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 :)
Komut dosyalarını "摩根纳斯达克100基金风险大吗" için ara
MACDVMACDV = Moving Average Convergence Divergence Volume
The MACDV indicator uses stochastic accumulation / distribution volume inflow and outflow formulas to visualize it in a standard MACD type of appearance.
To be able to merge these formulas I had to normalize the math.
Accumulation / distribution volume is a unique scale.
Stochastic is a 0-100 scale.
MACD is a unique scale.
The normalized output scale range for MACDV is -100 to 100.
100 = overbought
-100 = oversold
Everything in between is either bullish or bearish.
Rising = bullish
Falling = bearish
crossover = bullish
crossunder = bearish
convergence = direction change
divergence = momentum
The default input settings are:
7 = K length, Stochastic accumulation / distribution length
3 = D smoothing, smoothing stochastic accumulation / distribution volume weighted moving average
6 = MACDV fast, MACDV fast length line
color = blue
13 = MACDV slow, MACDV slow length line
color = white
4 = MACDV signal, MACDV histogram length
color rising above 0 = bright green
color falling above 0 = dark green
color falling below 0 = bright red
color rising below 0 = dark red
2 = Stretch, Output multiplier for MACDV visual expansion
Horizontal lines:
100
75
50
25
0
-25
-50
-75
-100
Anchored VWAP+This indicator is an enhanced version of the Anchored VWAP indicator with additional functions:
1. Anchored AP (average price). It removes the volume weighting step in Anchored VWAP, and can display the average price over a period of time. For example, if the price of the stock in the last 3 days is 100, 200, 300, then AP is their average value of 200
2. Anchored AC (average cost). The average cost over time can be displayed. For example, if the price of the stock in the last 2 days is 100,300, then AC is (1+1)/(1/100+1/300)=150
When using the indicator, you need to choose a starting point, then the indicator will start to calculate the subsequent VWAP, AP and AC from this starting point, and draw 3 lines in the graph
These three lines can be regarded as the average cost line of the market, with potential support and resistance effects
We have filled the shadow between VWAP and AP, which can be regarded as a potential support resistance band
===========================中文版本===========================
该指标为增强版本的Anchored VWAP指标。在Anchored VWAP基础上增加了额外功能：
1. Anchored AP。其去掉了Anchored VWAP中成交量加权的步骤，可以显示一段时间的平均价格。举个例子，假如股票最近3天的价格为100，200，300，那么AP为他们的平均值200
2. Anchored AC。可以显示一段时间的平均成本。举个例子，假如股票最近2天的价格为100，300，那么AC为(1+1)/(1/100+1/300)=150
使用指标时你需要先选择一个起点，随后指标将会以该起点开始计算后续的VWAP、AP和AC，并且在图中绘制3根线
这3根线均可以视作是市场的平均成本线，具有潜在的支撑和阻力效果
我们让VWAP和AP之间填充了阴影，该阴影可以视作潜在的支撑阻力带
Moving Average Resting Point [theEccentricTrader]█ OVERVIEW
This indicator uses peak and trough prices to calculate the moving average resting point and plots it as a line on the chart. The lookback length is variable and the indicator can plot up to three lines with different lookback lengths and colors.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Wave Length
Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars.
Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles.
Wave Height
Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20.
Amplitude
Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10.
Resting Point
The resting point is here calculated by subtracting the current trough price from the current peak price and adding the difference to the current trough price to output the price in the middle of the two prices. Essentially it is the current trough price plus the amplitude. For example, if the current peak price is 100 and the current trough price is 80, the resting point 90.
The moving average resting point is here calculated by subtracting the moving average trough price from the moving average peak price, dividing the answer by two and adding the difference to the moving average trough price.
Frequency
Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
█ FEATURES
Inputs
Show MARP 1
Show MARP 2
Show MARP 3
MARP 1 Length
MARP 2 Length
MARP 3 Length
MARP 1 Color
MARP 2 Color
MARP 3 Color
█ HOW TO USE
This indicator can be used like any other moving average indicator to analyse trend direction and momentum, identify potential support and resistance levels, or for filtering trading strategies and developing new ones.
Free Volume RSIdear fellows,
this indicator is a mod or tweak on the standard RSI here available.
the original RSI formula is, as you know,
100 - 100/(1+RS)
which equals to
100 * RS/(1+RS)
where
the 100 factor is merely a scale adjustment to 100's percent basis
the RS is the ratio between average gain and average loss within the last N candles.
thus, the absolute gain of the up candles within the last N candles window is averaged; same for absolute loss.
this averaging uses EMA.
the ratio between this averages is RS.
the RS ranges from 0 to infinity, thus the ratio RS/(1+RS) locks it between 0 and 1.
in regard of our changes
we use VWMA instead of EMA
we plot the resulting RS directly, instead of its smooth version RS/(1+RS)
we dismiss the 100 factor.
we specify logarithmic scale for the resulting plot
on the justifications of our changes
by using VWMA instead of EMA we get both a more dynamic averaging (WMA is faster) as well as a de facto strength of the price action, since now volume is considered alongside the price change. this way one can quantify accumulation and distribution intensities.
to anyone who ever was restricted against his will over a sufficiently large period of time on his freedom to move, would understand that an unrestricted indicator conveys better its info.
as we're dealing with ratios, the distance between 1 and 2 is the same between 1 and 0.5; thus, a log scale is specified for reading this indicator without distortions.
on how to use this indicators
this is still an early result, hence it lacks more testing.
so far, when it's oversold, buy; and vice versa.
best regards.
Average Down [Zeiierman]AVERAGING DOWN
Averaging down is an investment strategy that involves buying additional contracts of an asset when the price drops. This way, the investor increases the size of their position at discounted prices. The averaging down strategy is highly debated among traders and investors because it can either lead to huge losses or great returns. Nevertheless, averaging down is often used and favored by long-term investors and contrarian traders. With careful/proper risk management, averaging down can cover losses and magnify the returns when the asset rebounds. However, the main concern for a trader is that it can be hard to identify the difference between a pullback or the start of a new trend.
HOW DOES IT WORK
Averaging down is a method to lower the average price at which the investor buys an asset. A lower average price can help investors come back to break even quicker and, if the price continues to rise, get an even bigger upside and thus increase the total profit from the trade. For example, We buy 100 shares at $60 per share, a total investment of $6000, and then the asset drops to $40 per share; in order to come back to break even, the price has to go up 50%. (($60/$40) - 1)*100 = 50%.
The power of Averaging down comes into play if the investor buys additional shares at a lower price, like another 100 shares at $40 per share; the total investment is ($6000+$4000 = $10000). The average price for the investment is now $50. (($60 x 100) + ($40 x 100))/200; in order to get back to break even, the price has to rise 25% ($50/$40)-1)*100 = 25%, and if the price continues up to $60 per share, the investor can secure a profit at 16%. So by averaging down, investors and traders can cover the losses easier and potentially have more profit to secure at the end.
THE AVERAGE DOWN TRADINGVIEW TOOL
This script/indicator/trading tool helps traders and investors to get the average price of their position. The tool works for Long and Short and displays the entry price, average price, and the PnL in points.
HOW TO USE
Use the tool to calculate the average price of your long or short position in any market and timeframe.
Get the current PnL for the investment and keep track of your entry prices.
APPLY TO CHART
When you apply the tool on the chart, you have to select five entry points, and within the setting panel, you can choose how many of these five entry points are active and how many contracts each entry has. Then, the tool will display your average price based on the entries and the number of contracts used at each price level.
LONG
Set your entries and the number of contracts at each price level. The indicator will then display all your long entries and at what price you will break even. The entry line changes color based on if the entry is in profit or loss.
SHORT
Set your entries and the number of contracts at each price level. The indicator will then display all your short entries and at what price you will break even. The entry line changes color based on if the entry is in profit or loss.
-----------------
Disclaimer
Copyright by Zeiierman.
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
EMA_cumulativeVolume_crossover [indicator]while I was doing some research with exp MA crossovers and volume indicator , I have noticed that when ema 50 is above cumulative volume of 100 period , shows to capture nice profits in that trend. Shorting also (ema50 cross down volume of 100 period) also shows nice results.
BUY
When ema50 crossover cumulative volume of 100 period
Exit
When ema50 cross down cumulative volume of 100 period
Short Selling
Reverse above BUY conditions
Back ground color shows blue when ema50 is above cumulative volume of 100 period, shows purple when ema50 is below cumulative volume of 100 period
I will publish the strategy for back testing later today
Warning
For the use of educational purpose only
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
Complex Oscillator [-W-]Eng.
Tradingview in the free version has a limitation - you can only use three indicators on the chart.
Complex Oscillator indicator combines several indicators in one, it is:
- RSI
- Stochastic
- WPR (%R)
- Volumes
The first three are chosen because their values are in the range |0-100| and one scale can be used for them.
The volumes are added because I personally feel sorry to allocate one of the three available places for them. =)
It is much more convenient to use them together with some other indicator.
Volumes also in the range 0-100, that is, they will not show the real numerical value, but only the value relative to the previous volumes.
You can display all the indicators at once or only a few of them.
The chart above shows the same indicator in three different variations.
If you know any other standard indicators with values in the range |0-100|, write in the comments, I will add to this indicator.
Rus.
Tradingview в бесплатной версии имеет ограничение - вы можете использовать только три индикатора на графике.
Индикатор Complex Oscillator объединяет несколько индикаторов в одном, это:
- RSI
- Stochastic
- WPR (%R)
- Volumes
Первые три выбраны из-за того, что их значения лежат в диапазоне |0-100| и для них можно использовать одну шкалу.
Объёмы добавлены, потому что лично мне жалко выделять для них одно из трёх доступных мест. =)
Намного удобнее использовать их вместе с каким-нибудь другим индикатором.
Объёмы относительные, тоже лежат в диапазоне 0-100, то есть реальное численное значение они не покажут, а только величину относительно предыдущих объёмов.
Вы можете вывести показания сразу всех индикаторов или только нескольких из них.
На графике выше представлен один и тот же индикатор в трёх разных вариациях.
Если вы знаете ещё какие-нибудь стандартные индикаторы со значениями в интервале |0-100|, напишите в комментариях, я добавлю в этот индикатор.
Commercial Movement Index-BuschiEnglish
Inspired by the book "The Commitments of Traders Bible" by Stephen Briese, this indicator is a follow-up of my already published "Commercial Index-Buschi".
Here, the Commercial Index isn't shown in values from 0 to 100, but in how far the value changed from a given timeframe (default Movement Reference: 6 weeks). Therefore it ranges from 100 (bullish move from the Commercials during the last weeks) to -100 (bearish move).
Deutsch
Inspiriert durch das Buch "The Commitments of Traders Bible" by Stephen Briese, ist dieser Indikator eine Weiterentwicklung meines bereits veröffentlichten Skriptes "Commercial Index-Buschi".
Hier wird der Commercial Index nicht in Werten von 0 bis 100 angezeigt, sondern in wieweit er sich innerhalb eines vorgegebenen Zeitfensters (Standard: Movement Reference: 6 Wochen) verändert hat. Daher schwankt er zwischen 100 (bullishe Bewegung der Commercials innerhalb der letzten Wochen) und -100 (bearishe Bewegung).
ADL-NDX Rank Difference-Buschi
English:
An expansion of the Advance Decline Line of the NASDAQ. It can be interesting to compare the Advance Decline Line with the corresponding benchmark index. I therefore made a ranking (0 to 100) based on the performance over the last days (default: 21 days). The difference is the target figure and ranges between -100 (bearish divergence) to +100 (bullish divergence).
Deutsch:
Eine Erweiterung der Advance Decline Line der NASDAQ. Oft möchte man den Verlauf der Advance Decline Line mit dem zugehörigen Leitindex vergleichen. Daher habe ich für beide ein Ranking (0 bis 100) erstellt auf Basis des Verlaufs über die letzten Tage (Standardwert: 21 Tage). Die Differenz stellt dabei die Zielgröße dar und schwankt zwischen -100 (bärische Divergenz) und +100 (bullische Divergenz).
ADL-SPX Rank Difference-Buschi
English:
An expansion of the Advance Decline Line of the NYSE. It can be interesting to compare the Advance Decline Line with the corresponding benchmark index. I therefore made a ranking (0 to 100) based on the performance over the last days (default: 21 days). The difference is the target figure and ranges between -100 (bearish divergence) to +100 (bullish divergence).
Deutsch:
Eine Erweiterung der Advance Decline Line der NYSE. Oft möchte man den Verlauf der Advance Decline Line mit dem zugehörigen Leitindex vergleichen. Daher habe ich für beide ein Ranking (0 bis 100) erstellt auf Basis des Verlaufs über die letzten Tage (Standardwert: 21 Tage). Die Differenz stellt dabei die Zielgröße dar und schwankt zwischen -100 (bärische Divergenz) und +100 (bullische Divergenz).
APEX - Aroon / Aroon Oscillator [v1]Simple Script that combines Aroon and Aroon Oscillator with MTF functionality for APEX.
Aroon
The Aroon also know as Aroon Up/Down will help you determine the trend of the asset of if the asset is ranging. The indicator consists of two lines the AroonDown and the Aroon Up.When Aroon Up reaches 100, a new uptrend may have begun. If it remains persistently between 70 and 100, and the Aroon-Down remains between 0 and 30, then a new uptrend is underway.If the Aroon-Up crosses above the Aroon-Down, then a new uptrend may start soon. Conversely, if Aroon-Down crosses above the Aroon-Up, then a new downtrend may start soon. When Aroon-Up reaches 100, a new uptrend may have begun. If it remains persistently between 70 and 100, and the Aroon-Down remains between 0 and 30, then a new uptrend is underway.
Aroon Oscillator
The Aroon Oscillator is the difference between Aroon-Up and Aroon-Down. These two indicators are usually plotted together for easy comparison, but chartists can also view the difference between these two indicators with the Aroon Oscillator. This indicator fluctuates between -100 and +100 with zero as the middle line. An upward trend bias is present when the oscillator is positive, while a downward trend bias exists when the oscillator is negative.
Triple Standard Deviation＝＝日本語説明も併記 // Japanese discription is following ＝＝
■ Momentum Indicator (Triple Indication of Standard Deviation Volatilities)
■ Effective assets: All
■Example of utilization
1) Assume that a trend is generated at the timing when the yellow area chart (26) rises
2) Confirm the candlestick and if the price jumps out of the Bollinger band ± 1 σ, the trend toward that direction
3) If the closing price is confirmed within ± 1σ of the Bollinger band, close the position
■ Detailed explanation
Three standard deviation volatilities with different parameters are displayed at the same time. As represented by convergence divergence of Bollinger, it has a characteristic that it rises in the trend generation period and falls during the trend convergence period.
It develops color in a rising phase so that trend generation is easy to recognize, and fades in a falling phase.
Daily use is basic, but you can use it with the same parameters for other time feet.
The basic parameter (26) is displayed in yellow area for the most visibility.
The long-term parameter (52) is indicated by a yellow dot as an auxiliary element for judging the rising margin of the basic line.
The short-term parameter (13) is displayed as a line as an auxiliary element for recognizing the peak out of the basic line in advance.
In some cases, by changing short term (13) to super long term (100) you can recognize the major market price level once in several years.
Three periods The phrase "all lines" goes from "low position" to "rising together" is considered the strongest trend.
On the other hand, in the case where the short-term line rises backwards as the longer-term line goes down, it tends to end up with short-lived trends and failure to form trends.
If the trend speed is constant as a standard feature of calculating the standard deviation, the standard deviation may decrease even during trend continuation. Therefore, it is desirable to make a comprehensive judgment by comparing the shape of candlestick with the longer-term line.
Please note that there is no way to judge whether the trend suggested by this index rises or falls from this index, so it is necessary to confirm the main chart. (It is preferable to display parabolic or Bollinger band)
■ Remarks
It is an index created assuming that it is used as Triple STD-ADX in combination with Triple Smoothed ADX（to be posted later）.
■ About Triple STD-ADX
Triple Standard Deviation "and" Triple Smoothed ADX "are superimposed and displayed as" Screen (without scale) "to function as" Triple STD - ADX ".
The method of utilization is the same as Triple Standard Deviation and Triple Smoothed ADX, but by simultaneously displaying two momentum indicators with different calculation approaches with multiple parameters, we aim to mutually complement the cognitive power of trends.
STD (13, 26, 52, 100, 200) and ADX (7, 14, 26, 52, 100) correspond to reaction rates respectively.
By choosing different reaction rates you can expect to further increase reliability.
You can estimate the reliability of the trend most reliably in a situation where all six signals in total rise from low to high.
■Sample: STD-ADX Trade Signal
========================================================
■ モメンタム指標（標準偏差ボラティリティの3連表示）
■ 有効アセット：すべて
■ 活用の一例
１）黄色のエリアチャート（26）が上昇したタイミングでトレンド発生を想定
２）ローソク足を確認し、ボリンジャーバンド±1σの外に価格が飛び出している場合はその方向へのトレンドと認識
３）ボリンジャーバンド±1σ以内で終値が確定した場合にはポジションクローズ
■ 詳細説明
パラメーターの異なる３つの標準偏差ボラティリティを同時に表示します。ボリンジャーの収束発散に代表されるように、トレンド発生期に上昇しトレンド収束期に低下する特性を持ちます。
トレンド発生を認識しやすいように上昇局面で発色し、下降局面で退色します。
活用は日足が基本ですが、他の時間足に対しても同一パラメーターで使用することができます。
基本パラメーター（26）は最も視認しやすいように黄色のエリア表示にしています。
長期パラメーター（52）は基本線の上昇余力を判断するための補助要素として黄色の丸点で表示しています。
短期パラメーター（13）は基本線のピークアウトを先行して認識するための補助要素としてラインで表示にしています。
場合によって、短期(13)を超長期（100）に変更することで数年に一度のレベルの大相場が認識できます。
3期間「全てのライン」が「低い位置」から「揃って上昇」する局面を最も強いトレンドと考えます。
一方、より長期のラインが低下する中、より短期のラインが逆行して上昇するケースでは、短命のトレンドやトレンド形成失敗に終わることが多くなります。
標準偏差の計算上の特徴としてトレンドの速度が一定の場合にトレンド継続中も標準偏差が低下することがあります。そのため、ローソク足の形状とより長期のラインを見比べて総合的に判断することが望ましいです。
なお、本指標が示唆するトレンドが上昇か下降かは本指標からは判断する術はないため、必ずメインチャートを確認する必要があります。（パラボリックやボリンジャーバンドを表示すると好適）
■備考
追って掲載するTriple Smoothed ADXと併用して、Triple STD-ADXとして使用することを想定して作成した指標です。
■Triple STD-ADXについて
「Triple Standard Deviation」と「Triple Smoothed ADX」を一方を「スクリーン（スケールなし）」として重ねて表示させることで「Triple STD-ADX」として機能します。
活用方法はTriple Standard DeviationやTriple Smoothed ADXと同じですが、算出アプローチの異なる２つのモメンタム指標を複数パラメーターで同時に表示させることで、トレンドの認識力を相互に補完する狙いがあります。
反応速度はそれぞれSTD（13,26,52,100,200)とADX（7,14,26,52,100)がほぼ対応します。
異なる反応速度を選択することで信頼度をさらに高めることを期待できます。
合計6本のシグナル全てが低い位置から揃って上昇する局面でトレンドの信頼性を最も高く見積もることができます。
CCI Multi-TimeframeThe Commodity Channel Index (CCI) is a leading oscillating momentum indicator that was developed by Donald Lambert to identify cyclical turns in commodities but can also be used on securities and bonds as well.
HOW IS IT USED ?
Lambert used the CCI to generate entry and exit signals when the CCI moved above +100% and below -100% respectively. When the CCI moves above +100%, the security enters into a strong uptrend and an entry signal is given. When the CCI moves back below +100% this position should be closed. Conversely, when the CCI moves below -100%, the security enters into a strong downtrend and an exit signal is given. When the CCI moves back above -100% this position should be closed.
In addition, an entry signal is given when the CCI bounces off of the zero line. When the CCI reaches the zero line, the security's average price is at the moving average used to calculate the CCI and when a security bounces off its moving average it is considered a good entry position as the security has pulled back to its short-term support with the bounce reaffirming the current trend.
The CCI can also be used to identify overbought and oversold levels. A security could be considered oversold when the CCI moves below -100 and overbought when it moves above +100. From an oversold level, an entry signal may be given when the CCI moves above -100. From an overbought level, an exit signal might be given when the CCI moves below +100.
Divergences can also be applied to the CCI. A positive divergence below -100 would increase the probability of a signal based on a move above -100, and a negative divergence above +100 would increase the probability of a signal based on a move back below +100.
Trend line breaks can be used to generate entry and exit signals. Trend lines can be drawn connecting the peaks and troughs. From oversold levels, a move above -100 and a trend line breakout could be used as an entry signal. Conversely, from overbought levels, a move below +100 and a trend line breakout could be used as an exit signal.
I added the possibility to add on the chart a 2nd timeframe for confirmation.
If you found this script useful, a tip is always welcome... :)
Multiplier ChartI am proposing an alternative to the percent change.
An alternative that is symmetrical to both positive and negative change, unlike percentage change.
The simple idea is to have a positive number if the reference value (called val in the script) is lower than the stock value and needs to be multiplied;
a negative number instead if the reference number is higher than the stock value, so the reference value needs to be divided.
Multiplying all by 100 to give clearer and more readable results, the Multiplier would have a huge gap between +100 and -100, because a stock multiplied by 1 or divided by 1 are the same thing.
So we need to compromise and move all positive numbers down by 100 and all negative numbers up by 100. This actually gives a similar result to percentage change, and it is actually identical in the positive range.
The fundamental difference lies on the negative range, which is completely symmetrical. So if a stock goes up 100 points one day (doubles), and the next it goes down another 100 points (halves), at the end of the second day the stock has the same value as it had at the beginning of the first day! On percentage change it would be +100% the first day and -50% the second.
We mustn't undervalue the human tendency to compare a 1% change to a -1% change, but they do not mean the same even if they seem to indicate so.
A clear example of this can be found on CMC 0.60% -3.56% -3.56% (CoinMarketCap), in which each day are shown the best and worst performing coins of the day. So you might see a +900% there in the top performing, but you'll never see a -900%, because percentage change cannot go further than -100%. It is a fundamentally asymmetric scale that can confuse people a lot especially in those fast moving new markets.ù
I am welcome to feedback and all kinds of opinions and critics.
Some interesting things to note: you can use it as a percentage change indicator or as a different perspective to a stock chart. In fact, it lets you see how big of a difference it made buying coins when they were very cheap, because when they are cheap a difference of what it might seem nothing is amplified by all the gains that the stock/coin made after. So, looking at coins charts using this indicator shows how "not flat" were the early days, which in a normal chart are flattened to 0.
Burt's Multi-EMA Ribbon 🔥 with Alerts & Shading📈 Burt’s Multi-EMA Ribbon 🔥
A sleek, professional EMA overlay designed for real traders who want fast momentum insight with minimal chart clutter.
Features:
5 core EMAs: 9, 21, 50, 100, 200 – ideal for intraday and swing analysis
Color-coded lines for instant recognition
Dynamic trend shading between EMA 9 & 21
Built-in bullish & bearish crossover alerts for momentum shifts
Overlay design keeps your chart clean and focused
How to use:
Use the EMA ribbon spacing to assess trend strength
Watch for EMA 9/21 crosses to enter early
Combine with price action or volume for confluence
🧠 Built by Burt for speed, clarity, and edge.
MA Crossover Strategy with +100 Target & Time Filter//@version=5
strategy("5 SMA Crosses Above 20 SMA", overlay=true)
// User-defined input parameters for stop loss and take profit
stopLoss = input.int(10, title="Stop Loss (points)", minval=1)
takeProfit = input.int(20, title="Take Profit (points)", minval=1)
// Define the moving averages
sma5 = ta.sma(close, 5)
sma20 = ta.sma(close, 20)
sma50 = ta.sma(close, 50)
// Detect crossovers on candle close
crossAbove = ta.crossover(sma5, sma20)
crossBelow = ta.crossunder(sma5, sma20)
// Change candle color to white when crossover occurs
barcolor(crossAbove or crossBelow ? color.white : na)
// Shade background based on price relative to the 50 SMA
backgroundGreen = close > sma50
bgcolor(backgroundGreen ? color.new(color.green, 90) : color.new(color.red, 90))
// Buy condition: 5 SMA crosses above 20 SMA and price is above 50 SMA
if (crossAbove and backgroundGreen)
strategy.entry("Buy", strategy.long)
// Sell condition: 5 SMA crosses below 20 SMA and price is below 50 SMA
if (crossBelow and not backgroundGreen)
strategy.entry("Sell", strategy.short)
// Exit conditions
if (strategy.position_size > 0) // Long position
strategy.exit("Exit Long", from_entry="Buy", stop=close - stopLoss, limit=close + takeProfit)
if (strategy.position_size < 0) // Short position
strategy.exit("Exit Short", from_entry="Sell", stop=close + stopLoss, limit=close - takeProfit)
// Plot the SMAs for reference
plot(sma5, color=color.blue, linewidth=2, title="5 SMA")
plot(sma20, color=color.orange, linewidth=2, title="20 SMA")
Gabriel's Relative Strength IndexGabriel’s RSI—The Reinvention of Relative Strength
Not your average RSI.
This is a fully reengineered Relative Strength Index that merges the power of advanced signal processing, adaptive smoothing, volume dynamics, and intelligent divergence detection into a single, modular toolkit designed for precision trading across all markets.
Whether you’re scalping crypto, swing trading equities, or dissecting futures contracts—Gabriel’s RSI adapts to your strategy with unrivaled control and clarity.
⚙️ 1. RSI Settings
RSI Length (Jurik): Set to 51 by default to mimic a 21-period standard RSI when Jurik smoothing is applied. Adjust lower (e.g., 22) to mimic a 9-period RSI. 32 would be almost ~14, 13.33 RSI.
RSI Source: The default is hlc3 for smoother RSI. Can be changed to any price-based series (close, open, etc.) for customization.
📡 VIX-Aware: Automatically switches to high/low/close during VIX spikes using a custom Z-score model if toggled. (I backtested it, and it catches bottoms better.) 📡
🎯 2. RSI Smoothing Options
MA Type: Smoothing applies to both RSI and its MA overlay simultaneously. I used to use the 56 EMA RSI, and it works well too.
Options: JMA, T3, Kalman, Laguerre, Super Smoother, ALMA, VWMA, LSMA, etc.
JMA: Best for adaptive recursive smoothing. A power of 2 and a phase of 50 are used.
T3: Smooth and lag-reduced, suitable for trend detection. The alpha is 0.7.
SMA + Bollinger Bands: Adds deviation-based envelopes for volatility spotting. BB StdDev: Only relevant if BBs are used. Controls bandwidth for overbought/oversold zones.
MA Length: Affects how smooth or reactive the RSI signal is.
📉 3. MACD Settings
Fast/Slow Length: Defaults (21/81) optimized for smoother MACD with SMA or T3. For Algo trading, EMA/JMA is best.
Signal Length: Shorter (e.g., 2) gives more reactive crossover signals; it can be increased.
Source: Default is close. Close works best for the settings I input. I also tuned some of the other MA types that worked for it.
MA Types: JMA and EMA reduce noise and increase signal generation. Select SMA for simplicity or T3 for trend-following.
Histogram: Bar colors signal strength and trend of MACD directly on your chart.
🔀 4. Directional Movement Index (DMI)
ADX Smoothing: High values (e.g., 100) offer strong trend confirmation with Hann Window smoothing 12, or 14 for either regular RMA or double smoothed.
DI Length: Affects DI+/- sensitivity. 100 ADX - 12/14 DI or 15 ADX - 35 DI are suggested, the latter for quicker boot time, as 100 bars is quite long.
Smoothing Type: Choose Hann Window for refined smoothing; RMA (SMMA) for simplicity. Double-smoothing is RMA -> Hann window, best of both types.
Volatility Type: ATR includes gaps for a full-range volatility; ADR is useful for gapless strategies, particularly OTC markets and intraday.
Plotted as area fills, 0 to 100 scaled.
Color-coded as Red (ADX), Orange (DI-), Blue (DI+).
📊 5. Volume Z-Score
%R Length: Normalizes volume to percentile range (73 swing, 112 exhaustion).
Z-Score Lengths: Compares short-term and long-term volume trends with Z-scores of volume.
Fast Z-Score < Slow Z-Score = Gives a Volume Squeeze.
Fast MA > Slow MA = Bullish Volume Divergence; volume has been fired. Not via Z-score, but instead via SMA, ALMA, and RMA of volume.
WPR Volume: Weighted %R used to highlight exhaustion/pivot points.
Plot volume bars after a volume squeeze has been fired; if bars aren't plotted, then it's under squeeze. Backtest on ES1! Prove it's good for catching bottoms below 15 minutes as well.
🧠 6. Divergence Engine
Pivot Settings: Pivot Period (12), Divergence minval Lookback (5), and max Lookback Bars (100) control sensitivity. Works well on any asset class; these are the optimal settings for the RSI.
Source Options: RSI, MACD, ADX, DI difference, or Volume %R.
Divergence Types: Regular (Mean Reversal), Hidden (Trend Continuation).
Heikin Ashi Mode: Enables use of HA candles on normal charts for smoother pivots. May distort values if your chart is H.A. so leave it unchecked then.
💥 7. Squeeze Momentum System (SQZMOM PRO)
Squeeze Types:
⚫ Wide (Black) — Regular Compression
🔴 Normal (Red) — Standard squeeze
🟡 Narrow (Yellow) — Golden squeeze
🟣 Very Narrow (Purple) — Extreme compression
🟢 Fired (Green) — Fired Squeeze = Breakout
Plotted on the very bottom of my indicator.
Momentum Bars:
🔷 Cyan = Rising
🔵 Blue = Pullback
🔴 Red = Falling
🟡 Yellow = Corrective
Plotted on the top of my indicator.
Reversal Signals: Dashed lines on momentum–JMA crossovers (DM-style pivot logic) ploted directly on the chart.
📈 8. Rate of Change (RoC)
RoC of Momentum: EMA-smoothed RoC on momentum for leading signals. Double smoothed, once and then another time for smoother signals.
RoC of Momentum → EMA → EMA → JMA Signal.
Signal Line: JMA used to filter noise and generate reversal signals.
Crossovers: Bullish/bearish signals based on RoC vs. signal line are plotted as triangles directly on your chart.
Optimized: Backtested for short-term setups like 1H or faster. Works on Daily timeframes as well for Futures and 24/7 Markets.
🕰️ 9. Multi-Timeframe Squeeze Settings
Each timeframe (Hourly, 4H, Daily, Weekly, Monthly) has:
Reversal Toggle: Enables dashed line DM-style pivots on crossovers.
MA Length: For Jurik MA smoothing on momentum.
BB/KC Thresholds: Define squeeze sensitivity per timeframe. A shorter BB/KC length, 17-14-12, responds better on lower timeframes.
Momentum Length: Tailors oscillator responsiveness; 20 is ideal.
🧮 10. BB Std. Deviation Scaling
Low-Pass Super Smoother : Smooths noise for BBs.
High-Pass Butterworth : Extracts cycles for BB Stdv. blend.
Root Mean Squared : Dynamic BB width adjustment based on market activity. True-range-based.
LP -> HP -> RMS -> Bollinger Band Multiplier (2.0)
Optional Intensify: Increases the squeeze rate * 4. Can be used for some option pricing strategies.
🧵 11. Moving Average Ribbon
4 optional MAs with full customization:
Choose from 13 MA types (incl. Kalman, Laguerre, T3, ALMA)
Color-coded for trend analysis (MA1–MA4 mimicking 9/21/50/200 periods)
Optional crossover alerts
🔔12. Alerts
RSI: Overbought/oversold reversals. Several types. (🦅 / 🕊️)
MACD: Histogram shift through zero line. (🐘 / 🐴)
DMI/ADX: Crossovers and strength conditions. The key level is the level where if DI/ADX is past this threshold, then it's considered to be trending. (🐬 / 🐋 / 🛡️)
Volume: Smart Money alerts on low-volume zones. May concentrate on ICT sessions. (🚨)
Squeeze: Alerts on all 5 squeeze states. (⚫, 🔴, 🟡, 🟣, 🟢)
Momentum: Momentum / JMA crosses and reversals. (🐂 / 🐻)
RoC: Bullish and bearish crosses. (📈 / 📉)
Divergences: Regular, hidden, and combined. (🐂 / 🐻 / 🐾 / 🐼)
MA Ribbon: Cross alert (⚔️)
VIX: VIX Z-Score past 2.0 (🏴☠️)
📊 13. Visual Output Summary
RSI Line + MA + Optional BB
MACD Histogram (Color Adaptive)
DMI/ADX Area Fills
%R Volume Bars (Smart Money)
Squeeze Dots (Circles)
Momentum Bars (Squares)
RoC Arrows (Cross Signals)
Pivot Break Lines (Dashed)
Auto-Divergence Lines & Labels
MA Ribbon Overlay (Optional)
✅ Best Practices ✅
Watch the slope of the RSI for pullbacks on a strong trend. Combine it with squeeze for exit timing.
Combine RSI Divergence with MACD histogram cross and Squeeze firing for precise entry.
Use Volume Z-Score to filter for institutional activity, and enter Long. Watch for reversals as well.
Watch RoC crossovers for fast, leading signals.
Enable Reversal Lines on 1H+ charts for breakout or breakdown pivots.
Use multi-timeframe thresholds for swing confirmation. The TFs I use the most are 2-5-15 minutes for futures and swinging with 1 hour daily and weekly. Those are the TFs I backtested.
An optional MA Ribbon is here as well; it supports 13 MA types.
🌎 Asset-Agnostic
MACD Automatically adjusts for Crypto, Forex, Stocks, Commodities, and Indices.
Custom ALMA, T3, Kalman, and Laguerre filters optimized per asset class and timeframe.
📚 Tech Highlights
Over 15,000 lines of modular, structured Pine Script v6 code.
Integration of Ehlers Cycle Theory and various other filters, one for each indicator.
Designed for visual clarity, multi-dimensional signal stacking, and low lag/high accuracy.
🌀 All 64 outputs are filled, so there might not be any more future updates. It's also a bit slow to load due to that.
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE)
A Three-Pillar Framework for Decoding Institutional Activity
🎓 THEORETICAL FOUNDATION
The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture.
This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum.
⚡ THE THREE-PILLAR ARCHITECTURE
1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT')
Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? "
Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market.
Formulaic Concept:
Coherence = f(Dominance, Synchronization)
Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers.
Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action.
The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions.
2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION')
Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? "
Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes."
Algorithmic Process:
Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events.
Node Creation: A raw node is created at the mean price of the identified candle.
Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level.
Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics.
3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING')
Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? "
Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles.
Algorithmic Process:
Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle).
Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle."
Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak).
Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum.
🔧 COMPREHENSIVE INPUT SYSTEM
Pillar I: Market Coherence Engine
Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine.
Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise.
Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions.
Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns.
Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation.
Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals.
Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves.
Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals.
Pillar II: Harmonic Liquidity Matrix
Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints.
Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels.
Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent.
Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike.
High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes.
Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest.
Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes.
High (0.6-0.8): Creates wider, more consolidated zones of liquidity.
Low (0.2-0.3): Creates more numerous, precise, and distinct levels.
Pillar III: Cyclical Resonance Matrix
Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance.
Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping.
Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading.
Institutional Signal Architecture
Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence.
Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency.
Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default.
Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals.
Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts.
🎨 ADVANCED VISUAL SYSTEM
The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed.
Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes.
Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels.
Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance.
🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment.
Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context.
Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent.
💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average.
Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry.
🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process."
Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim.
⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm.
Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy.
📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD)
The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status.
Header: Displays the script title and version.
Coherence Engine Section:
State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition.
Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing.
Liquidity Matrix Section:
Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked.
Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest.
Cycle Matrix Section:
Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy.
Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation.
Signal Status Section:
A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color.
🎯 SIGNAL GENERATION LOGIC
Aetherium's signal logic is built on the principle of strict, non-negotiable confluence.
Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market.
Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node.
For a Buy Signal: Price must be rejecting the Node from below (testing it as support).
For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance).
Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction.
Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike.
Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move.
🚀 ADVANCED TRADING STRATEGIES
The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal.
The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion.
Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future.
Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties.
Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change.
Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal.
Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics.
🔮 CONCLUSION
The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations.
It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm.
"In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung
— Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
RSI of RSI Deviation (RoRD)RSI of RSI Deviation (RoRD) - Advanced Momentum Acceleration Analysis
What is RSI of RSI Deviation (RoRD)?
RSI of RSI Deviation (RoRD) is a insightful momentum indicator that transcends traditional oscillator analysis by measuring the acceleration of momentum through sophisticated mathematical layering. By calculating RSI on RSI itself (RSI²) and applying advanced statistical deviation analysis with T3 smoothing, RoRD reveals hidden market dynamics that single-layer indicators miss entirely.
This isn't just another RSI variant—it's a complete reimagining of how we measure and visualize momentum dynamics. Where traditional RSI shows momentum, RoRD shows momentum's rate of change . Where others show static overbought/oversold levels, RoRD reveals statistically significant deviations unique to each market's character.
Theoretical Foundation - The Mathematics of Momentum Acceleration
1. RSI² (RSI of RSI) - The Core Innovation
Traditional RSI measures price momentum. RoRD goes deeper:
Primary RSI (RSI₁) : Standard RSI calculation on price
Secondary RSI (RSI²) : RSI calculated on RSI₁ values
This creates a "momentum of momentum" indicator that leads price action
Mathematical Expression:
RSI₁ = 100 - (100 / (1 + RS₁))
RSI² = 100 - (100 / (1 + RS₂))
Where RS₂ = Average Gain of RSI₁ / Average Loss of RSI₁
2. T3 Smoothing - Lag-Free Response
The T3 Moving Average, developed by Tim Tillson, provides:
Superior smoothing with minimal lag
Adaptive response through volume factor (vFactor)
Noise reduction while preserving signal integrity
T3 Formula:
T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
Where e1...e6 are cascaded EMAs and c1...c4 are volume-factor-based coefficients
3. Statistical Z-Score Deviation
RoRD employs dual-layer Z-score normalization :
Initial Z-Score : (RSI² - SMA) / StDev
Final Z-Score : Z-score of the Z-score for refined extremity detection
This identifies statistically rare events relative to recent market behavior
4. Multi-Timeframe Confluence
Compares current timeframe Z-score with higher timeframe (HTF)
Provides directional confirmation across time horizons
Filters false signals through timeframe alignment
Why RoRD is Different & More Sophisticated
Beyond Traditional Indicators:
Acceleration vs. Velocity : While RSI measures momentum (velocity), RoRD measures momentum's rate of change (acceleration)
Adaptive Thresholds : Z-score analysis adapts to market conditions rather than using fixed 70/30 levels
Statistical Significance : Signals are based on mathematical rarity, not arbitrary levels
Leading Indicator : RSI² often turns before price, providing earlier signals
Reduced Whipsaws : T3 smoothing eliminates noise while maintaining responsiveness
Unique Signal Generation:
Quantum Orbs : Multi-layered visual signals for statistically extreme events
Divergence Detection : Automated identification of price/momentum divergences
Regime Backgrounds : Visual market state classification (Bullish/Bearish/Neutral)
Particle Effects : Dynamic visualization of momentum energy
Visual Design & Interpretation Guide
Color Coding System:
Yellow (#e1ff00) : Neutral/balanced momentum state
Red (#ff0000) : Overbought/extreme bullish acceleration
Green (#2fff00) : Oversold/extreme bearish acceleration
Orange : Z-score visualization
Blue : HTF Z-score comparison
Main Visual Elements:
RSI² Line with Glow Effect
Multi-layer glow creates depth and emphasis
Color dynamically shifts based on momentum state
Line thickness indicates signal strength
Quantum Signal Orbs
Green Orbs Below : Statistically rare oversold conditions
Red Orbs Above : Statistically rare overbought conditions
Multiple layers indicate signal strength
Only appear at Z-score extremes for high-conviction signals
Divergence Markers
Green Circles : Bullish divergence detected
Red Circles : Bearish divergence detected
Plotted at pivot points for precision
Background Regimes
Green Background : Bullish momentum regime
Grey Background : Bearish momentum regime
Blue Background : Neutral/transitioning regime
Particle Effects
Density indicates momentum energy
Color matches current RSI² state
Provides dynamic market "feel"
Dashboard Metrics - Deep Dive
RSI² ANALYSIS Section:
RSI² Value (0-100)
Current smoothed RSI of RSI reading
>70 : Strong bullish acceleration
<30 : Strong bearish acceleration
~50 : Neutral momentum state
RSI¹ Value
Traditional RSI for reference
Compare with RSI² for acceleration/deceleration insights
Z-Score Status
🔥 EXTREME HIGH : Z > threshold, statistically rare bullish
❄️ EXTREME LOW : Z < threshold, statistically rare bearish
📈 HIGH/📉 LOW : Elevated but not extreme
➡️ NEUTRAL : Normal statistical range
MOMENTUM Section:
Velocity Indicator
▲▲▲ : Strong positive acceleration
▼▼▼ : Strong negative acceleration
Shows rate of change in RSI²
Strength Bar
██████░░░░ : Visual power gauge
Filled bars indicate momentum strength
Based on deviation from center line
SIGNALS Section:
Divergence Status
🟢 BULLISH DIV : Price making lows, RSI² making highs
🔴 BEARISH DIV : Price making highs, RSI² making lows
⚪ NO DIVERGENCE : No divergence detected
HTF Comparison
🔥 HTF EXTREME : Higher timeframe confirms extremity
📊 HTF NORMAL : Higher timeframe is neutral
Critical for multi-timeframe confirmation
Trading Application & Strategy
Signal Hierarchy (Highest to Lowest Priority):
Quantum Orb + HTF Alignment + Divergence
Highest conviction reversal signal
Z-score extreme + timeframe confluence + divergence
Quantum Orb + HTF Alignment
Strong reversal signal
Wait for price confirmation
Divergence + Regime Change
Medium-term reversal signal
Monitor for orb confirmation
Threshold Crosses
Traditional overbought/oversold
Use as alert, not entry
Entry Strategies:
For Reversals:
Wait for Quantum Orb signal
Confirm with HTF Z-score direction
Enter on price structure break
Stop beyond recent extreme
For Continuations:
Trade with regime background color
Use RSI² pullbacks to center line
Avoid signals against HTF trend
For Scalping:
Focus on Z-score extremes
Quick entries on orb signals
Exit at center line cross
Risk Management:
Reduce position size when signals conflict with HTF
Avoid trades during regime transitions (blue background)
Tighten stops after divergence completion
Scale out at statistical mean reversion
Development & Uniqueness
RoRD represents months of research into momentum dynamics and statistical analysis. Unlike indicators that simply combine existing tools, RoRD introduces several genuine innovations :
True RSI² Implementation : Not a smoothed RSI, but actual RSI calculated on RSI values
Dual Z-Score Normalization : Unique approach to finding statistical extremes
T3 Integration : First RSI² implementation with T3 smoothing for optimal lag reduction
Quantum Orb Visualization : Revolutionary signal display method
Dynamic Regime Detection : Automatic market state classification
Statistical Adaptability : Thresholds adapt to market volatility
This indicator was built from first principles, with each component carefully selected for its mathematical properties and practical trading utility. The result is a professional-grade tool that provides insights unavailable through traditional momentum analysis.
Best Practices & Tips
Start with default settings - they're optimized for most markets
Always check HTF alignment before taking signals
Use divergences as early warning , orbs as confirmation
Respect regime backgrounds - trade with them, not against
Combine with price action - RoRD shows when, price shows where
Adjust Z-score thresholds based on market volatility
Monitor dashboard metrics for complete market context
Conclusion
RoRD isn't just another indicator—it's a complete momentum analysis system that reveals market dynamics invisible to traditional tools. By combining momentum acceleration, statistical analysis, and multi-timeframe confluence with intuitive visualization, RoRD provides traders with a sophisticated edge in any market condition.
Whether you're scalping rapid reversals or positioning for major trend changes, RoRD's unique approach to momentum analysis will transform how you see and trade market dynamics.
See momentum's future. Trade with statistical edge.
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
AWR Pearsons R & LR Oscillator MTF1. Overview
This indicator is designed to analyze the correlation between a price series (or any custom indicator) and the bar index using Pearson’s correlation coefficient. It performs multiple linear regressions over shifted periods and then aggregates these results to create an oscillator. In addition, it integrates a multi-timeframe (MTF) analysis by retrieving the same calculations on 3 different time intervals, providing a more comprehensive view of the trend evolution.
2. User Parameters
The indicator offers several configurable parameters that allow the user to adjust both the calculations and the display:
Source (Linear Regression): The data source on which the regressions are applied (by default, the closing price).
Number of Linear Regressions (numOfLinReg): Allows choosing the number of correlation calculations (up to 10) to be carried out on different shifted periods.
Start Period (startPeriod) and Period Increment (periodIncrement): These parameters define the reference window for each regression. The calculation starts with a base period and then increases with each regression by a fixed increment, creating several time windows to assess the relationship between price evolution and time progression.
Deviation (def_deviation): Although defined, this parameter is intended to control the sensitivity of the calculations. It can be used in further developments of the indicator.
For Multi Time Frames analysis, three additional timeframes are provided through inputs in addition of the current period:
Sum up :
Timeframe 1 = current
Timeframe 2 = 30-minute (default settings)
Timeframe 3 = 1-hour (default settings)
Timeframe 4 = 4-hour (default settings)
These different timeframes allow you to obtain consistent or divergent signals over multiple resolutions, thereby enhancing the confidence of trading decisions.
3. Calculation Logic
At the core of the indicator is the f_calcConditions() function, which performs several essential tasks:
Calculating Pearson's Coefficients For each linear regression, the script uses ta.correlation() to measure the correlation between the chosen source (for example, the closing price) and the chronological index (bar_index). Up to 10 coefficients are computed over shifted windows, providing an evolving view of the linear relationship over different intervals.
Averaging the Results Once the coefficients are calculated, they are stored in an array and averaged to produce a global correlation value called avgPR_local.
Applying Moving Averages
The resulting average is then smoothed using several moving averages (SMA):
A short-term SMA (period of 14),
An intermediate SMA (period of 100),
A long-term SMA (period of 400).
These moving averages help to highlight the underlying trend of the oscillator by indicating the direction in which the correlation is moving.
Defining Trading Conditions Based on avgPR_local and its associated SMAs, multiple conditions are set to generate buy or sell signals:
Simple SMA Conditions :
Small signal :
Light blue below bar signal :
When the averaged coefficients lie between -1 and -0.63, are above the short-term SMA (14 periods), and are increasing, it may indicate a bullish dynamic (buy signal).
Orange above bar signal :
Conversely, when the value is higher (between 0.63 and 1) and below its SMA (14 periods), and are decreasing the trend is considered bearish (sell signal).
Medium signal :
Dark green signal
When the averaged coefficients lie between -1 and -0.45, are above the short-term SMA (14 periods), and are increasing, and also the average 100 is increasing. It may indicate a bullish dynamic (buy signal).
Light red signal :
Conversely, when the value is higher (between 0.45 and 1) and below its SMA (14 periods), the trend and are decreasing, and also the average 100 is decreasing. It may indicate a bearish dynamic(sell signal).
Light green signal :
When the averaged coefficients lie between -1 and -0.15, are above the short-term SMA (14 periods), and are increasing, and also the average 100 & 400 is increasing . It may indicate a bullish dynamic (buy signal).
Dark red signal :
Conversely, when the value is higher (between 0.45 and 1) and below its SMA (14 periods), the trend and are decreasing, and also the average 100 & 400 is decreasing. It may indicate a bearish dynamic(sell signal).
These additional conditions further refine the signals by verifying the consistency of the movement over longer periods. They check that the trends from the respective averages (intermediate and long-term) are in line with the direction indicated by the initial moving average.
These conditions are designed to capture moments when the oscillator's dynamics change, which can be interpreted as opportunities to enter or exit a trade.
4. Multi-Timeframes and Display
One of the main strengths of this indicator is its multi-timeframe approach.
This offers several advantages:
Comparative Analysis: Compare short-term dynamics with broader trends.
Enhanced Signal Reliability: A signal confirmed across multiple timeframes has a higher probability of success.
To visually highlight these signals on the chart, the indicator uses the plotchar() function with distinct symbols for each timeframe:
Current Timeframe: Signals are represented by the character "1"
30-Minute Timeframe: Displayed with the character "2".
1-Hour Timeframe: Displayed with the character "3".
4-Hour Timeframe: Displayed with the character "4".
The colors used are various shades of green for buy signals and shades of red/orange for sell signals, making it easy to distinguish between the different alerts.
5. Integrated Alerts
To avoid missing any trading opportunities, the indicator includes an alert condition via the alertcondition() function. This alert is triggered if any buy or sell signal is generated on any of the analyzed timeframes. The message "MTF valide" indicates that multiple timeframes are confirming the signal, enabling more informed decision-making.
6. How to Use This Indicator
Installation and Configuration: Copy the script into the TradingView Pine Script editor and add it to your chart. The default parameters can be tuned according to market behavior or personal preferences regarding sensitivity and responsiveness.
Interpreting the Signals:
Watch for the symbols on the chart corresponding to each timeframe.
A buy signal appears as a specific symbol below the bar (indicating a bullish condition based on a rising or less negative correlation), while a sell signal appears above the bar.
Multi-Timeframe Analysis: By comparing signals across timeframes, you can filter out false signals. For example, if the short-term timeframe shows a buy signal but the 4-hour timeframe indicates a bearish trend, you may need to reassess your position.
Adjusting the Settings: Depending on the asset type or market volatility, you might need to tweak the periods (startPeriod, periodIncrement) or the number of linear regressions to generate signals that better align with the price dynamics.
Using Alerts: Activate the built-in alert feature so that TradingView notifies you as soon as a multi-timeframe signal is detected. This ensures you stay informed even if you are not continuously monitoring the chart.
In Conclusion
The AWR Pearsons R & LR Oscillator MTF is a powerful tool for traders seeking a detailed understanding of market trends by combining statistical rigor (via Pearson's correlation coefficient) with a multi-timeframe approach. It is capable of generating clear entry and exit signals, visualized with specific symbols and colors depending on the timeframe. By adjusting the parameters to match your trading strategy and leveraging the alert system, you now have a robust instrument for making well-informed market decisions.
Feel free to dive deeper into each component and experiment with different configurations to see how the oscillator integrates with your overall technical analysis strategy. Enjoy exploring its potential and refining your trading approach!
