RSI & Backed-Weighted MA StrategyRSI & MA Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators that work best together: the Relative Strength Index (RSI) and the Moving Average (MA). We're going to use the RSI as a trend-follower indicator, rather than a reversal indicator as most are used to. To the signals sent by the RSI, we'll add a condition on the chart's MA, filtering out irrelevant signals and considerably increasing our winning rate. This is a medium/long-term strategy. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RSI :
The RSI is one of the best-known and most widely used indicators in trading. Its purpose is to warn traders when an asset is overbought or oversold. It was designed to send reversal signals, but we're going to use it as a trend indicator by increasing its length to 20. The RSI formula is as follows :
RSI (n) = 100 - (100 / (1 + (H (n)/L (n))))
With n the length of the RSI, H(n) the average of days closing above the open and L(n) the average of days closing below the open.
MA :
The Moving Average is also widely used in technical analysis, to smooth out variations in an asset. The SMA formula is as follows :
SMA (n) = (P1 + P2 + ... + Pn) / n
where n is the length of the MA.
However, an SMA does not weight any of its terms, which means that the price 10 days ago has the same importance as the price 2 days ago or today's price... That's why in this strategy we use a RWMA, i.e. a back-weighted moving average. It weights old prices more heavily than new ones. This will enable us to limit the impact of short-term variations and focus on the trend that was dominating. The RWMA used weights :
The 4 most recent terms by : 100 / (4+(n-4)*1.30)
The other oldest terms by : weight_4_first_term*1.30
So the older terms are weighted 1.30 more than the more recent ones. The moving average thus traces a trend that accentuates past values and limits the noise of short-term variations.
PARAMETERS :
RSI Length : Lenght of RSI. Default is 20.
MA Type : Choice between a SMA or a RWMA which permits to minimize the impact of short term reversal. Default is RWMA.
MA Length : Length of the selected MA. Default is 19.
RSI Long Signal : Minimum value of RSI to send a LONG signal. Default is 60.
RSI Short signal : Maximum value of RSI to send a SHORT signal. Default is 40.
ROC MA Long Signal : Maximum value of Rate of Change MA to send a LONG signal. Default is 0.
ROC MA Short signal : Minimum value of Rate of Change MA to send a SHORT signal. Default is 0.
TP activation in multiple of ATR : Threshold value to trigger trailing stop Take Profit. This threshold is calculated as multiple of the ATR (Average True Range). Default value is 5 meaning that to trigger the trailing TP the price need to move 5*ATR in the right direction.
Trailing TP in percentage : Percentage value of trailing Take Profit. This Trailing TP follows the profit if it increases, remaining selected percentage below it, but stops if the profit decreases. Default is 3%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD with a timeframe set to 6h. Parameters are set as follows :
MA type: RWMA
MA Length: 19
RSI Long Signal: >60
RSI Short Signal : <40
ROC MA Long Signal : <0
ROC MA Short Signal : >0
TP Activation in multiple ATR : 5
Trailing TP in percentage : 3
ENTER RULES :
The principle is very simple:
If the asset is overbought after a bear market, we are LONG.
If the asset is oversold after a bull market, we are SHORT.
We have defined a bear market as follows : Rate of Change (20) RWMA < 0
We have defined a bull market as follows : Rate of Change (20) RWMA > 0
The Rate of Change is calculated using this formula : (RWMA/RWMA(20) - 1)*100
Overbought is defined as follows : RSI > 60
Oversold is defined as follows : RSI < 40
LONG CONDITION :
RSI > 60 and (RWMA/RWMA(20) - 1)*100 < -1
SHORT CONDITION :
RSI < 40 and (RWMA/RWMA(20) - 1)*100 > 1
EXIT RULES FOR WINNING TRADE :
We have a trailing TP allowing us to exit once the price has reached the "TP Activation in multiple ATR" parameter, i.e. 5*ATR by default in the profit direction. TP trailing is triggered at this point, not limiting our gains, and securing our profits at 3% below this trigger threshold.
Remember that the True Range is : maximum(H-L, H-C(1), C-L(1))
with C : Close, H : High, L : Low
The Average True Range is therefore the average of these TRs over a length defined by default in the strategy, i.e. 20.
RISK MANAGEMENT :
This strategy may incur losses. The method for limiting losses is to set a Stop Loss equal to 3*ATR. This means that if the price moves against our position and reaches three times the ATR, we exit with a loss.
Sometimes the ATR can result in a SL set below 10% of the trade value, which is not acceptable. In this case, we set the SL at 10%, limiting losses to a maximum of 10%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
Cari skrip untuk "黄金近20年走势"
5EMA BollingerBand Nifty Stock Scanner
What ?
We all heard about (well: over-heard) 5-EMA strategy. Which falls into the broader category of mean reversal type of trading setup.
What is mean reversal?
Price (or any time series, in fact) tries to follow a mean . Whenever price diverges from the mean it tries to meet it back.
It is empirically observed by some traders (I honestly don't know who first time observed it) that in Indian context specially, 5 Exponential Moving Average (5-EMA) works pretty good as that mean.
So whenever price moves away from that 5-EMA, it ultimately comes back and attain total nirvana :) Means: if price moved way higher than the 5EMA without touching it, then price will correct to meet it's 5-EMA and if price moved way lower, it will be uplifted to meet it's 5-EMA. Funny - but it works !
Now there are already enough social media coverage on this 5-EMA strategy/setup. Even TradingView has some excellent work done on these setups. Kudos to all those great souls.
So when we came to know about this, we were thinking what we should do for the community. Because it is well cover topic (specially in Indian context). Also, there are public indicators.
Then we thought why not come up with a scanner which will scan all the Nifty-50 constituent stocks and find out on the fly, real-time which all stocks are matching this 5-EMA setup and causing a Buy/Sell trade recommendation.
Hence here we are with the first version of our first scanner on the 5EMA setup (well it has some more masala than merely a 5-EMA setup).
Why?
Parts of why is already covered up.
Now instead of blindly following 5-EMA setup, we added the Bollinger band as well. Again: it's also not new. There are enough coverage in social media about the 5-EMA+BB strategy/setup. We mercilessly borrowed from all of these.
Suppose you have an indicator.
Now you apply the indicator in your chart. And then you need to (rock) and roll through your watchlist of Nifty-50 stocks (note: TradingView has no default watchlist of Nifty-50 stock by default - you have to create one custom watchlist to list all manually) to find out which all are matching the setup, need to take a note about the trade recomendations (entry, SL, target) and other stuffs like VWAP, Volume, volatility (Bollinger Band Width).
Not any more.
This scanner will track all the Nifty-50 stocks (technically: 40 stocks other than Banking stocks) and provide which one to Buy or Sell (if any), what's the entry, SL, target, where is the VWAP of the day, what's the picture in volume (high, low, rising, falling) and the implied volatility (using Bolling band width). Also it has a naive alerting mechanism as well.
In fact the code is there to monitor the (Future) OI also and all the OI drama (OI vs price and all the 4 stuffs like long build up, long unwinding, short covering, short buildup). But unfortunately, due to some limitations of the TradingView (that one can not monitor more than 40 `ta.security` call) we have to comment out the code. If you wish you can monitor only 20 stocks and enable the OI monitoring also (20 for stocks + 20 for their OI monitoring .. total 40 `ta.security` call).
How?
To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB.
Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB.
Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low.
Present bar's volume is compared with the previous bar's volume to know if it's rising or falling.
VWAP is also determined using `ta.vwap` built-in support of TradingView.
The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle).
Simple, but effective.
Customization
As usual the EMA setup (5 default), the BB setup (20 SMA with 1.5 standard deviation), we provided option wherther to include or exclude BB role in the 5-EMA setup (as we found out there are two schools of thought .. some people use BB some don't. Lets make all happy :))
We also provide options to choose other symbols using Settings if they wish so. We have the default 40 non banking Nifty stocks (why non-banking? - Bank Nifty is in ATH :) .. enough :)). But if user wishes can monitor others too (provided the symbol is there in TradingView).
Although we strongly recommend the timeframe as 30 minutes , you can choose what's fit you most.
The output of the scanner is a table. By default the table is placed in the right-bottom (as we are most comfortable with that). However you can change per your wish. We have the option to choose that.
What is unique in it ?
This is more of an indicator. This is a scanner (of Nifty-50 stocks). So you can apply (our recommendation is in 30m timeframe) it to any chart (does not matter which chart it is) and it will show every 30 mins (which is also configurable) which all stocks (along with trade levels) to Buy and Sell according to the setup.
It will ease your trading activity.
You can concentrate only on the execution, the filtering you can leave it to this one.
Limitations
There is a build in limitation of the TradingView platform is that one can call only upto 40 securities API. Not beyond that. So naturally we are constraint by that. Otherwise we could monitor 190 Nifty F&O stocks itself.
30m is the recommended timeframe. In very lower (say 5m) this script tends to go out of heap (out of memory). Please note that also.
How to trade using this?
Put any chart in 30m (recommended) timeframe.
Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard).
This will provide the Buy (shown in green color) or Sell (shown in red color) recommendations in a table, at every 30m candle closing.
Note the volume and BB width as well.
Wait for at least 2 5-minutes candles to close above/below the recommended level .
Take the trade with the SL and target mentioned.
Mentions
@QuantNomad. The whole implementation concept we mercilessly borrowed from him, even some of his code snippet we took it (after asking him through one of his videos comment section and seeking explicit permission which he readily granted within an hour). Thank You sir @QuantNomad. Indebted to you.
Monika (Rawat) ji: for reviewing, correcting, providing real time examples during live market hours, often compromising her own trading activities, about the effectiveness and usefulness of this setup. Thank You madam ji. Indebted to you.
There are innumerable contents in social media about this. Don't even know whom all we checked. Thanks to all of them.
Happy Trading (in stocks - isn't enough of Indices already?)
Disclaimer
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
Hull Suite Oscillator - Normalized | IkkeOmarThis script is based off the Hull Suite by @InSilico.
I made this script to provide and calculate the Hull Moving Average (HMA) based on the chosen variation (HMA, TMA, or EMA) and length to then normalize the HMA values to a range of 0 to 100. The normalized values are further smoothed using an exponential moving average (EMA).
The smoothed oscillator is plotted as a line, where values above 80 are colored red, values below 20 are colored green, and values between 20 and 80 are colored blue. Additionally, there are horizontal dashed lines at the levels of 20 and 80 to serve as reference points.
Explanation for the code:
The script uses the close price of the asset as the source for calculations. The modeSwitch parameter allows selecting the type of Hull variation: Hma, Thma, or Ehma. The length parameter determines the calculation period for the Hull moving averages. The lengthMult parameter is used to adjust the length for higher timeframes. The oscSmooth parameter determines the lookback period for smoothing the oscillator.
There are three functions defined for calculating different types of Hull moving averages: HMA, EHMA, and THMA. These functions take the source and length as inputs and return the corresponding Hull moving average.
The Mode function acts as a switch and selects the appropriate Hull variation based on the modeSwitch parameter. It returns the chosen Hull moving average.
The script calculates the Hull moving averages using the selected mode, source, and length. The main Hull moving average is stored in the _hull variable, and aliases are created for the main Hull moving average (HULL), the main Hull value (MHULL), and the secondary Hull value (SHULL).
To create the normalized oscillator values, the script finds the highest and lowest values of the Hull moving average within the specified length. It then normalizes the Hull values to a range of 0 to 100 using a formula. This normalized oscillator represents the strength of the trend.
To smooth out the oscillator values, an exponential moving average is applied using the oscSmooth parameter.
The smoothed oscillator is plotted as a line chart. The line color is determined based on the oscillator value using conditional statements. If the oscillator value is above or equal to 80, the line color is set to red. If it is below or equal to 20, the color is green. Otherwise, it is blue. The linewidth is set to 2.
Additionally, two horizontal reference lines are plotted at levels 20 and 80 for visual reference. They are displayed in gray and dashed style.
Anchored SMAThis is not your usual single moving average (SMA) indicator. It is an anchored SMA indicator. The anchored SMA does what other SMAs cannot--it stays at an anchored timeframe and presents that SMA relative to the timeframe you are in. For example, standard SMA indicators adjust to the timeframe you are viewing in your chart. So if you set it to a 20 day SMA while in the 1 Day timeframe, when you switch to the 5 minute timeframe, your 20 day SMA now becomes a 100 minute SMA indicator--that is it is only calculating the SMA for 20 ticks at 5 minutes each rather than holding the 20 day indicator at the higher timeframe. However, with the anchored SMA, the indicator would have held at the 20 day SMA while you were in the 5 minute timeframe.
The default setting is for the anchored SMA is the five day SMA. This can be adjusted in the settings to be any amount of ticks in any timeframe you choose from 1 minute to 1 week. The indicator does not hold accurately at timeframes outside of this range. The accompanying chart is the SPX in the 15 minute timeframe with the default anchored SMA settings in blue and the standard 200 tick SMA in black. Now, you could manually adjust the ticks to 130 SMA to fit the same blue line, but why do so when the anchored SMA does it for you?
This brings us to a very important note--this indicator is set to standard market hours at 6.5 hours per day. This means this indicator would not give the same results in markets with different hours, such as futures, FOREX, or Crypto markets. This only holds for equity markets. However, that is not to say it cannot be used in these other markets, it's that it wouldn't be the same result. Anyway, enjoy!
[blackcat] L3 Candle Skew 3821 TraderLevel 3
Background
By modeling skew to produce long and short entry points.
Function
The concept of skew comes from physics and statistics, and is used in market technical analysis to reflect the expectation of future stock price distribution. Because the return distribution of stocks in the trend market has skew (Skew), it is reasonable to judge the trend continuity according to the historical and current skew. It is precisely because the stock price rises that there is a skew. The greater the strength of the rise, the greater the angle of inclination and the greater the skew. The degree of this upward or downward slope in the statistical distribution of stock prices is defined as skew. Through the size of skew, we can know the direction, inertia and extent of the stock's rise or fall, and find stocks with a high probability of quick profit. The technical indicator introduced today is a simplified but effective stock price skew model used to generate buying and selling points.
The principle of this technical indicator is based on the success rate test results of different moving averages corresponding to different skews as follows:
10 trading cycles profit 5% success rate (%)
5 period moving average 10 period moving average 20 period moving average 30 period moving average 60 period moving average
skew>=0 51.36 52.26 52.65 52.55 52.08
skew>=0.5 55.44 58.06 60.56 62.37 65.66
skew>=1 59.72 63.06 67.07 69.78 70.62
skew>=1.5 63.01 67.08 71.61 72.9 70.61
skew>=2 65.53 70.22 74.18 73.76 70.12
skew>=2.5 67.89 72.93 75.32 73.66 68.92
skew>=3 70.07 75.32 75.69 72.54 67.45
skew>=3.5 71.85 77.05 75.32 73.63 63.82
skew>=4 73.6 78.06 74.19 68.96 59.91
skew>=4.5 76.04 78.56 72.85 69.55 49.24
skew>=5 77.44 78.88 71.58 67.28 51.69
skew>=5.5 78.97 78.39 70.33 64.31 49.7
skew>=6 79.68 78.07 68.82 61.65 53.57
Table 1
As can be seen from the above table, with the increase of the 5-period and 10-period moving average skew values, the success rate is increasing, but after the 20- and 30-period moving average skew values increase to an upper bound, it shows a downward trend. When the skew of the 20-period and 30-period moving averages is greater than 0.5, the 10-period profit of 5% is above 60%, and when it is greater than 1.5, the success rate can reach above 70%. The larger the 5-period moving average skew, the higher the success rate, but often because the short-term skew is too large, the stock price has risen rapidly to a high level, and chasing up is risky, which is not suitable for the investment habits of most people, so prudent investors may like to do swings. Investors may wish to pay more attention to the skew of the 20-period and 30-period moving averages. Based on the above analysis, as a short-term trading enthusiast, I need to choose the 5-period and 10-period moving average skew, and consider the medium-term trend as a compromise, and I also need to consider the 20-period moving average skew. Finally, according to the principle of personal preference, I chose 3 groups of periods based on Fibonacci magic numbers: 3 periods, 8 periods, 21 periods, and skews that take into account both short-term and mid-line trends. So, I named this indicator number 3821 as a distinction.
002084 1D from TradingView
BTCUSDT 1H from TradingView
Tesla 1D from TradingView
[APD] Sharegenius Swing Trading StrategyThis script plots GTT Price , Target Prices , Buy Zone , Target Zone and Information Dashboard according to Sharegenius Swing Trading Strategy. SST is for Swing Trading.
👉🏻 Strategy by Mahesh Kaushik -
1️⃣ Track the 20-Day Low of the instrument.
2️⃣ Create a GTT order which is 5% above 20 DL.
3️⃣ If the share makes a new 20 DL before getting purchased, then update your GTT order to be 5% above the new 20 DL.
4️⃣ Next GTT will be started when the average price falls by 10%. (GTT will be created as 5% above the last 20 DL or Buy on 10%, 20%, 30% fall in average price.)
5️⃣ Sell target is 5% of the average price. Sell all units or Set sell target on buy price.
6️⃣ No stop loss is needed as we buy when the stock falls.
👉🏻 Note:-
Trade in fundamentally good stocks & strong stocks those are outperforming index because we do not take stop loss in this strategy.
DISCLAIMER:- This Script is for educational purposes only. Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security or investment.
Real Woodies CCIAs always, this is not financial advice and use at your own risk. Trading is risky and can cost you significant sums of money if you are not careful. Make sure you always have a proper entry and exit plan that includes defining your risk before you enter a trade.
Ken Wood is a semi-famous trader that grew in popularity in the 1990s and early 2000s due to the establishment of one of the earliest trading forums online. This forum grew into "Woodie's CCI Club" due to Wood's love of his modified Commodity Channel Index (CCI) that he used extensively. From what I can tell, the website is still active and still follows the same core principles it did in the early days, the CCI is used for entries, range bars are used to help trader's cut down on the noise, and the optional addition of Woodie's Pivot Points can be used as further confirmation of support and resistance. This is my take on his famous "Woodie's CCI" that has become standard on many charting packages through the years, including a TradingView sponsored version as one of the many stock indicators provided by TradingView. Woodie has updated his CCI through the years to include several very cool additions outside of the standard CCI. I will have to say, I am a bit biased, but I think this is hands down one of the best indicators I have ever used, and I am far too young to have been part of the original CCI Club. Being a daytrader primarily, this fits right in my timeframe wheel house. Woodie designed this indicator to work on a day-trading time scale and he frequently uses this to trade futures and commodity contracts on the 30 minute, often even down to the one minute timeframe. This makes it unique in that it is probably one of the only daytrading-designed indicators out there that I am aware of that was not a popular indicator, like the MACD or RSI, that was just adopted by daytraders.
The CCI was originally created by Donald Lambert in 1980. Over time, it has become an extremely popular house-hold indicator, like the Stochastics, RSI, or MACD. However, like the RSI and Stochastics, there are extensive debates on how the CCI is actually meant to be used. Some trade it like a reversal indicator, where values greater than 100 or less than -100 are considered overbought or oversold, respectively. Others trade it like a typical zero-line cross indicator, where once the value goes above or below the zero-line, a trade should be considered in that direction. Lastly, some treat it as strictly a momentum indicator, where values greater than 100 or less than -100 are seen as strong momentum moves and when these values are reached, a new strong trend is establishing in the direction of the move. The CCI itself is nothing fancy, it just visualizes the distance of the closing price away from a user-defined SMA value and plots it as a line. However, Woodie's CCI takes this simple concept and adds to it with an indicator with 5 pieces to it designed to help the trader enter into the highest probability setups. Bear with me, it initially looks super complicated, but I promise it is pretty straight-forward and a fun indicator to use.
1) The CCI Histogram. This is your standard CCI value that you would find on the normal CCI. Woodie's CCI uses a value of 14 for most trades and a value of 20 when the timeframe is equal to or greater than 30minutes. I personally use this as a 20-period CCI on all time frames, simply for the fact that the 20 SMA is a very popular moving average and I want to know what the crowd is doing. This is your coloured histogram with 4 colours. A gray colouring is for any bars above or below the zero line for 1-4 bars. A yellow bar is a "trend bar", where the long period CCI has been above/below the zero line for 5 consecutive bars, indicating that a trend in the current direction has been established. Blue bars above and red bars below are simply 6+n number of bars above or below the zero line confirming trend. These are used for the Zero-Line Reject Trade (explained below). The CCI Histogram has a matching long-period CCI line that is painted the same colour as the histogram, it is the same thing but is used just to outline the Histogram a bit better.
2) The CCI Turbo line. This is a sped-up 6 period CCI. This is to be used for the Zero-Line Reject trades, trendline breaks, and to identify shorter term overbought/oversold conditions against the main trend. This is coloured as the white line.
3) The Least Squares Moving Average Baseline (LSMA) Zero Line. You will notice that the Zero Line of the indicator is either green or red. This is based on when price is above or below the 25-period LSMA on the chart. The LSMA is a 25 period linear regression moving average and is one of the best moving averages out there because it is more immune to noise than a typical MA. Statistically, an LSMA is designed to find the line of best fit across the lookback periods and identify whether price is advancing, declining, or flat, without the whipsaw that other MAs can be privy to. The zero line of the indicator will turn green when the close candle is over the LSMA or red when it is below the LSMA. This is meant to be a confirmation tool only and the CCI Histogram and Turbo Histogram can cross this zero line without any corresponding change in the colour of the zero line on that immediate candle.
4) The +100 and -100 lines are used in two ways. First, they can be used by the CCI Histogram and CCI Turbo as a sort of minor price resistance and if the CCI values cannot get through these, it is considered weakness in that trade direction until they do so. You will notice that both of these lines are multi-coloured. They have been plotted with the ChopZone Indicator, another TradingView built-in indicator. The ChopZone is a trend identification tool that uses the slope and the direction of a 34-period EMA to identify when price is trending or range bound. While there are ~10 different colours, the main two a trader needs to pay attention to are the turquoise/cyan blue, which indicates price is in an uptrend, and dark red, which indicates price is in a downtrend based on the slope and direction of the 34 EMA. All other colours indicate "chop". These colours are used solely for the Zero-Line Reject and pattern trades discussed below. They are plotted both above and below so you can easily see the colouring no matter what side of the zero line the CCI is on.
5) The +200 and -200 lines are also used in two ways. First, they are considered overbought/oversold levels where if price exceeds these lines then it has moved an extreme amount away from the average and is likely to experience a pullback shortly. This is more useful for the CCI Histogram than the Turbo CCI, in all honesty. You will also notice that these are coloured either red, green, or yellow. This is the Sidewinder indicator portion. The documentation on this is extremely sparse, only pointing to a "relationship between the LSMA and the 34 EMA" (see here: tlc.thinkorswim.com). Since I am not a member of Woodie's CCI Club and never intend to be I took some liberty here and decided that the most likely relationship here was the slope of both moving averages. Therefore, the Sidewinder will be green when both the LSMA and the 34 EMA are rising, red when both are falling, and yellow when they are not in agreement with one another (i.e. one rising/flat while the other is flat/falling). I am a big fan of Dr. Alexander Elder as those who follow me know, so consider this like Woodie's version of the Elder Impulse System. I will fully admit that this version of the Sidewinder is a guess and may not represent the real Sidewinder indicator, but it is next to impossible to find any information on this, so I apologize, but my version does do something useful anyways. This is also to be used only with the Zero-Line Reject trades. They are plotted both above and below so you can easily see the colouring no matter what side of the zero line the CCI is on.
How to Trade It According to Woodie's CCI Club:
Now that I have all of my components and history out of the way, this is what you all care about. I will only provide a brief overview of the trades in this system, but there are quite a few more detailed descriptions listed in the Woodie's CCI Club pamphlet. I have had little success trading the "patterns" but they do exist and do work on occasion. I just prefer to trade with the flow of the markets rather than getting overly scalpy. If you are interested in these patterns, see the pamphlet here (www.trading-attitude.com), hop into the forums and see for yourself, or check out a couple of the YouTube videos.
1) Zero line cross. As simple as any other momentum oscillator out there. When the long period CCI crosses above or below the zero line open a trade in that direction. Extra confirmation can be had when the CCI Turbo has already broken the +100/-100 line "resistance or support". Trend traders may wish to wait until the yellow "trend confirmation bar" has been printed.
2) Zero Line Reject. This is when the CCI Turbo heads back down to the zero line and then bounces back in the same direction of the prevailing trend. These are fantastic continuation trades if you missed the initial entry either on the zero line cross or on the trend bar establishment. ZLR trades are only viable when you have the ChopZone indicator showing a trend (turquoise/cyan for uptrend, dark red for downtrend), the LSMA line is green for an uptrend or red for a downtrend, and the SideWinder is either green confirming the uptrend or red confirming the downtrend.
3) Hook From Extreme. This is the exact same as the Zero Line Reject trade, however, the CCI Turbo now goes to the +100/-100 line (whichever is opposite the currently established trend) and then hooks back into the established trend direction. Ideally the HFE trade needs to have the Long CCI Histogram above/below the corresponding 100 level and the CCI Turbo both breaks the 100 level on the trend side and when it does break it has increased ~20 points from the previous value (i.e. CCI Histogram = +150 with LSMA, CZ, and SW all matching up and trend bars printed on CCI Histogram, CCI Turbo went to -120 and bounced to +80 on last 2 bars, current bar closes with CCI Turbo closing at +110).
4) Trend Line Break. Either the CCI Turbo or CCI Histogram, whichever you prefer (I find the Turbo a bit more accurate since its a faster value) creates a series of higher highs/lows you can draw a trend line linking them. When the line breaks the trendline that is your signal to take a counter trade position. For example, if the CCI Turbo is making consistently higher lows and then breaks the trendline through the zero line, you can then go short. This is a good continuation trade.
5) The Tony Trade. Consider this like a combination zero line reject, trend line break, and weak zero line cross all in one. The idea is that the SW, CZ, and LSMA values are all established in one direction. The CCI Histogram should be in an established trend and then cross the zero line but never break the 100 level on the new side as long as it has not printed more than 9 bars on the new side. If the CCI Histogram prints 9 or less bars on the new side and then breaks the trendline and crosses back to the original trend side, that is your signal to take a reversal trade. This is best used in the Elder Triple Screen method (discussed in final section) as a failed dip or rip.
6) The GB100 Trade. This is a similar trade as the Tony Trade, however, the CCI Histogram can break the 100 level on the new side but has to have made less than 6 bars on the new side. A trendline break is not necessary here either, it is more of a "pop and drop" or "momentum failure" trade trying in the new direction.
7) The Famir Trade. This is a failed CCI Long Histogram ZLR trade and is quite complicated. I have never traded this but it is in the pamphlet. Essentially you have a typical ZLR reject (i.e. all components saying it is likely a long/short continuation trade), but the ZLR only stays around the 50 level, goes back to the trend side, fails there as well immediately after 1 bar and then rebreaks to the new side. This is important to be considered with the LSMA value matching the side of the trade, so if the Famir says to go long, you need the LSMA indicator to also say to go long.
8) The Vegas Trade. This is essentially a trend-reversal trade that takes into account the LSMA and a cup and handle formation on the CCI Long Histogram after it has reached an extreme value (+200/-200). You will see the CCI Histogram hit the extreme value, head towards the zero line, and then sort of round out back in the direction of the extreme price. The low point where it reversed back in the direction of the extreme can be considered support or resistance on the CCI and once the CCI Long Histogram breaks this level again, with LSMA confirmation, you can take a counter trend trade with a stop under/over the highest/lowest point of the last 2 bars as you want to be out quickly if you are wrong without much damage but can get a huge win if you are right and add later to the position once a new trade has formed.
9) The Ghost Trade. This is nothing more than a(n) (inverse) head and shoulders pattern created on the CCI. Draw a trend line connecting the head and shoulders and trade a reversal trade once the CCI Long Histogram breaks the trend line. Same deal as the Vegas Trade, stop over/under the most recent 2 bar high/low and add later if it is a winner but cut quickly if it is a loser.
Like I said, this is a complicated system and could quite literally take years to master if you wanted to go into the patterns and master them. I prefer to trade it in a much simpler format, using the Elder Triple Screen System. First, since I am a day trader, I look to use the 20 period Woodie's on the hourly and look at the CZ, SW, and LSMA values to make sure they all match the direction of the CCI Long Histogram (a trend establishment is not necessary here). It shows you the hourly trend as your "tide". I then drill down to the 15 minute time frame and use the Turbo CCI break in the opposite direction of the trend as my "wave" and to indicate when there is a dip or rip against the main trend. Lastly, I drill down to a 3 minute time frame and enter when the CCI Long Histogram turns back to match the main trend ("ripple") as long as the CCI Turbo has broken the 100 level in the matched direction.
Enjoy, and please read the pamphlet if you have any questions about the patterns as they are not how I use these and will not be able to answer those questions.
CheckmateTrades - Pivots End GameThis indicator is based on the Pivot study. Traders will be able to plot CPR, Standard floor pivots as well as Camarilla Pivots on multiple timeframes.
Why pivots from multiple timeframes are relevant and included in this one indicator?
We can analyse pivots on multiple timeframes for different trading setups. As in, Daily floor pivots are best suited for analysing the market trend for Day trading. Similarly, Weekly and Monthly floor pivots can be analysed for Swing and positional trading entries. Whereas yearly pivot is best suited for trend analysis for investment purpose.
What is the relevance of plotting tomorrow's pivot level in advance?
Pivot are calculated based on the price happened on a previous day. And hence trader can plot tomorrow pivots in advance to shortlist stocks for tomorrow's trading session.
TimeFrames Available to traders are –
1. Daily
2. Weekly
3. Monthly
A) Daily Pivots
Present Day –
1. Trader can plot Daily CPR
2. Trader can plot Daily R1, R2, R3 and R4 pivot resistance levels
3. Trader can plot Daily S1, S2, S3 and S4 pivot support levels
4. Trader can plot Daily Camarilla levels
Future Day –
1. Trader can plot Tomorrow CPR
2. Trader can plot Tomorrow R1, R2, R3 and R4 pivot resistance levels
3. Trader can plot Tomorrow S1, S2, S3 and S4 pivot support levels
4. Trader can plot Tomorrow Camarilla levels
5. Previous Day High and Low
B) Weekly Pivots
Present Week –
1. Trader can plot Present week CPR
2. Trader can plot Present week R1, R2, R3 and R4 pivot resistance levels
3. Trader can plot Present week S1, S2, S3 and S4 pivot support levels
4. Trader can plot Present week Camarilla levels
Next Week –
1. Trader can plot Next week CPR
2. Trader can plot Next week R1, R2, R3 and R4 pivot resistance levels
3. Trader can plot Next week S1, S2, S3 and S4 pivot support levels
4. Trader can plot Next week Camarilla levels
5. Previous Week High and Low
C) Monthly Pivots
Present Month –
1. Trader can plot Present Month CPR
2. Trader can plot Present Month R1, R2, R3 and R4 pivot resistance levels
3. Trader can plot Present Month S1, S2, S3 and S4 pivot support levels
4. Trader can plot Present Month Camarilla levels
Next Month –
1. Trader can plot Next Month CPR
2. Trader can plot Next Month R1, R2, R3 and R4 pivot resistance levels
3. Trader can plot Next Month S1, S2, S3 and S4 pivot support levels
4. Trader can plot Next Month Camarilla levels
5. Previous Month High and Low
Moreover, I have also included SMA (Simple moving averages) study in this indicator. Trader can add 20,50 & 200 SMA on there charts.
Why is it relevant? Trader can get a visual confirmation of an up-trending or an down-trending move by looking at rising or falling 20 & 50 SMA respectively
Usually in an uptrending stocks. 20 & 50 SMA will move in parallel to each other and will rise upwards. Price will tend to trade above the 20 SMA and 20 SMA will continue to act as a support.
Bollinger Bands - Custom moving averageFormula for bollinger bands is as below:
Mid = sma(20)
Top = sma(20) + 2*StdDev(20)
Bottom = sma(20) - 2*StdDev(20)
While standard bollinger bands allow changing standard deviation and length, there is no option to use different moving average.
This indicator allows you to define bollinger bands based on different moving average types which can be selected from input.
Bitcoin - MA Crossover StrategyBefore You Begin:
Please read these warnings carefully before using this script, you will bear all fiscal responsibility for your own trades.
Trading Strategy Warning - Past performance of this strategy may not equal future performance, due to macro-environment changes, etc.
Account Size Warning - Performance based upon default 10% risk per trade, of account size $100,000. Adjust BEFORE you trade to see your own drawdown.
Time Frame - D1 and H4. H4 has a lower profit factor (more fake-outs, and account drawdown), D1 recommended.
Trend Following System - Profitability of this system is dependent on STRONG future trends in Bitcoin (BTCUSD).
Default Settings:
This script was tested on Daily and 4 Hourly charts using the following default settings. Note that 4 Hourly exhibits higher drawdowns and lower profit factor, whilst Daily appears more stable.
Account Size ($): 100,000 (please adjust to simulate your own risk)
Equity Risk (%): 10 (please adjust to simulate your own risk)
Fast Moving Average (Period): 20
Slow Moving Average (Period): 40
Relative Strength Index (Period): 14
Trading Mechanism:
Trend following strategies work well for assets that display the tendency of long-trends. Please do not use this script on financial assets that have a historical tendency for mean reversion. Bitcoin has historically exhibited strong trends, and thus this script is designed to capitalise on that behaviour. It is hoped (but we cannot predict), that Bitcoin will strongly trend in the coming days.
LONG:
Enter Long - When fast moving average (20) crosses ABOVE slow moving average (40)
Exit Long - When fast moving average (20) crosses BELOW slow moving average (40)
SHORT:
Enter Short - When fast moving average (20) crosses BELOW slow moving average (40)
Exit Short - When fast moving average (20) crosses ABOVE slow moving average (40)
Risk Warnings:
Do note that "moving averages" are a lagging indicator, and as such heavy drawdowns could occur when a trade is open. If you are trading this system manually, it is best to avoid emotions and let the system tell you when to enter and exit. Do not panic and exit manually when under heavy drawdown, always follow the system. Do not be emotional. If possible, connect this to your broker for auto-trading. Ensure that your risk per trade (Equity Risk) is SMALL enough that it does not result in a margin-call on your trading account. Equity risk must always be considered relative to your total account size.
Remember: You bear all financial responsibility for your trades, best of luck.
Donchian Channel CloudsFor this indicator, I got inspired by this paragraph in an article on Investopedia:
"Donchian channels also make natural partners with another moving average indicator for a crossover strategy. The Donchian moving average middle line is likely to form the short-term average in these situations, although some have used a 20-day Donchian channel in conjunction with a five- or 10-day channel to exit a position before a consolidation eats into short-term profits."
The default is a 20-period Donchian channel with the middle line from a 10-period channel superimposed on it. Red for 20, green for 10. When 10 is over 20, the cloud between them is green; the cloud is red when 20 is over 10.
(JS)DMI BarsAlright - so this is my own version of John Carter's "10x Bars"... I have done multiple things that are different from his version so they are slightly different..
So first of all the main indicator is based off of the ADX and the DMI;
For those who aren't familiar with it, Directional Movement is what you'd pull up under "built-in's" from the indicators tab (if you want to check it out).
The standard interpretation of this however, is when the ADX is above 20 that suggests the trend is strong, whereas under 20 suggests it is weak.
Also, when the D+ is above the D- that suggests a bullish trend, and D- above D+ suggests a bearish trend.
These bars take away the need to have it at the bottom of your screen, and places the data on the bars on your chart instead.
=========================================================================================================================================
So here's what the colors stand for -
Yellow - The ADX is under 20, no strength in trend
Shades of green occur when the ADX is above 20 and there's a bullish trend (D+ higher than D-)
Bright Green (Lime) - Bullish trend, D+ above 30
Green - Bullish Trend
Yellow Green - Bullish trend, D+ below 15
Shades of red occur when the ADX is above 20 and there's a bearish trend (D- higher than D+)
Bright Red - Bearish trend, D- above 30
Red - Bearish Trend
Orange - Bearish trend, D- below 15
=========================================================================================================================================
I have also added multiple time frame labels (label script used is the one created by Ricardo Santos)
These labels are color coded the same as the bars/candles, and they appear off to the right of your screen using every built in time increment from TradingView.
The purpose is to show you in real time, and on any chart resolution, what the current trend is on every individual time frame.
So using just one single chart you'll see your current resolutions candles, but also on the labels you'll see:
1 Minute
3 Minute
5 Minute
15 Minute
30 Minute
45 Minute
1 Hour
2 Hour
3 Hour
4 Hour
Daily
Weekly
Monthly
There is an input I added that allows you to adjust where your labels appear on the side of your screen as well!
=========================================================================================================================================
Now onto the volume spike portion of the indicator. This will plot a blue dot under each bar that has a spike in volume which meets your specified criteria.
I have 500% as the default setting.
What that means is that this indicator looks back and gets the 50 bar volume average and then applies dots where volume is 500% above average.
=========================================================================================================================================
Now finally, the reversal arrows. This is another simple to understand concept that I first read in John Carter's book "Mastering the Trade" that he calls "HOLP/LOHP".
I have added the ability to change the look back period you'd like the indicator to watch for highs and lows on.
What that stands for is 'High of Low Period' and 'Low of High Period', and it is used like this-
Whenever a bar makes a new high the indicator watches the low on that highest bar. Then when a bar afterwards makes a lower low then the one on the high bar,
a reversal arrow is given. Apply this same concept in the other direction in for the highs on the lowest bars.
=========================================================================================================================================
Now, I didn't want to make a "set" or have a bunch of different indicators out there that are all intended for the same package, so I took the time to put them together,
and if there's a part of it you don't care for they can easily be turned off in the settings.
Enjoy!
MACD/EMA/SMA/Ichimoku Confluence StrategyThis strategy uses a number of chart indicators to provide a Bullish/Bearish signal. Using a combination of the 200 SMA, the 20 EMA, the MACD and the Ichimoku cloud, the strategy logic will adjust the amount of confluence required between the indicators depending on how bullish or bearish the chart is looking. The logic looks for the following:
- Are we above or below the 200 SMA?
- Are we above or below the 20 EMA?
- Have we had a bullish MACD cross?
- Where are we in relation to the Ichimoku cloud?
If the coin is below the 200 SMA, then the strategy will only give a buy signal if the coin closes a candle above the 20 EMA AND the MACD is bullish and either the Ichimoku cloud is green, or the coin is above the Ichimoku cloud (regardless of colour).
If the coin is above the 200 SMA, Then the strategy will give a buy signal if the coin closes a candle above the 20 EMA AND the MACD is bullish and the coin is either IN the cloud (not necessarily above it) or the cloud is green.
The reverse is true for a sell signal, i.e. when the coin is above the 200 SMA it must close a candle below the Ichimoku cloud and be bearish in relation to the 20 EMA and MACD. If it is below the 200 SMA, then the strategy will give a sell signal if the the EMA/MACD conditions are true and the coin enters the cloud.
This strategy gives a fairly conservative signal for entry and exit points, but is fairly successful across a number of time frames, both short term and long term. As with all my strategies, I only include LONG entries and closes, not SHORT entries (as I find they make for inaccurate backtesting).
Please feel free to like, share, critique and suggest any improvements to this strategy. All feedback, positive and negative, is appreciated.
Wyckoff Volume ColorThis volume indicator is intended to be used for the Wyckoff strategy.
Green volume bar indicates last price close above close 10 days ago together with volume larger than 2 * SMA(volume, 20)
Blue volume bar indicates last price close above close 10 days ago together with volume less than 2 * SMA(volume, 20)
Orange volume bar indicates last price close lower than close 10 days ago together with volume less than 2 * SMA(volume, 20)
Red volume bar indicates last price close lower than close 10 days ago together with volume larger than 2 * SMA(volume, 20)
The main purpose is to have green bars with a buying climax and red bars with a selling climax.
Three variables can be changed by simply pressing the settings button.
How many days back the closing price is compared to. Now 10 days.
How many times the SMA(volume) is multiplied by. Now times 2.
How many days the SMA(volume) consists by. Now 20 days.
3riple Moving AverageBITFINEX:ETHUSD
Description:
Mixing three Simple Moving Averages (7 - 20 - 65) to determine "uptrends" and "downtrends".
Uptrend: When the 7 Line is upper than 20, And 20 Line is upper than 65 that usually means the price is trending up.
Downtrend: When the 7 Line is lower than 20, And 20 Line is lower than 65 that usually means the price is trending down.
BTC Energy + HR + Longs + M2
BTC Energy Ratio + Hashrate + Longs + M2
The #1 Bitcoin Macro Weapon on TradingView 🚀🔥
If you’re tired of getting chopped by fakeouts, ETF noise, and Twitter hopium — this is the one chart that finally puts you on the right side of every major move.
What you’re looking at:
Orange line → Bitcoin priced in real-world mining energy (Oil × Gas + Uranium × Coal) × 1000
→ The true fundamental floor of BTC
Blue line → Scaled hashrate trend (miner strength & capex lag)
Green line → Bitfinex longs EMA (leveraged bull sentiment)
Purple line → Global M2 money supply (US+EU+CN+JP) with 10-week lead (the liquidity wave BTC rides)
Why this indicator prints money:
Most tools react to price.
This one predicts where price is going based on energy, miners, leverage, and liquidity — the only four things that actually drive Bitcoin long-term.
It has nailed:
2022 bottom at ~924 📉
2024 breakout above 12,336 🚀
2025 top at 17,280 🏔️
And right now it’s flashing generational accumulation at ~11,500 (Nov 2025)
13 permanent levels with right-side labels — no guessing what anything means:
20,000 → 2021 Bull ATH
17,280 → 2025 ATH
15,000 → 2024 High Resist
14,000 → Overvalued Zone
13,000 → 2024 Breakout
12,336 → Bull/Bear Line (the most important level)
12,000 → 2024 Volume POC
10,930 → Key Support 2024
9,800 → Strong Buy Fib
8,000 → Deep Support 2023
6,000 → 2021 Mid-Cycle
4,500 → 2023 Accum Low
924 → 2022 Bear Low
Live dashboard tells you exactly what to do — no thinking required:
Current ratio (updates live)
Hashrate + 24H %
Longs trend
Risk Mode → Orange vs Hashrate (RISK ON / RISK OFF)
180-day correlation
RSI
13-tier Zone + SIGNAL (STRONG BUY / ACCUMULATE / HOLD / DISTRIBUTE / EXTREME SELL)
Dead-simple rules that actually work:
Weekly timeframe = cleanest view
Blue peaking + orange holding support → miner pain = next leg up
Green spiking + orange failing → overcrowded longs = trim
Purple rising → liquidity coming in = ride the wave
Risk Mode = RISK OFF → price is cheap vs miners → buy
Set these 3 alerts and walk away:
Ratio > 12,336 → Bull confirmed → add
Ratio > 14,000 → Start scaling out
Ratio < 9,800 → Generational buy → back up the truck
No repainting • Fully open-source • Forced daily data • Works on any TF
Energy is the only real backing Bitcoin has.
Hashrate lag is the best leading indicator.
Longs show greed.
M2 is the tide.
This chart combines all four — and right now it’s screaming ACCUMULATE.
Load it. Trust it.
Stop trading hope. Start trading reality.
DYOR • NFA • For entertainment purposes only 😎
#bitcoin #macro #energy #hashrate #m2 #cycle #riskon #riskoff
TenUp Bots S R - Fixed (ta.highest)//@version=5
indicator("TenUp Bots S R - Fixed (ta.highest)", overlay = true)
// Inputs
a = input.int(10, "Sensitivity (bars)", minval = 1, maxval = 9999)
d_pct = input.int(85, "Transparency (%)", minval = 0, maxval = 100)
// Convert 0-100% to 0-255 transparency (color.new uses 0..255)
transp = math.round(d_pct * 255 / 100)
// Colors with transparency applied
resColor = color.new(color.red, transp)
supColor = color.new(color.blue, transp)
// Helper (calculations only)
getRes(len) => ta.highest(high, len)
getSup(len) => ta.lowest(low, len)
// === PLOTS (all in global scope) ===
plot(getRes(a*1), title="Resistance 1", color=resColor, linewidth=2)
plot(getSup(a*1), title="Support 1", color=supColor, linewidth=2)
plot(getRes(a*2), title="Resistance 2", color=resColor, linewidth=2)
plot(getSup(a*2), title="Support 2", color=supColor, linewidth=2)
plot(getRes(a*3), title="Resistance 3", color=resColor, linewidth=2)
plot(getSup(a*3), title="Support 3", color=supColor, linewidth=2)
plot(getRes(a*4), title="Resistance 4", color=resColor, linewidth=2)
plot(getSup(a*4), title="Support 4", color=supColor, linewidth=2)
plot(getRes(a*5), title="Resistance 5", color=resColor, linewidth=2)
plot(getSup(a*5), title="Support 5", color=supColor, linewidth=2)
plot(getRes(a*6), title="Resistance 6", color=resColor, linewidth=2)
plot(getSup(a*6), title="Support 6", color=supColor, linewidth=2)
plot(getRes(a*7), title="Resistance 7", color=resColor, linewidth=2)
plot(getSup(a*7), title="Support 7", color=supColor, linewidth=2)
plot(getRes(a*8), title="Resistance 8", color=resColor, linewidth=2)
plot(getSup(a*8), title="Support 8", color=supColor, linewidth=2)
plot(getRes(a*9), title="Resistance 9", color=resColor, linewidth=2)
plot(getSup(a*9), title="Support 9", color=supColor, linewidth=2)
plot(getRes(a*10), title="Resistance 10", color=resColor, linewidth=2)
plot(getSup(a*10), title="Support 10", color=supColor, linewidth=2)
plot(getRes(a*15), title="Resistance 15", color=resColor, linewidth=2)
plot(getSup(a*15), title="Support 15", color=supColor, linewidth=2)
plot(getRes(a*20), title="Resistance 20", color=resColor, linewidth=2)
plot(getSup(a*20), title="Support 20", color=supColor, linewidth=2)
plot(getRes(a*25), title="Resistance 25", color=resColor, linewidth=2)
plot(getSup(a*25), title="Support 25", color=supColor, linewidth=2)
plot(getRes(a*30), title="Resistance 30", color=resColor, linewidth=2)
plot(getSup(a*30), title="Support 30", color=supColor, linewidth=2)
plot(getRes(a*35), title="Resistance 35", color=resColor, linewidth=2)
plot(getSup(a*35), title="Support 35", color=supColor, linewidth=2)
plot(getRes(a*40), title="Resistance 40", color=resColor, linewidth=2)
plot(getSup(a*40), title="Support 40", color=supColor, linewidth=2)
plot(getRes(a*45), title="Resistance 45", color=resColor, linewidth=2)
plot(getSup(a*45), title="Support 45", color=supColor, linewidth=2)
plot(getRes(a*50), title="Resistance 50", color=resColor, linewidth=2)
plot(getSup(a*50), title="Support 50", color=supColor, linewidth=2)
plot(getRes(a*75), title="Resistance 75", color=resColor, linewidth=2)
plot(getSup(a*75), title="Support 75", color=supColor, linewidth=2)
plot(getRes(a*100), title="Resistance 100", color=resColor, linewidth=2)
plot(getSup(a*100), title="Support 100", color=supColor, linewidth=2)
plot(getRes(a*150), title="Resistance 150", color=resColor, linewidth=2)
plot(getSup(a*150), title="Support 150", color=supColor, linewidth=2)
plot(getRes(a*200), title="Resistance 200", color=resColor, linewidth=2)
plot(getSup(a*200), title="Support 200", color=supColor, linewidth=2)
plot(getRes(a*250), title="Resistance 250", color=resColor, linewidth=2)
plot(getSup(a*250), title="Support 250", color=supColor, linewidth=2)
plot(getRes(a*300), title="Resistance 300", color=resColor, linewidth=2)
plot(getSup(a*300), title="Support 300", color=supColor, linewidth=2)
plot(getRes(a*350), title="Resistance 350", color=resColor, linewidth=2)
plot(getSup(a*350), title="Support 350", color=supColor, linewidth=2)
plot(getRes(a*400), title="Resistance 400", color=resColor, linewidth=2)
plot(getSup(a*400), title="Support 400", color=supColor, linewidth=2)
plot(getRes(a*450), title="Resistance 450", color=resColor, linewidth=2)
plot(getSup(a*450), title="Support 450", color=supColor, linewidth=2)
plot(getRes(a*500), title="Resistance 500", color=resColor, linewidth=2)
plot(getSup(a*500), title="Support 500", color=supColor, linewidth=2)
plot(getRes(a*750), title="Resistance 750", color=resColor, linewidth=2)
plot(getSup(a*750), title="Support 750", color=supColor, linewidth=2)
plot(getRes(a*1000), title="Resistance 1000", color=resColor, linewidth=2)
plot(getSup(a*1000), title="Support 1000", color=supColor, linewidth=2)
plot(getRes(a*1250), title="Resistance 1250", color=resColor, linewidth=2)
plot(getSup(a*1250), title="Support 1250", color=supColor, linewidth=2)
plot(getRes(a*1500), title="Resistance 1500", color=resColor, linewidth=2)
plot(getSup(a*1500), title="Support 1500", color=supColor, linewidth=2)
TenUp Bots S R - Fixed (ta.highest)//@version=5
indicator("TenUp Bots S R - Fixed (ta.highest)", overlay = true)
// Inputs
a = input.int(10, "Sensitivity (bars)", minval = 1, maxval = 9999)
d_pct = input.int(85, "Transparency (%)", minval = 0, maxval = 100)
// Convert 0-100% to 0-255 transparency (color.new uses 0..255)
transp = math.round(d_pct * 255 / 100)
// Colors with transparency applied
resColor = color.new(color.red, transp)
supColor = color.new(color.blue, transp)
// Helper (calculations only)
getRes(len) => ta.highest(high, len)
getSup(len) => ta.lowest(low, len)
// === PLOTS (all in global scope) ===
plot(getRes(a*1), title="Resistance 1", color=resColor, linewidth=2)
plot(getSup(a*1), title="Support 1", color=supColor, linewidth=2)
plot(getRes(a*2), title="Resistance 2", color=resColor, linewidth=2)
plot(getSup(a*2), title="Support 2", color=supColor, linewidth=2)
plot(getRes(a*3), title="Resistance 3", color=resColor, linewidth=2)
plot(getSup(a*3), title="Support 3", color=supColor, linewidth=2)
plot(getRes(a*4), title="Resistance 4", color=resColor, linewidth=2)
plot(getSup(a*4), title="Support 4", color=supColor, linewidth=2)
plot(getRes(a*5), title="Resistance 5", color=resColor, linewidth=2)
plot(getSup(a*5), title="Support 5", color=supColor, linewidth=2)
plot(getRes(a*6), title="Resistance 6", color=resColor, linewidth=2)
plot(getSup(a*6), title="Support 6", color=supColor, linewidth=2)
plot(getRes(a*7), title="Resistance 7", color=resColor, linewidth=2)
plot(getSup(a*7), title="Support 7", color=supColor, linewidth=2)
plot(getRes(a*8), title="Resistance 8", color=resColor, linewidth=2)
plot(getSup(a*8), title="Support 8", color=supColor, linewidth=2)
plot(getRes(a*9), title="Resistance 9", color=resColor, linewidth=2)
plot(getSup(a*9), title="Support 9", color=supColor, linewidth=2)
plot(getRes(a*10), title="Resistance 10", color=resColor, linewidth=2)
plot(getSup(a*10), title="Support 10", color=supColor, linewidth=2)
plot(getRes(a*15), title="Resistance 15", color=resColor, linewidth=2)
plot(getSup(a*15), title="Support 15", color=supColor, linewidth=2)
plot(getRes(a*20), title="Resistance 20", color=resColor, linewidth=2)
plot(getSup(a*20), title="Support 20", color=supColor, linewidth=2)
plot(getRes(a*25), title="Resistance 25", color=resColor, linewidth=2)
plot(getSup(a*25), title="Support 25", color=supColor, linewidth=2)
plot(getRes(a*30), title="Resistance 30", color=resColor, linewidth=2)
plot(getSup(a*30), title="Support 30", color=supColor, linewidth=2)
plot(getRes(a*35), title="Resistance 35", color=resColor, linewidth=2)
plot(getSup(a*35), title="Support 35", color=supColor, linewidth=2)
plot(getRes(a*40), title="Resistance 40", color=resColor, linewidth=2)
plot(getSup(a*40), title="Support 40", color=supColor, linewidth=2)
plot(getRes(a*45), title="Resistance 45", color=resColor, linewidth=2)
plot(getSup(a*45), title="Support 45", color=supColor, linewidth=2)
plot(getRes(a*50), title="Resistance 50", color=resColor, linewidth=2)
plot(getSup(a*50), title="Support 50", color=supColor, linewidth=2)
plot(getRes(a*75), title="Resistance 75", color=resColor, linewidth=2)
plot(getSup(a*75), title="Support 75", color=supColor, linewidth=2)
plot(getRes(a*100), title="Resistance 100", color=resColor, linewidth=2)
plot(getSup(a*100), title="Support 100", color=supColor, linewidth=2)
plot(getRes(a*150), title="Resistance 150", color=resColor, linewidth=2)
plot(getSup(a*150), title="Support 150", color=supColor, linewidth=2)
plot(getRes(a*200), title="Resistance 200", color=resColor, linewidth=2)
plot(getSup(a*200), title="Support 200", color=supColor, linewidth=2)
plot(getRes(a*250), title="Resistance 250", color=resColor, linewidth=2)
plot(getSup(a*250), title="Support 250", color=supColor, linewidth=2)
plot(getRes(a*300), title="Resistance 300", color=resColor, linewidth=2)
plot(getSup(a*300), title="Support 300", color=supColor, linewidth=2)
plot(getRes(a*350), title="Resistance 350", color=resColor, linewidth=2)
plot(getSup(a*350), title="Support 350", color=supColor, linewidth=2)
plot(getRes(a*400), title="Resistance 400", color=resColor, linewidth=2)
plot(getSup(a*400), title="Support 400", color=supColor, linewidth=2)
plot(getRes(a*450), title="Resistance 450", color=resColor, linewidth=2)
plot(getSup(a*450), title="Support 450", color=supColor, linewidth=2)
plot(getRes(a*500), title="Resistance 500", color=resColor, linewidth=2)
plot(getSup(a*500), title="Support 500", color=supColor, linewidth=2)
plot(getRes(a*750), title="Resistance 750", color=resColor, linewidth=2)
plot(getSup(a*750), title="Support 750", color=supColor, linewidth=2)
plot(getRes(a*1000), title="Resistance 1000", color=resColor, linewidth=2)
plot(getSup(a*1000), title="Support 1000", color=supColor, linewidth=2)
plot(getRes(a*1250), title="Resistance 1250", color=resColor, linewidth=2)
plot(getSup(a*1250), title="Support 1250", color=supColor, linewidth=2)
plot(getRes(a*1500), title="Resistance 1500", color=resColor, linewidth=2)
plot(getSup(a*1500), title="Support 1500", color=supColor, linewidth=2)
Coin Jin Multi SMA+ BB+ SMA forecast Ver2.02This script provides a complete trend-analysis system based on the
5 / 20 / 60 / 112 / 224 / 448 / 896 SMAs.
It precisely detects bullish/bearish alignment and automatically identifies
12 advanced trend-shift signals (Start, End, and Reversal).
Key Features:
● 9 SMA lines (including custom X1 & X2)
Each SMA supports custom color, width, and style (Line/Step/Circles).
● Bollinger Bands with customizable options
Fully adjustable length, source, width, style, fill transparency, and more.
● SMA Forecast (curved projection)
– Slope computed via linear regression
– Predicts up to 30 future bars
– Forced dotted style ensures visibility at all zoom levels
● 12 Advanced Trend Signals (alertcondition)
Automatically detects:
Start of full alignment (with/without SMA 896)
End of alignment
Bull ↔ Bear transitions
Perfect for momentum trading, trend-following, reversal detection, or automated alert systems.
● Labeling last value of each SMA
Each SMA prints a label such as "5", “20”, “60”, “896”, or custom lengths at the latest bar.
이 스크립트는 5 / 20 / 60 / 112 / 224 / 448 / 896 이동평균선을 기반으로
정배열·역배열 상태를 정밀하게 분석하고,
총 12가지 고급 추세 신호(시작·종료·전환) 를 자동으로 감지하는 통합 추세 분석 도구입니다.
주요 기능:
● 9개의 SMA 표시 (커스텀 X1, X2 포함)
각 SMA는 색상·굵기·형태(Line/Step/Circle)를 개별 설정할 수 있습니다.
● 볼린저밴드 표시 및 채우기 옵션
BB 길이, 소스, 타입, 두께, 투명도 등을 자유롭게 조절 가능.
● SMA Forecast (미래 방향 곡선 예측)
– 기울기 기반 선형회귀 슬로프 계산
– 곡선 형태로 미래 30봉까지 예측
– 점선(Dotted) 강제 적용으로 어떤 배율에서도 선명하게 표시
● 12가지 고급 추세 신호(alertcondition)
정배열·역배열의
Start (처음 완성될 때)
End (깨질 때)
Switch (전환)
을 모두 자동 탐지하여 트레이딩뷰 알림으로 받을 수 있음.
● SMA 마지막 가격 라벨 표시
각 SMA 끝 지점에 “5 / 20 / 60 / ... / 896” 식으로 라벨 표시.
Turtle System 1 Long & Short (Donchian + N-Stop) + MTF Table V6 Turtle Trading Long & Short (System 1 – 20/10 Donchian + True 2N Trailing Stop) + Multi-Timeframe Dashboard – Pine Script v6This indicator is a 100 % faithful implementation of the famous original Turtle Trading System 1 (Richard Dennis & William Eckhardt) with the following genuine rules:Entry: 20-period Donchian Channel breakout (using the high/low of the previous completed bars only → )
Exit: Classic 10-period Donchian opposite breakout OR hit of the volatility-based stop
Risk Management: True 2N trailing stop (N = 20-period ATR). The stop is pulled tighter on every new favorable extreme (real Turtle trailing – not fixed!)
Fully dynamic position tracking (Long / Short / Flat) on the chart’s timeframe
Visual signals: green/red triangles for entries, diamonds for exits, trailing stop line, entry labels with current N and stop price
Unique Feature – Multi-Timeframe (MTF) Status Table
A clean table in the top-right corner instantly shows the current Turtle position status on five higher timeframes simultaneously:Turtle MTF
1H
4H
8H
1D
1W
Status
LONG / SHORT / FLAT (color-coded)
This allows you to see at a glance whether higher timeframes are already in a Turtle trend – perfect for trend confirmation, filtering, or multi-timeframe trading.Key Visual ElementsLime upper Donchian line (20-period high)
Red lower Donchian line (10-period low)
Gray channel fill
Fuchsia trailing 2N stop line (moves only in favorable direction)
Entry labels showing current N-value and exact stop price
Arrows and diamonds for entries/exits
Alerts
Two ready-to-use alert conditions:“Turtle Long Entry”
“Turtle Short Entry”
Works on any market and any chart timeframe (stocks, forex, futures, crypto).
Completely written and tested in Pine Script version 6.A true, clean, no-nonsense Turtle System 1 with real trailing volatility stops and a powerful higher-timeframe dashboard – exactly how the original Turtles traded (only better visualized)! Enjoy the trends!
Keltner Channels BandsKeltner Channels Bands - パブリッシュ用説明文
日本語版
タイトル
Keltner Channels Bands (Multi-Timeframe)
説明文
概要
シンプルで視認性の高いケルトナーチャネルインジケーターです。マルチタイムフレーム機能を搭載し、どの時間足でも上位足のケルトナーチャネルを表示できます。
特徴
グレーカラーでチャートを見やすく保持
マルチタイムフレーム対応（デフォルト: 1時間足）
4時間足以上で自動非表示機能（チャートの見やすさを維持）
EMAまたはSMAの選択が可能
ATR倍率とバンド幅を自由にカスタマイズ
トレードコンセプト
ケルトナーチャネルは、価格のボラティリティに基づいたトレンド追従型インジケーターです。
基本的な使い方:
トレンド判定: 価格がバンドの上部で推移している場合は上昇トレンド、下部で推移している場合は下降トレンド
エントリー: 価格がバンド外に出た後、バンド内に戻るタイミングでトレンド方向へエントリー
エグジット: 価格が中心線（MA）に到達、または反対側のバンドに接近した時
ブレイクアウト: バンドを勢いよく突破した場合、新たなトレンドの始まりを示唆
推奨設定:
スイングトレード: Length 20, Multiplier 2.2, 1時間足または4時間足
デイトレード: Length 20, Multiplier 2.0, 5分足または15分足で1時間足を表示
注意事項
このインジケーターは単独での使用ではなく、他のテクニカル指標やプライスアクションと組み合わせて使用することを推奨します。
English Version
Title
Keltner Channels Bands (Multi-Timeframe)
Description
Overview
A simple and visually clean Keltner Channels indicator with multi-timeframe capabilities. Display higher timeframe Keltner Channels on any chart timeframe.
Features
Clean gray color scheme for better chart visibility
Multi-timeframe support (Default: 1-hour)
Auto-hide on 4H+ timeframes to maintain chart clarity
Choice between EMA or SMA
Customizable ATR multiplier and band width
Trading Concept
Keltner Channels is a volatility-based trend-following indicator that helps traders identify trend direction and potential entry/exit points.
Basic Usage:
Trend Identification: Price staying near upper band indicates uptrend; near lower band indicates downtrend
Entry Signals: Enter in trend direction when price returns inside the bands after moving outside
Exit Signals: Consider exits when price reaches the center line (MA) or approaches the opposite band
Breakout Trading: Strong momentum breaks through the bands may signal the start of a new trend
Recommended Settings:
Swing Trading: Length 20, Multiplier 2.2, 1H or 4H timeframe
Day Trading: Length 20, Multiplier 2.0, Display 1H channels on 5M or 15M charts
Disclaimer
This indicator should not be used alone. Combine it with other technical indicators and price action analysis for better trading decisions.
NormalizedIndicatorsNormalizedIndicators Library - Comprehensive Trend Normalization & Pre-Calibrated Systems
Overview
The NormalizedIndicators Library is an advanced Pine Script™ collection that provides normalized trend-following indicators, calculation functions, and pre-calibrated consensus systems for technical analysis. This library extends beyond simple indicator normalization by offering battle-tested, optimized parameter sets for specific assets and timeframes.
The main advantage lies in its dual functionality:
Individual normalized indicators with standardized outputs (1 = bullish, -1 = bearish, 0 = neutral)
Pre-calibrated consensus functions that combine multiple indicators with asset-specific optimizations
This enables traders to either build custom strategies using individual indicators or leverage pre-optimized systems designed for specific markets.
📊 Library Structure
The library is organized into three main sections:
1. Trend-Following Indicators
Individual indicators normalized to standard output format
2. Calculation Indicators
Statistical and mathematical analysis functions
3. Pre-Calibrated Systems ⭐ NEW
Asset-specific consensus configurations with optimized parameters
🔄 Trend-Following Indicators
Stationary Indicators
These oscillate around a fixed value and are not bound to price.
TSI() - True Strength Index ⭐ NEW
Source: TradingView
Parameters:
price: Price source
long: Long smoothing period
short: Short smoothing period
signal: Signal line period
Logic: Double-smoothed momentum oscillator comparing TSI to its signal line
Signal:
1 (bullish): TSI ≥ TSI EMA
0 (bearish): TSI < TSI EMA
Use Case: Momentum confirmation with trend direction
SMI() - Stochastic Momentum Index ⭐ NEW
Source: TradingView
Parameters:
src: Price source
lengthK: Stochastic period
lengthD: Smoothing period
lengthEMA: Signal line period
Logic: Enhanced stochastic that measures price position relative to midpoint of high/low range
Signal:
1 (bullish): SMI ≥ SMI EMA
0 (bearish): SMI < SMI EMA
Use Case: Overbought/oversold with momentum direction
BBPct() - Bollinger Bands Percent
Source: Algoalpha X Sushiboi77
Parameters:
Length: Period for Bollinger Bands
Factor: Standard deviation multiplier
Source: Price source (typical: close)
Logic: Calculates the position of price within the Bollinger Bands as a percentage
Signal:
1 (bullish): when positionBetweenBands > 50
-1 (bearish): when positionBetweenBands ≤ 50
Special Feature: Uses an array to store historical standard deviations for additional analysis
RSI() - Relative Strength Index
Source: TradingView
Parameters:
len: RSI period
src: Price source
smaLen: Smoothing period for RSI
Logic: Classic RSI with additional SMA smoothing
Signal:
1 (bullish): RSI-SMA > 50
-1 (bearish): RSI-SMA < 50
0 (neutral): RSI-SMA = 50
Non-Stationary Indicators
These follow price movement and have no fixed boundaries.
NorosTrendRibbonSMA() & NorosTrendRibbonEMA()
Source: ROBO_Trading
Parameters:
Length: Moving average and channel period
Source: Price source
Logic: Creates a price channel based on the highest/lowest MA value over a specified period
Signal:
1 (bullish): Price breaks above upper band
-1 (bearish): Price breaks below lower band
0 (neutral): Price within channel (maintains last state)
Difference: SMA version uses simple moving averages, EMA version uses exponential
TrendBands()
Source: starlord_xrp
Parameters: src (price source)
Logic: Uses 12 EMAs (9-30 period) and checks if all are rising or falling simultaneously
Signal:
1 (bullish): All 12 EMAs are rising
-1 (bearish): All 12 EMAs are falling
0 (neutral): Mixed signals
Special Feature: Very strict conditions - extremely strong trend filter
Vidya() - Variable Index Dynamic Average
Source: loxx
Parameters:
source: Price source
length: Main period
histLength: Historical period for volatility calculation
Logic: Adaptive moving average that adjusts to volatility
Signal:
1 (bullish): VIDYA is rising
-1 (bearish): VIDYA is falling
VZO() - Volume Zone Oscillator
Parameters:
source: Price source
length: Smoothing period
volumesource: Volume data source
Logic: Combines price and volume direction, calculates the ratio of directional volume to total volume
Signal:
1 (bullish): VZO > 14.9
-1 (bearish): VZO < -14.9
0 (neutral): VZO between -14.9 and 14.9
TrendContinuation()
Source: AlgoAlpha
Parameters:
malen: First HMA period
malen1: Second HMA period
theclose: Price source
Logic: Uses two Hull Moving Averages for trend assessment with neutrality detection
Signal:
1 (bullish): Uptrend without divergence
-1 (bearish): Downtrend without divergence
0 (neutral): Trend and longer MA diverge
LeonidasTrendFollowingSystem()
Source: LeonidasCrypto
Parameters:
src: Price source
shortlen: Short EMA period
keylen: Long EMA period
Logic: Simple dual EMA crossover system
Signal:
1 (bullish): Short EMA < Key EMA
-1 (bearish): Short EMA ≥ Key EMA
ysanturtrendfollower()
Source: ysantur
Parameters:
src: Price source
depth: Depth of Fibonacci weighting
smooth: Smoothing period
bias: Percentage bias adjustment
Logic: Complex system with Fibonacci-weighted moving averages and bias bands
Signal:
1 (bullish): Weighted MA > smoothed MA (with upward bias)
-1 (bearish): Weighted MA < smoothed MA (with downward bias)
0 (neutral): Within bias zone
TRAMA() - Trend Regularity Adaptive Moving Average
Source: LuxAlgo
Parameters:
src: Price source
length: Adaptation period
Logic: Adapts to trend regularity - accelerates in stable trends, slows in consolidations
Signal:
1 (bullish): Price > TRAMA
-1 (bearish): Price < TRAMA
0 (neutral): Price = TRAMA
HullSuite()
Source: InSilico
Parameters:
_length: Base period
src: Price source
_lengthMult: Length multiplier
Logic: Uses Hull Moving Average with lagged comparisons for trend determination
Signal:
1 (bullish): Current Hull > Hull 2 bars ago
-1 (bearish): Current Hull < Hull 2 bars ago
0 (neutral): No change
STC() - Schaff Trend Cycle
Source: shayankm (described as "Better MACD")
Parameters:
length: Cycle period
fastLength: Fast MACD period
slowLength: Slow MACD period
src: Price source
Logic: Combines MACD concepts with stochastic normalization for early trend signals
Signal:
1 (bullish): STC is rising
-1 (bearish): STC is falling
🧮 Calculation Indicators
These functions provide specialized mathematical calculations for advanced analysis.
LCorrelation() - Long-term Correlation
Creator: unicorpusstocks
Parameters:
Input: First time series
Compare: Second time series
Logic: Calculates the average of correlations across 6 different periods (30, 60, 90, 120, 150, 180)
Returns: Correlation value between -1 and 1
Application: Long-term relationship analysis between assets, markets, or indicators
MCorrelation() - Medium-term Correlation
Creator: unicorpusstocks
Parameters:
Input: First time series
Compare: Second time series
Logic: Calculates the average of correlations across 6 different periods (15, 30, 45, 60, 75, 90)
Returns: Correlation value between -1 and 1
Application: Medium-term relationship analysis with higher sensitivity
assetBeta() - Beta Coefficient
Creator: unicorpusstocks
Parameters:
measuredSymbol: The asset to be measured
baseSymbol: The reference asset (e.g., market index)
Logic:
Calculates Beta across 4 different time horizons (50, 100, 150, 200 periods)
Beta = Correlation × (Asset Standard Deviation / Market Standard Deviation)
Returns the average of all 4 Beta values
Returns: Beta value (typically 0-2, can be higher/lower)
Interpretation:
Beta = 1: Asset moves in sync with the market
Beta > 1: Asset more volatile than market
Beta < 1: Asset less volatile than market
Beta < 0: Asset moves inversely to the market
🎯 Pre-Calibrated Systems ⭐ NEW FEATURE
These are ready-to-use consensus functions with optimized parameters for specific assets and timeframes. Each calibration has been fine-tuned through extensive backtesting to provide optimal performance for its target market.
Universal Calibrations
virtual_4d_cal(src) - Virtual/General 4-Day Timeframe
Use Case: General purpose 4-day chart analysis
Optimized For: Broad crypto market on 4D timeframe
Indicators Used: BBPct, Noro's, RSI, VIDYA, HullSuite, TrendContinuation, Leonidas, TRAMA
Characteristics: Balanced sensitivity for swing trading
virtual_1d_cal(src) - Virtual/General 1-Day Timeframe
Use Case: General purpose daily chart analysis
Optimized For: Broad crypto market on 1D timeframe
Indicators Used: BBPct, Noro's, RSI, VIDYA, HullSuite, TrendContinuation, Leonidas, TRAMA
Characteristics: Standard daily trading parameters
Cryptocurrency Specific
sui_cal(src) - SUI Ecosystem Tokens
Use Case: Tokens in the SUI blockchain ecosystem
Timeframe: 1D
Characteristics: Fast-response parameters for high volatility projects
deep_1d_cal(src) - DEEP Token Daily
Use Case: Deepbook (DEEP) token analysis
Timeframe: 1D
Characteristics: Tuned for liquidity protocol token behavior
wal_1d_cal(src) - WAL Token Daily
Use Case: Specific for WAL token
Timeframe: 1D
Characteristics: Mid-range sensitivity parameters
sns_1d_cal(src) - SNS Token Daily
Use Case: Specific for SNS token
Timeframe: 1D
Characteristics: Balanced parameters for DeFi tokens
meme_cal(src) - Meme Coin Calibration
Use Case: Highly volatile meme coins
Timeframe: Various
Characteristics: Wider parameters to handle extreme volatility
Warning: Meme coins carry extreme risk
base_cal(src) - BASE Ecosystem Tokens
Use Case: Tokens on the BASE blockchain
Timeframe: Various
Characteristics: Optimized for L2 ecosystem tokens
Solana Ecosystem
sol_4d_cal(src) - Solana 4-Day
Use Case: SOL token on 4-day charts
Characteristics: Responsive parameters for major L1 blockchain
sol_meme_4d_cal(src) - Solana Meme Coins 4-Day
Use Case: Meme coins on Solana blockchain
Timeframe: 4D
Characteristics: Handles high volatility of Solana meme sector
Ethereum Ecosystem
eth_4d_cal(src) - Ethereum 4-Day
Use Case: ETH and major ERC-20 tokens
Timeframe: 4D
Indicators Used: BBPct, Noro's, RSI, TSI, HullSuite, TrendContinuation, Leonidas, SMI
Special: Uses TSI and SMI instead of VIDYA and TRAMA
Characteristics: Tuned for Ethereum's market cycles
Bitcoin
btc_4d_cal(src) - Bitcoin 4-Day
Use Case: Bitcoin on 4-day charts
Timeframe: 4D
Characteristics: Slower, smoother parameters for the most established crypto asset
Notes: Conservative parameters suitable for position trading
Traditional Markets
qqq_4d_cal(src) - QQQ (Nasdaq-100 ETF) 4-Day
Use Case: QQQ ETF and tech-heavy indices
Timeframe: 4D
Characteristics: Largest parameter sets reflecting lower volatility of traditional markets
Notes: Can be adapted for similar large-cap tech indices
💡 Usage Examples
Example 1: Using Pre-Calibrated System
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Simple one-line implementation for Bitcoin
btcSignal = lib.btc_4d_cal(close)
// Trading logic
longCondition = btcSignal > 0.5
shortCondition = btcSignal < -0.5
// Plot
plot(btcSignal, "BTC 4D Consensus", color.orange)
Example 2: Custom Multi-Indicator Consensus
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Build your own combination
signal1 = lib.BBPct(20, 2.0, close)
signal2 = lib.RSI(14, close, 5)
signal3 = lib.TRAMA(close, 50)
signal4 = lib.TSI(close, 25, 13, 13)
// Custom consensus
customConsensus = math.avg(signal1, signal2, signal3, signal4)
plot(customConsensus, "Custom Consensus", color.blue)
Example 3: Asset-Specific Strategy Switching
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Automatically use the right calibration
signal = switch syminfo.ticker
"BTCUSD" => lib.btc_4d_cal(close)
"ETHUSD" => lib.eth_4d_cal(close)
"SOLUSD" => lib.sol_4d_cal(close)
"QQQ" => lib.qqq_4d_cal(close)
=> lib.virtual_4d_cal(close) // Default
plot(signal, "Auto-Calibrated Signal", color.orange)
Example 4: Correlation-Filtered Trading
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Only trade when strong correlation with market exists
spy = request.security("SPY", timeframe.period, close)
correlation = lib.MCorrelation(close, spy)
trendSignal = lib.virtual_1d_cal(close)
// Only signals with positive market correlation
tradeBuy = trendSignal > 0.5 and correlation > 0.5
tradeSell = trendSignal < -0.5 and correlation > 0.5
Example 5: Beta-Adjusted Position Sizing
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
spy = request.security("SPY", timeframe.period, close)
beta = lib.assetBeta(close, spy)
// Adjust position size based on Beta
basePositionSize = 100
adjustedSize = basePositionSize / beta // Less size with high Beta
// Use with calibrated signal
signal = lib.qqq_4d_cal(close)
🎯 Choosing the Right Calibration
Decision Tree
1. What asset are you trading?
Bitcoin → btc_4d_cal()
Ethereum/ERC-20 → eth_4d_cal()
Solana → sol_4d_cal()
Solana memes → sol_meme_4d_cal()
SUI ecosystem → sui_cal()
BASE ecosystem → base_cal()
Meme coins (any chain) → meme_cal()
QQQ/Tech indices → qqq_4d_cal()
Other/General → virtual_4d_cal() or virtual_1d_cal()
2. What timeframe?
Most calibrations are optimized for 4D (4-day) or 1D (daily)
For other timeframes, start with virtual calibrations and adjust
3. What's the asset's volatility?
High volatility (memes, new tokens) → Use meme_cal() or similar
Medium volatility (established alts) → Use specific calibrations
Low volatility (BTC, major indices) → Use btc_4d_cal() or qqq_4d_cal()
⚙️ Technical Details
Normalization Standard
Bullish: 1
Bearish: -1
Neutral: 0 (only for selected indicators)
Calibration Methodology
Pre-calibrated functions were optimized using:
Historical backtesting on target assets
Parameter optimization for maximum Sharpe ratio
Validation on out-of-sample data
Real-time forward testing
Iterative refinement based on market conditions
Advantages of Pre-Calibrations
Instant Deployment: No parameter tuning needed
Asset-Optimized: Tailored to specific market characteristics
Tested Performance: Validated through extensive backtesting
Consistent Framework: All use the same 8-indicator structure
Easy Comparison: Compare different assets using same methodology
Performance Considerations
All functions are optimized for Pine Script v5
Proper use of var for state management
Efficient array operations where needed
Minimal recursive calls
Pre-calibrations add negligible computational overhead
📋 License
This code is subject to the Mozilla Public License 2.0 at mozilla.org
🔧 Installation
pinescriptimport unicorpusstocks/NormalizedIndicators/1
Then use functions with your chosen alias:
pinescript// Individual indicators
lib.BBPct(20, 2.0, close)
lib.RSI(14, close, 5)
lib.TSI(close, 25, 13, 13)
// Pre-calibrated systems
lib.btc_4d_cal(close)
lib.eth_4d_cal(close)
lib.meme_cal(close)
⚠️ Important Notes
General Usage
All indicators are lagging, as is typical for trend-following indicators
Signals should be combined with additional analysis (volume, support/resistance, etc.)
Backtesting is recommended before starting live trading with these signals
Different assets and timeframes may require different parameter optimizations
Pre-Calibrated Systems
Calibrations are optimized for specific timeframes - using them on different timeframes may reduce effectiveness
Market conditions change - what worked historically may need adjustment
Pre-calibrations are starting points, not guaranteed solutions
Always validate performance on your specific use case
Consider current market regime (trending vs. ranging)
Risk Management
Meme coin calibrations are designed for extremely volatile assets - use appropriate position sizing
Pre-calibrated systems do not eliminate risk
Always use stop losses and proper risk management
Past performance does not guarantee future results
Customization
Pre-calibrations can serve as templates for your own optimizations
Feel free to adjust individual parameters within calibration functions
Test modifications thoroughly before live deployment
🎓 Advanced Use Cases
Multi-Asset Portfolio Dashboard
Create a dashboard showing consensus across different assets:
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
btc = request.security("BTCUSD", "4D", close)
eth = request.security("ETHUSD", "4D", close)
sol = request.security("SOLUSD", "4D", close)
btcSignal = lib.btc_4d_cal(btc)
ethSignal = lib.eth_4d_cal(eth)
solSignal = lib.sol_4d_cal(sol)
// Plot all three for comparison
plot(btcSignal, "BTC", color.orange)
plot(ethSignal, "ETH", color.blue)
plot(solSignal, "SOL", color.purple)
Regime Detection
Use correlation and calibrations together:
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Detect market regime
btc = request.security("BTCUSD", timeframe.period, close)
correlation = lib.MCorrelation(close, btc)
// Choose strategy based on correlation
signal = correlation > 0.7 ? lib.btc_4d_cal(close) : lib.virtual_4d_cal(close)
Comparative Analysis
Compare asset-specific vs. general calibrations:
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
specificSignal = lib.btc_4d_cal(close) // BTC-specific
generalSignal = lib.virtual_4d_cal(close) // General
divergence = specificSignal - generalSignal
plot(divergence, "Calibration Divergence", color.yellow)
🚀 Quick Start Guide
For Beginners
Identify Your Asset: What are you trading?
Find the Calibration: Use the decision tree above
One-Line Implementation: signal = lib.btc_4d_cal(close)
Set Thresholds: Buy when > 0.5, sell when < -0.5
Add Risk Management: Always use stops
For Advanced Users
Start with Pre-Calibration: Use as baseline
Analyze Performance: Backtest on your specific market
Fine-Tune Parameters: Adjust individual indicators if needed
Combine with Other Signals: Volume, market structure, etc.
Create Custom Calibrations: Build your own based on library structure
For Developers
Import Library: Access all functions
Mix and Match: Combine indicators creatively
Build Custom Logic: Use indicators as building blocks
Create New Calibrations: Follow the established pattern
Share and Iterate: Contribute to the trading community
🎯 Key Takeaways
✅ 10 normalized indicators - Consistent interpretation across all
✅ 16+ pre-calibrated systems - Ready-to-use for specific assets
✅ Asset-optimized parameters - No guesswork required
✅ Calculation functions - Advanced correlation and beta analysis
✅ Universal framework - Works across crypto, stocks, forex
✅ Professional-grade - Built on proven technical analysis principles
✅ Flexible architecture - Use pre-calibrations or build your own
✅ Battle-tested - Validated through extensive backtesting
NormalizedIndicators Library transforms complex multi-indicator analysis into actionable signals through both customizable individual indicators and pre-optimized consensus systems. Whether you're a beginner looking for plug-and-play solutions or an advanced trader building sophisticated strategies, this library provides the foundation for data-driven trading decisions.WiederholenClaude kann Fehler machen. Bitte überprüfen Sie die Antworten. Sonnet 4.5
Sentiment Heatmap with EMA Sentiment Heatmap with EMA Let’s build a script mini-LuxAlgo-style sentiment heatmap Enhanced Simple Sentiment Heatmap + Right-Side Legend Automatic legend on the right side
Just like professional indicators:
MAX GREED
GREED
NEUTRAL
FEAR
MAX FEAR
✔ Legend stays updated on the last bar
It moves automatically as price moves.
✔ Trend EMA included (optional) 9 EMA → White
20 EMA → Red
50 EMA → Yellow
100 EMA → Blue
200 EMA → Purple Alerts (e.g., “Max Fear – Buy Zone”)
✔ Liquidity line / support-resistance auto zones Full sentiment heatmap (Greed → Fear)
✔ Right-side legend like LuxAlgo
✔ All 5 EMAs added (my colors): EMA trend cloud (9/20, 20/50, 50/200)
Buy/Sell circles based on sentiment reversals Right-side legend: MAX GREED / GREED / NEUTRAL / FEAR / MAX FEAR
5 EMAs:
9 → White
20 → Red
50 → Yellow
100 → Blue
200 → Purple
