to establish artificial neural networks with gold data.(4H)
Details :
Learning cycles: 329818
Training error: 0.012767 ( Slightly above average but negligible.)
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: 5
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 : Alarms added.
And special thanks to dear wroclai for his great effort.
Deep learning series will continue . 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 .
Dow Factor Stoch RSIThe indicator was generated by adding the Dow Factor to the Stochastic Relative Strength Index.( Stoch RSI )
The Dow factor is the effect of the correlation coefficient, which determines the relationship between volume and price, on the existing indicators.
With these codes we are able to integrate them numerically into the indicators.
For more information on the Dow factor, please see my indicator:
This code is open source under the MIT license. ( github.com )
My dow factor updates will continue.We adapted the indicators and saw successful results, now it is time to examine and develop the factor itself.
Stay tuned , best regards.
Dow Factor Relative Strength IndexThis script was written to create a new, rapid relative strength index inspired by the Dow Theory.
More info about Dow Theory : www.investopedia.com
According to the Dow Theory, volume should confirm market trends.
The correlation coefficient between prices and volume is negative in weakening trends and negative trends , positive in strengthening or positive trends.a factor was formed based on the correlation coefficient between volume and prices.
This factor was added to the relative strength index.
Period 5 is selected because the volume is very volatile and can be slow.
You can use the period you want, but I recommend the period as a minimum of 5.
It is suitable for all instruments and timeframes and thanks to its design, it provides control over gradual buying and selling points.
I haven't fully tested it, it's open to updates. For now, just use it to create ideas.
If I find it necessary,
I'll update after the tests.
If you have suggestions on these issues,
Leave your comments in the comment window.
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.
CBOE PCR Factor Dependent Variable Odd Generator This script is the my Dependent Variable Odd Generator script :
with the Put / Call Ratio ( PCR ) appended, only for CBOE and the instruments connected to it.
For CBOE this script is more accurate and faster than Dependent Variable Odd Generator. And the stagnant market odds are better and more realistic.
Do not use for timeframe periods less than 1 day.
Because PCR data may give repaint error.
My advice is to use the 1-week bars to gain insight into your analysis.
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
I hope it will help your work.Best regards!
