Conway's Game of Life [NOT AN INDICATOR]This is not an indicator, just for fun and testing out the new table functions.
Requires bar replay to calculate (quickly) one generation to the next.
A random pregen seed and a few other known seeds picked at random. The limited grid dimensions affect the outcome for some.
Search in scripts for "grid"
Auto Fib Speed Resistance Fans by DGTFibonacci Speed and Resistance Fan is an analytical drawing tool used to indicate the support and resistance levels of an existing trend and the price level at which possible changes in the trend may occur.
A Fibonacci Speed Resistance Fan consists of a trend line drawn between two extreme points - a trough and opposing peak or a peak and opposing trough - on which a set of sequential speed resistance lines are drawn above (which represents time) and below (which represents price). These lines are drawn based on time/price percentages of the distance between the beginning and the end of the trend line.
Speed resistance lines not only help to measure trend corrections but also measure the speed of a trend (the rate at which a trendline ascends or descends)
Traders can use the lines of the Fibonacci Speed and Resistance Fan to predict key points of resistance or support, at which they might expect price trends to reverse. Once a trader identifies patterns within a chart, they can use those patterns to predict future price movements and future levels of support and resistance. Traders use the predictions to time their trades. Key support and resistance levels tend to occur frequently at the 61.8-percent level on both uptrends and downtrends.
Please check for further details in the education post that I will share shortly after this publication :
Nobody appears to know whether Fibonacci tools work because markets exhibit some form of natural pattern or because many investors use Fibonacci ratios to predict price movements, making them a self-fulfilling prophecy.
█ Study OPTIONS
Auto Fibonacci Speed and Resistance Fan , the main aim of the study
- Pivot threshold can be adjusted via “Deviation” and “Depth” input options
- Historical Fans option will allow plotting of Speed and Resistance Fans on previous pivot high/lows
- Ability to set ALERTs for the Speed and Resistance Levels
- Price Grid Lines if extended it will result with Fib Retracement levels
- All lines, line levels are customizable, default values are set exactly to the same with the available Fib Speed and Resistance Fan drawing tool
Zig Zag – Derived from build-in Auto Fib Retracement with some customization options.
Example Usages :
Disclaimer :
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Tic Tac Toe (For Fun)Hello All,
I think all of you know the game "Tic Tac Toe" :) This time I tried to make this game, and also I tried to share an example to develop a game script in Pine. Just for fun ;)
Tic Tac Toe Game Rules:
1. The game is played on a grid that's 3 squares by 3 squares.
2. You are "O", the computer is X. Players take turns putting their marks in empty squares.
3. if a player makes 3 of her marks in a row (up, down, across, or diagonally) the he is the winner.
4. When all 9 squares are full, the game is over (draw)
So, how to play the game?
- The player/you can play "O", meaning your mark is "O", so Xs for the script. please note that: The script plays with ONLY X
- There is naming for all squears, A1, A2, A3, B1, B2, B3, C1, C2, C3. you will see all these squares in the options.
- also You can set who will play first => "Human" or "Computer"
if it's your turn to move then you will see "You Move" text, as seen in the following screenshot. for example you want to put "O" to "A1" then using options set A1 as O
How the script play?
it uses MinMax algorithm with constant depth = 4. And yes we don't have option to make recursive functions in Pine at the moment so I made four functions for each depth. this idea can be used in your scripts if you need such an algorithm. if you have no idea about MinMax algorithm you can find a lot of articles on the net :)
The script plays its move automatically if its turn to play. you will just need to set the option that computer played (A1, C3, etc)
if it's computer turn to play then it calculates and show the move it wants to play like "My Move : B3 <= X" then using options you need to set B3 as X
Also it checks if the board is valid or not:
I have tested it but if you see any bug let me know please
Enjoy!
scaled.orders [highwater]FOR EDUCATIONAL PURPOSES
There are multiple tools that allow you to place "scaled orders" on your exchange, namely Alertatron and Bybit Tools. This script is based on some Alertatron features, but you can use it for any grid like order placing strategy. Even if thats not your thing it's an example of how to use arrays in pinescript.
FROM PRICE - is the price to start your orders.
TO PRICE - is the price your orders will end.
SCALED TYPES :
LINEAR - will distribute orders evenly between from and to price.
EASE IN - will cluster orders closer to from price, then start to widen the gaps as you move closer to to price.
EASE OUT - will have wider gaps near from price, and start to cluster near to price.
EASE IN OUT - will cluster orders near both from price and to price.
COUNT - number of orders in each scaled order.
MACD histogram relative open/closePrelude
This script makes it easy to capture MACD Histogram open/close for automated trading.
There seems to be no "magic" value for MACD Histogram that always works as a cut-off for trade entry/exit, because of the variation in market price over time.
The idea behind this script is to replicate the view of the MACD graph we (humans) see on the screen, in mathematics, so the computer can approximately detect when the curve is opening/closing.
Math
The maths for this is composed of 2 sections -
1. Entry -
i. To trigger entry, we normalize the Histogram value by first determining the lowest and highest values on the MACD curves (MACD, Signal & Hist).
ii. The lowest and highest values are taken over the "Frame of reference" which is a hyperparameter.
iii. Once the frame of reference is determined, the entry cutoff param can be defined with respect to the values from (i) (10% by default)
2. Exit
To trigger an exit, a trader searches for the point where the Histogram starts to drop "steeply".
To convert the notion of "steep" into mathematics -
i. Take the max histogram value reached since last MACD curve flip
ii. Define the cutoff with reference to the value from (i) (30% by default)
Plots
Gray - Dead region
Blue - Histogram opening
Red - Histogram is closing
Notes
A good value for the frame of reference can be estimated by looking at the timescale of the graph you generally work with during manual trading.
For me, that turned out to be ~2.5 hours. (as shown in the above graph)
For a 3-minute ticker, frame of reference = 2.5 * 60 / 3 = 50
Which is the default given in this script.
Ultimately, it is up to you to do grid search and find these hyperparams for the stock and ticker size you're working with.
Also, this script only serves the purpose of detecting the Histogram curve opening/closing.
You may want to add further checks to perform proper trading using MACD.
CDC ActionZone V3 2020## CDC ActionZone V3 2020 ##
This is an update to my earlier script, CDC ActionZone V2
The two scripts works slightly differently with V3 reacting slightly faster.
The main update is focused around conforming the standard to Pine Script V4.
## How it works ##
ActionZone is a very simple system, utilizing just two exponential moving
averages. The 'Zones' in which different 'actions' should be taken is
highlighted with different colors on the chart. Calculations for the zones
are based on the relative position of price to the two EMA lines and the
relationship between the two EMAs
CDCActionZone is your barebones basic, tried and true, trend following system
that is very simple to follow and has also proven to be relatively safe.
## How to use ##
The basic method for using ActionZone is to follow the green/red color.
Buy when bar closes in green.
Sell when bar closes in red.
There is a small label to help with reading the buy and sell signal.
Using it this way is safe but slow and is expected to have around 35-40%
accuracy, while yielding around 2-3 profit factors. The system works best
on larger time frames.
The more advanced method uses the zones to switch between different
trading system and biases, or in conjunction with other indicators.
example 1:
Buy when blue and Bullish Divergence between price and RSI is visible,
if not Buy on Green and vise-versa
example 2:
Set up a long-biased grid and trade long only when actionzone is in
green, yellow or orange.
change the bias to short when actionzone turns to te bearish side
(red, blue, aqua)
(Look at colors on a larger time frame)
## Note ##
The price field is set to close by default. change to either HL2 or OHLC4
when using the system in intraday timeframes or on market that does not close
(ie. Cryptocurrencies)
## Note2 ##
The fixed timeframe mode is for looking at the current signal on a larger time frame
ie. When looking at charts on 1h you can turn on fixed time frame on 1D to see the
current 'zone' on the daily chart plotted on to the hourly chart.
This is useful if you wanted to use the system's 'Zones' in conjunction with other
types of signals like Stochastic RSI, for example.
NSDT Chart Background ColorThe chart background settings from Tradingview only allow you to select a color from the built-in color grid, which is limited. This feature adds the ability to change the chart background color "shading" which allows you many more color options to fit your needs.
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.
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 MACD (BTC)
Logic is correct.
But I prefer to say experimental because the sample set is narrow. (300 columns)
Let's start:
6 inputs : Volume Change , Bollinger Low Band chg. , Bollinger Mid Band chg., Bollinger Up Band chg. , RSI change , MACD histogram change.
1 output : Future bar change (Historical)
Training timeframe : 15 mins (Analysis TF > 4 hours (My opinion))
Learning cycles : 337
Training error: 0.009999
Input columns: 6
Output columns: 1
Excluded columns: 0
Grid
Training example rows: 301
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network
Input nodes connected: 6
Hidden layer 1 nodes: 8
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Learning rate : 0.6 Momentum : 0.8
More info :
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
MACD Cross GridShow across all timeframes (15 minute to 1 week) whether MACD has crossed up (blue) or down (orange).
Supertrend Grid 1.0See the current pair's Supertrend direction on 4 different timeframes at once, so you won't get caught with your pants down trading against the trend. Handy for quickly space-barring through a watchlist.
Default settings are (from top to bottom) Daily, 4H, 1H and 15M but these can be changed. Any suggestions, let me know.
Coloured Volume Grid 1.0Candles are coloured based on relative price and volume:
- If today’s closing price and volume are greater than (n) bars ago, color today’s volume bar green.
- If today’s closing price is greater than (n) bars ago but volume is not, color today’s volume bar lime.
- Similarly, if today’s closing price and volume is less than (n) bars ago, color today’s volume bar orange.
- If today’s closing price is less than (n) bars ago but volume is not, color today’s volume bar red.
The above logic in itself gives pretty remarkable considering how simple the idea is. I have added a multi-timeframe feature where the same logic is applied to 4 other timeframes. This way you can quickly be aware without having to check. There are four layers and the default settings show (from top to bottom) daily, 4h, 1h and 15m
All timeframes are adjustable in the settings.
FXMM Zones TF:M5Observe the price reaction in the zones of supply/demand from multiple timeframes. Original idea from Forex MoneyMap, Dynamic Fibonacci Grid etc.
NOTE: Only for M5 !















