Inverse Fisher Transform on STOCHASTIC (modified graphics)Modified the graphic representation of the script from John Ehlers - From California, USA, he is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception). John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or sell. Hopefully, the signals are clear and unequivocal. However, more often than not your decision to pull the trigger is accompanied by crossing your fingers. Even if you have placed only a few trades you know the drill. In this article I will show you a way to make your oscillator-type indicators make clear black-or-white indication of the time to buy or sell. I will do this by using the Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of your indicators. In the past12 I have noted that the PDF of price and indicators do not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the familiar bell-shaped curve where the long “tails” mean that wide deviations from the mean occur with relatively low probability. The Fisher Transform can be applied to almost any normalized data set to make the resulting PDF nearly Gaussian, with the result that the turning points are sharply peaked and easy to identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is compressive. The Inverse Fisher Transform is found by solving equation 1 for x in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If the input falls between –0.5 and +0.5, the output is nearly the same as the input. For larger absolute values (say, larger than 2), the output is compressed to be no larger than unity. The result of using the Inverse Fisher Transform is that the output has a very high probability of being either +1 or –1. This bipolar probability distribution makes the Inverse Fisher Transform ideal for generating an indicator that provides clear buy and sell signals.
Pesquisar nos scripts por "ha溢价率"
Strenght and MomentumThe scope of this script is to measure momentum and strenght of EURO and DOLLAR using their indexes.
Forza (line) above 0 means EURO is stonger than DOLLAR
Momento (histogram) above 0 means EURO has a positive momentum against DOLLAR
The added value to see MACD and RSI directly on EURUSD chart is that indexes consider also other pairs so their RSI and MACD has a larger view on forex markets.
Script has also an option for multi timeframes.
I think that could be used as filters for LONG or SHORT positions in lower time frames.
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy
Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength.
My sell strategy is triggered by either one of these conditions:
the EMA(6) of the close value is crossing under the trailing stop value (green) or
the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength.
The trailing stop value (green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between the high and low values.
The scripts shows a lot of graphical information:
The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade.
the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end))
the EMA and SMA values for both buy and sell signals are shown as a line
the buy and sell(close) signals are labeled in blue
How to use this strategy?
Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR).
Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters)
Then keep using these parameters for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Important : optimizing these parameters is no guarantee for future winning trades!
Here are the parameters:
Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20)
Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100)
Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120)
Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20)
Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100)
Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120)
Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20)
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing):
BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20
NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78%
BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9
NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55%
AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8
NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938%
TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14
NetProfit: 129%, #Trade
Inverse Fisher Transform COMBO STO+RSI+CCIv2 by KIVANÇ fr3762A combined 3in1 version of pre shared INVERSE FISHER TRANSFORM indicators on RSI , on STOCHASTIC and on CCIv2 to provide space for 2 more indicators for users...
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function ( PDF ) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity . The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
Creator: John EHLERS
Inverse Fisher Transform on SMI (Stochastic Momentum Index)Inverse Fisher Transform on SMI (Stochastic Momentum Index)
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity. The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
DepthHouse - Moving Average ChannelsThe indicator Moving Average Channels was created for experimental purposes due to the parabolic moves BTC has made in the recent past.
How it works:
The basis, or center line, is a standard moving average that is set by the user.
The bands are then a customizable percentage of the basis.
Which based on the settings, could serve as possible support and resistance.
DepthHouse – Moving Average Channels has been published for you all to see and try for yourselves.
Maybe this indicator has uses elsewhere? If you find something feel free to post it in the comments below!
If you like this indicator, please drop a like or comment!
They are very much appreciated!
Be sure to go to my profile and check out my other indicators!
OHLC Volatility Estimators by @Xel_arjonaDISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is by Creative-Commons as TradingView's regulations. Any use, copy or re-use of this code should mention it's origin as it's authorship.
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED AS DEBUGING CODE The models included in the function have been taken from openly sources on the web so they could have some errors as in the calculation scheme and/or in it's programatic scheme. Debugging are welcome.
WHAT'S THIS?
Here's a full collection of candle based (compressed tick) Volatility Estimators given as a function, openly available for free, it can print IMPLIED VOLATILITY by an external symbol ticker like INDEX:VIX.
Models included in the volatility calculation function:
CLOSE TO CLOSE: This is the classic estimator by rule, sometimes referred as HISTORICAL VOLATILITY and is the must common, accepted and widely used out there. Is based on traditional Standard Deviation method derived from the logarithm return of current close from yesterday's.
ELASTIC WEIGHTED MOVING AVERAGE: This estimator has been used by RiskMetriks®. It's calculation is based on an ElasticWeightedMovingAverage Standard Deviation method derived from the logarithm return of current close from yesterday's. It can be viewed or named as an EXPONENTIAL HISTORICAL VOLATILITY model.
PARKINSON'S: The Parkinson number, or High Low Range Volatility, developed by the physicist, Michael Parkinson, in 1980 aims to estimate the Volatility of returns for a random walk using the high and low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval. n=10, 20, 30, 60, 90, 120, 150, 180 days.
ROGERS-SATCHELL: The Rogers-Satchell function is a volatility estimator that outperforms other estimators when the underlying follows a Geometric Brownian Motion (GBM) with a drift (historical data mean returns different from zero). As a result, it provides a better volatility estimation when the underlying is trending. However, this Rogers-Satchell estimator does not account for jumps in price (Gaps). It assumes no opening jump. The function uses the open, close, high, and low price series in its calculation and it has only one parameter, which is the period to use to estimate the volatility.
YANG-ZHANG: Yang and Zhang were the first to derive an historical volatility estimator that has a minimum estimation error, is independent of the drift, and independent of opening gaps. This estimator is maximally 14 times more efficient than the close-to-close estimator.
LOGARITHMIC GARMAN-KLASS: The former is a pinescript transcript of the model defined as in iVolatility . The metric used is a combination of the overnight, high/low and open/close range. Such a volatility metric is a more efficient measure of the degree of volatility during a given day. This metric is always positive.
Fractals and Levels by JustUncleLEven though there are a many other Fractal and Level indicators, this indicator has some unique features. The indicator will display Fractals, fractal levels and HH/LL points, they will only be drawn after they have completed. Also the indicator has options to :
Show Ideal Fractals Only.
Use Renko Style Fractals, where open/close values are used instead of high/low to find Fractals. This is used to show the correct Fractals when Renko Wicks are enabled.
Has an optional Filter to only display Fractals that are above/below a MA Ribbon.
References:
This code is based on Fractal Levels V8 by RicardoSantos
This is a Renko Chart with "Renko Style Fractals" enabled, notice that the wicks are ignored and only the true Bricks are used for Fractals:
Adaptive Donchian ChannelThis indicator adds a level of adaptivity to the simple Donchian Channel by adjusting the sensitivity (lookback periods) of the channel's upper and lower bounds based on the amount of time that has elapsed since the price has hit/expanded the channel boundaries. Comparing the results of this indicator to the standard Donchian Channel, the readier level of responsiveness may prove self-evident.
METHODOLOGY:
Specifically, the more recently the channel was expanded in one direction, the longer the lookback period grows in that direction. Conversely, if the channel has not been expanded in a given direction, the lookback period will contract so as to allow for a tighter channel.
For example, let the initial lookback period be 20 bars and let the factor argument be 0.1 (or 2 bars to start, as 20*0.1 = 2). Now say the current bar sets a new 20-period high. Then the lookback period for the upper bound is expanded by 2 bars to 22, and the lookback period for the lower bound is contracted by 2 bars to 18, thereby making it simultaneously harder to set new highs and easier to set new lows (and vice versa for hitting new lows). If neither a new high nor a new low is formed, both periods contract by the given factor.
Guth_3X_ConfirmThis indicator has three built in indicators based on the SMA of HIGH, SMA of LOW, and Stochastic. The baseline indicator is the retreats after departures from SMA of HIGH and LOW.
The first time a HIGH that is above the SMA HIGH has a lower HIGH but it still above the SMA HIGH, a (-) will appear at the bottom. This signals an aggressive entry point for potential coming downtrend. The second time the HIGH produces a lower high but is still above the SMA HIGH, a (S) will appear at the bottom which signals a more conservative entry point for potential coming downtrend. All of the opposite information is true of reversals beyond the SMA LOW.
When these reversals appear the same time the Stochastic is overbought or oversold, a red bar (overbought and potentially coming down) or a green bar (oversold and potentially coming up) will appear. NOTE: Aggressive symbols occur more often and will always occur when a conservative symbol appears. When a conservative indicator and respective overbought/oversold level occur at the same time, the bar is darker in color.
You can enter positions at any one of the indicators, however, the darker bars are what I look for. This has a high success rate but cannot guarantee results every time. I recommend adjusting the SMA, and Stoch parameters as well as time periods. I have had success with this indicator while day trading the 5, 10, 15, 30, 65 minute periods as well as daily and weekly periods. Every symbol traded can provide differing results based on the parameters used.
Please feel free to leave feedback and I know this can work well for you!
AlphaAlpha is a measure of the active return on an investment, the performance of that investment compared to the S&P500 index, where 0.01 = 1%
alpha < 0: the investment has earned too little for its risk (or, was too risky for the return)
alpha = 0: the investment has earned a return adequate for the risk taken
alpha > 0: the investment has a return in excess of the reward for the assumed risk
Mister Transistor 3.0This is a general purpose very flexible program to test the effectiveness of HA bars.
Please note that if you are charting at tradingview using Heikin-Ashi charting, your system will be trading fictitious prices even if you check the "use real prices" box. Thought you might like to know that before you lose all your money.
This program performs the HA calcs internally thus allowing you to use HA bars on a standard bar chart and obtaining real prices for your trades.
Courtesy of Boffin Hollow Lab
Author: Tarzan the Ape Man
Trailing Sharpe RatioThe Sharpe ratio allows you to see whether or not an investment has historically provided a return appropriate to its risk level. A Sharpe ratio above one is acceptable, above 2 is good, and above 3 is excellent. A Sharpe ratio less than one would indicate that an investment has not returned a high enough return to justify the risk of holding it. Interesting in this example, SPY's one year avg Sharpe ratio is above 3. This would mean on average SPY returns 3x better returns than the risk associated with holding it, implying there is some sort of underlying value to the investment.
When the sharpe ratio is above its signal, this implies the investment is currently outperforming compared to its typical return, below the signal means the investment is currently under performing. A negative Shape would mean that the investment has not provided a positive return, and may be a possible short candidate.
Zweig Market Breadth Thrust Indicator [LazyBear]The Breadth Thrust (BT) indicator is a market momentum indicator developed by Dr. Martin Zweig. According to Dr. Zweig a Breadth Thrust occurs when, during a 10-day period, the Breadth Thrust indicator rises from below 40 percent to above 61.5 percent.
A "Thrust" indicates that the stock market has rapidly changed from an oversold condition to one of strength, but has not yet become overbought. This is very rare and has happened only a few times. Dr. Zweig also points out that most bull markets begin with a Breadth Thrust.
All parameters are configurable. You can draw BT for NYSE, NASDAQ, AMEX or based on combined data (i.e., AMEX+NYSE+NASD). There is also a "CUSTOM" mode supported, so you can enter your own ADV/DEC symbols.
More info:
Definition: www.investopedia.com
A Breadth Thrust Signal: www.mcoscillator.com
A Rare "Zweig" Buy Signal: www.moneyshow.com
Zweig Breadth Thrust: recessionalert.com
List of my public indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
KK_Traders Dynamic Index_Bar HighlightingHey guys,
this is one of my favorite scripts as it represents a whole trading system that has given me very good results!
I have only used it on Bitcoin so far but I am sure it will also work for other instruments.
The original code to this was created by LazyBear, so all props to him for this great script!
I have linked his original post down below.
You can find the full rules to the system in this PDF (which has also been taken from LBs post):
www.forexmt4.com
Here is a short summary of the rules:
Go long when (all conditions have to be met):
The green line is above 50
The green line is above the red line
The green line is above the orange line
The close is above the upper Band of the Price Action Channel
The candles close is above its open
(The green line is below 68)
Go short when (all conditions have to be met):
The green line is below 50
The green line is below the red line
The green line is below the orange line
The close is below the lower band of the Price Action Channel
The candles close is below its open
(The green line is above 32)
Close when:
Any of these conditions aren't true anymore.
I have marked two of the rules in brackets as they seem to cut out a lot of the profits this system generates. You can choose to still use these rules by checking the box that says "Use Original Ruleset" in the options.
The system also contains rules regarding the Heiken Ashi bars. However these aren't as specific as the other rules. This is where your personal judgement comes in and this part is hard to explain. Take a look at the PDF I have linked to get a better understanding.
So far, this is just the TDI trading system and LBs script, now what have I changed?
I have incorporated the Price Action Channel to the system and changed it so that it highlights the bars whenever the system is giving a signal. As long as the bars are green the system is giving a long signal, as long as they are red the system is giving a short signal. Keep in mind that this doesn't consider the bar size of the HA bars. I recommend coloring all bars grey via the chart settings in order to be able to see the bar highlighting properly.
I have also published the Price Action Channel seperately in case some of you wish to view the Channel.
I am fairly new to creating scripts so use it with caution and let me know what you think!
LBs original post:
The seperate Price Action Channel script:
CM Stochastic POP Method 1 - Jake Bernstein_V1A good friend ucsgears recently published a Stochastic Pop Indicator designed by Jake Bernstein with a modified version he found.
I spoke to Jake this morning and asked if he had any updates to his Stochastic POP Trading Method. Attached is a PDF Jake published a while back (Please read for basic rules, which also Includes a New Method). I will release the Additional Method Tomorrow.
Jake asked me to share that he has Updated this Method Recently. Now across all symbols he has found the Stochastic Values of 60 and 30 to be the most profitable. NOTE - This can be Significantly Optimized for certain Symbols/Markets.
Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach how to create Trading Systems and how to Optimize the correct way.
Below are a few Strategy Results....Soon You Will Be Able To Find Results Like This Yourself on TradingView.com
BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005
Strategy 1:
Go Long When Stochastic Crosses Above 60. Go Short When Stochastic Crosses Below 30. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value.
Results:
Total Trades = 164
Profit = 50, 126 Pips
Win% = 38.4%
Profit Factor = 1.35
Avg Trade = 306 Pips Profit
***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6
Strategy 2:
Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule.
Results:
Total Trades = 164
Profit = 62, 876 Pips!!!
Win% = 38.4%
Profit Factor = 1.44
Avg Trade = 383 Pips Profit
***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6
Strategy 3:
Rules - Proprietary Optimization Jake Will Teach. Only added 1 Additional Exit Rule.
Results:
Winning Percent Increases to 72.6%!!! , Same Amount of Trades.
***Most Consecutive Wins = 21 ...Most Consecutive Losses = 4
Indicator Includes:
-Ability to Color Candles (CheckBox In Inputs Tab)
Green = Long Trade
Blue = No Trade
Red = Short Trade
-Color Coded Stochastic Line based on being Above/Below or In Between Entry Lines.
Link To Jakes PDF with Rules
dl.dropboxusercontent.com
We Are Witnessing A Historical Event With A Clear Outcome!!!"Full Disclosure: I came across this information from www.SentimenTrader.com
I have no financial affiliation…They provide incredible statistical facts on
The General Market, Currencies, and Futures. They offer a two week free trial.
I Highly Recommend.
The S&P 500 has gone 43 trading days without a 1% daily move, up or down.
which is the equivalent of two months and one day in trading days.
During this stretch, the S&P has gained more than 4%,
and it has notched a 52-week high recently as well.
Since 1952, there were nine other precedents. All of
these went 42 trading days without a 1% move, all of
them saw the S&P gain at least 4% during their streaks,
and all of them saw the S&P close at a 52-week highs.
***There was consistent weakness a week later, with only three
gainers, and all below +0.5%.
***After that, stocks did better, often continuing an Extraordinary move higher.
Charts can sometimes give us a better nuance than
numbers from a table, and from the charts we can see a
general pattern -
***if stocks held up well in the following
weeks, then they tended to do extremely well in the
months ahead.
***If stocks started to stumble after this two-
month period of calm, however, then the following months
tended to show a lot more volatility.
We already know we're seeing an exceptional market
environment at the moment, going against a large number
of precedents that argued for weakness here, instead of
the rally we've seen. If we continue to head higher in
spite of everything, these precedents would suggest that
we're in the midst of something that could be TRULY EXTRAORDINARY.
Trading Strategy based on BB/KC squeeze**** [Edit: New version (v02) posted, see the comments section for the code *****
Simple strategy. You only consider taking a squeeze play when both the upper and lower Bollinger Bands go inside the Keltner Channel. When the Bollinger Bands (BOTH lines) start to come out of the Keltner Channel, the squeeze has been released and a move is about to take place.
I have added more support indicators -- I highlight the bullish / bearish KC breaches (using GREEN/RED crosses) and a SAR to see where price action is trending.
Appreciate any feedback. Enjoy!
Color codes for v02:
----------------------------
When both the upper and lower Bollinger Bands go inside the Keltner Channel, the squeeze is on and is highlighted in RED.
When the Bollinger Bands (BOTH lines) start to come out of the Keltner Channel, the squeeze has been released and is highlighted in GREEN.
When one of the Bollinger Bands is out of Keltner Channel, no highlighting is done (this means, the background color shows up, so don't get confused if you have RED/GREEN in your chart's bground :))
Color codes for v01:
----------------------------
When both the upper and lower Bollinger Bands go inside the Keltner Channel, the squeeze is on and is highlighted in YELLOW.
When the Bollinger Bands (BOTH lines) start to come out of the Keltner Channel, the squeeze has been released and is highlighted in BLUE.
Trinity Dynamic ATR Levels (Saty)This is an updated version of the SATY ATR levels ()
Trinity Dynamic ATR Levels
The core logic is 100 % identical: same higher-timeframe ATR calculation, same trigger at ~23.6 %, same Fibonacci and extension levels, same 8-21-34 EMA ribbon for the trend color in the table, and the table itself looks exactly like the original again (4 rows, clean layout, no extra target row). The visual and usability upgrades you now have that the original does not:
Lower Trigger line is now red instead of yellow, Upper Trigger line is now green instead of aqua/cyan to indicate to go long or short.
Every single level group has its own color input so you can customize everything (previous close, fib levels, 61.8 %, 100 % ATR, extensions, 200 %, 300 %, etc.) without touching the code. Every plotted level now has a clear text label on the right side of the chart (“Prev Close”, “Lower Trig”, “Upper Trig”, “-61.8 %”, “+100 %”, “-200 %”, etc.) so you instantly know what you’re looking at.
A new input called “Target Distance (×ATR)” lets you decide how far your profit target is (default 1.0 = +100 % ATR, but you can set 1.618, 2.0, 2.618, etc. instantly).
As soon as price closes above the Upper Trigger or below the Lower Trigger, a big, obvious target box automatically appears on the right side of the screen showing the exact dollar target price for the active long or short (green box for longs, red box for shorts). When there is no active trigger, the box disappears and the table stays perfectly clean.
In short, you now have the exact same beloved Saty ATR indicator everyone uses, but with red/green triggers, full color control, level labels, and a beautiful dynamic target box that only shows up when you actually have a trade on — all while keeping the original clean 4-row table untouched. It’s the cleanest and most professional version you’ll find anywhere. Enjoy! 🚀
Global M2 Money Supply Growth (GDP-Weighted)📊 Global M2 Money Supply Growth (GDP-Weighted)
This indicator tracks the weighted aggregate M2 money supply growth across the world's four largest economies: United States, China, Eurozone, and Japan. These economies represent approximately 69.3 trillion USD in combined GDP and account for the majority of global liquidity, making this a comprehensive macro indicator for analyzing worldwide monetary conditions.
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🔧 KEY FEATURES:
📈 GDP-Weighted Aggregation
Each economy is weighted proportionally by its nominal GDP using 2025 IMF World Economic Outlook data:
• United States: 44.2% (30.62 trillion USD)
• China: 28.0% (19.40 trillion USD)
• Eurozone: 21.6% (15.0 trillion USD)
• Japan: 6.2% (4.28 trillion USD)
The weights are fully adjustable through the indicator settings, allowing you to update them annually as new IMF forecasts are released (typically April and October).
⏱️ Multiple Time Period Options
Choose between three calculation methods to analyze different timeframes:
• YoY (Year-over-Year): 12-month growth rate for identifying long-term liquidity trends and cycles
• MoM (Month-over-Month): 1-month growth rate for detecting short-term monetary policy shifts
• QoQ (Quarter-over-Quarter): 3-month growth rate for medium-term trend analysis
🔄 Advanced Offset Function
Shift the entire indicator forward by 0-365 days to test lead/lag relationships between global liquidity and asset prices. Research suggests a 56-70 day lag between M2 changes and Bitcoin price movements, but you can experiment with different offsets for various assets (equities, gold, commodities, etc.).
🌍 Individual Country Breakdown
Real-time display of each economy's M2 growth rate with:
• Current percentage change (YoY/MoM/QoQ)
• GDP weight contribution
• Color-coded values (green = monetary expansion, red = contraction)
📊 Smart Overlay Capability
Displays directly on your main price chart with an independent left-side scale, allowing you to visually correlate global liquidity trends with any asset's price action without cluttering the chart.
🔧 Customizable GDP Weights
All GDP values can be adjusted through the indicator settings without editing code, making annual updates simple and accessible for all users.
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📡 DATA SOURCES:
All M2 money supply data is sourced from ECONOMICS (Trading Economics) for consistency and reliability:
• ECONOMICS:USM2 (United States)
• ECONOMICS:CNM2 (China)
• ECONOMICS:EUM2 (Eurozone)
• ECONOMICS:JPM2 (Japan)
All values are normalized to USD using current daily exchange rates (USDCNY, EURUSD, USDJPY) before GDP-weighted aggregation, ensuring accurate cross-country comparisons.
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💡 USE CASES & APPLICATIONS:
🔹 Liquidity Cycle Analysis
Track global monetary expansion/contraction cycles to identify when central banks are coordinating loose or tight monetary policies.
🔹 Market Timing & Risk Assessment
High M2 growth (>10%) historically correlates with risk-on environments and rising asset prices across crypto, equities, and commodities. Negative M2 growth signals monetary tightening and potential market corrections.
🔹 Bitcoin & Crypto Correlation
Compare with Bitcoin price using the offset feature to identify the optimal lag period. Many traders use 60-70 day offsets to predict crypto market movements based on liquidity changes.
🔹 Macro Portfolio Allocation
Use as a regime filter to adjust portfolio exposure: increase risk assets during liquidity expansion, reduce during contraction.
🔹 Central Bank Policy Divergence
Monitor individual country metrics to identify when major central banks are pursuing divergent policies (e.g., Fed tightening while China eases).
🔹 Inflation & Economic Forecasting
Rapid M2 growth often leads inflation by 12-18 months, making this a leading indicator for future inflation trends.
🔹 Recession Early Warning
Negative M2 growth is extremely rare and has preceded major recessions, making this a valuable risk management tool.
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📊 INTERPRETATION GUIDE:
🟢 +10% or Higher
Aggressive monetary expansion, typically during crises (2001, 2008, 2020). The COVID-19 period saw M2 growth reach 20-27%, which preceded significant inflation and asset price surges. Strong bullish signal for risk assets.
🟢 +6% to +10%
Above-average liquidity growth. Central banks are providing stimulus beyond normal levels. Generally favorable for equities, crypto, and commodities.
🟡 +3% to +6%
Normal/healthy growth rate, roughly in line with GDP growth plus 2% inflation targets. Neutral environment with moderate support for risk assets.
🟠 0% to +3%
Slowing liquidity, potential tightening phase beginning. Central banks may be raising rates or reducing balance sheets. Caution warranted for high-beta assets.
🔴 Negative Growth
Monetary contraction - extremely rare. Only occurred during aggressive Fed tightening in 2022-2023. Strong warning signal for risk assets, often precedes recessions or major market corrections.
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🎯 OPTIMAL USAGE:
📅 Recommended Timeframes:
• Daily or Weekly charts for macro analysis
• Monthly charts for very long-term trends
💹 Compatible Asset Classes:
• Cryptocurrencies (especially Bitcoin, Ethereum)
• Equity indices (S&P 500, NASDAQ, global markets)
• Commodities (Gold, Silver, Oil)
• Forex majors (DXY correlation analysis)
⚙️ Suggested Settings:
• Default: YoY calculation with 0 offset for current liquidity conditions
• Bitcoin traders: YoY with 60-70 day offset for predictive analysis
• Short-term traders: MoM with 0 offset for recent policy changes
• Quarterly rebalancers: QoQ with 0 offset for medium-term trends
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📋 VISUAL DISPLAY:
The indicator plots a blue line showing the selected growth metric (YoY/MoM/QoQ), with a dashed reference line at 0% to clearly identify expansion vs. contraction regimes.
A comprehensive table in the top-right corner displays:
• Current global M2 growth rate (large, prominent display)
• Individual country breakdowns with their GDP weights
• Color-coded growth rates (green for positive, red for negative)
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🔄 MAINTENANCE & UPDATES:
GDP weights should be updated annually (ideally in April or October) when the IMF releases new World Economic Outlook forecasts. Simply adjust the four GDP input parameters in the indicator settings - no code editing required.
The relative GDP proportions between the Big 4 economies change very gradually (typically <1-2% per year), so even if you update weights once every 1-2 years, the impact on the indicator's accuracy is minimal.
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💭 TRADING PHILOSOPHY:
This indicator embodies the principle that "liquidity drives markets." By tracking the combined M2 money supply of the world's largest economies, weighted by their economic size, you gain insight into the fundamental liquidity conditions that underpin all asset prices.
Unlike single-country M2 indicators, this GDP-weighted approach captures the true global picture, accounting for the fact that US monetary policy has 2x the impact of Japanese policy due to economic size differences.
Perfect for macro-focused traders, long-term investors, and anyone seeking to understand the "tide that lifts all boats" in financial markets.
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Created for traders and investors who incorporate global liquidity trends into their decision-making process. Best used alongside other technical and fundamental analysis tools for comprehensive market assessment.
⚠️ Disclaimer: M2 money supply is a lagging macroeconomic indicator. Past correlations do not guarantee future results. Always use proper risk management and combine with other analysis methods.
Fear & Greed Oscillator - Risk SentimentThe Fear & Greed Oscillator – Risk Sentiment is a macro-driven sentiment indicator inspired by the popular Fear & Greed Index , but rebuilt from the ground up using real, market-based economic data and statistical normalization.
While the traditional Fear & Greed Index uses components like volatility, volume, and social media trends to estimate sentiment, this version is powered by the Copper/Gold ratio — a historically respected gauge of macroeconomic confidence and risk appetite.
📈 Expansion vs. Contraction Theory
At the heart of this oscillator is a simple macroeconomic insight:
🟢 Copper performs well during periods of economic expansion and risk-on behavior (industrials, construction, manufacturing growth).
🔴 Gold performs well during periods of economic contraction , as a classic risk-off, capital-preserving asset.
By tracking the ratio of Copper to Gold prices over time and converting it into a Z-score , this tool shows when macro sentiment is statistically stretched toward greed or fear — based on how unusually strong one side of the ratio is relative to its historical average.
⚙️ How It Works
The script takes two user-defined tickers (default: Copper and Gold) and calculates their ratio.
It then applies Z-score normalization over a user-defined period (default: 200 bars).
A color gradient line is plotted:
🔴 Z < -2 = Extreme Fear
🟣 -2 to 0 = Mild Fear to Neutral
🔵 0 to 2 = Neutral to Greed
🟢 Z > 2 = Extreme Greed
Visual guides at ±1, ±2, ±3 standard deviations give immediate context.
Includes alert conditions when the Z-score crosses above +2 (Greed) or below -2 (Fear).
🔔 Alerts
“Z-Score has entered the Greed Zone ” when Z > 2
“Z-Score has entered the Fear Zone ” when Z < -2
These are designed to help catch macro sentiment extremes before or during large shifts in market behavior.
⚠️ Disclaimer
This indicator is a macro sentiment tool, not a direct trading signal. While the Copper/Gold ratio often reflects economic risk trends, correlation with risk assets (like Bitcoin or equities) is not guaranteed and may vary by cycle. Always use this indicator in conjunction with other tools and contextual analysis.
WTC Step Buy Step Edition CbyCarlo📊 WT Cross Modified – Step Buy Step Edition (v4)
WTC_StepBuyStep_Edition is an enhanced, practical, and optimized version of the classic WaveTrend (WT) Cross Indicator.
Developed for the Step Buy Step project, this tool helps traders identify market momentum shifts, structural price zones, and potential reversal areas with high clarity and precision.
🔍 Concept & Purpose
This indicator builds upon the established WaveTrend / LazyBear logic and extends it with additional structural intelligence.
The goal is to make overbought/oversold phases and trend reversals easier to spot — while also highlighting historically validated price zones where the market has previously reacted strongly.
⚙️ Key Features
1️⃣ WT Cross Signals
WT1 (yellow) and WT2 (purple) visualize market momentum.
A WT1 cross above WT2 while below the Oversold zone (−53) can indicate potential Long opportunities.
A WT1 cross below WT2 while above the Overbought zone (+53) can indicate potential Short opportunities.
Signals only confirm after candle close to prevent repainting.
2️⃣ Dynamic “WT SignalZone” Panel
Displayed in the top-right corner, this panel shows the last three valid price levels derived from WT signals:
🟢 LonLev – Buy support levels from previous WT Long signals
🔴 ShoLev – Sell resistance levels from previous WT Short signals
These zones act as objective support/resistance structures, based on historical momentum turning points — not subjective lines.
3️⃣ Flexible Calculation Modes
Choose how levels are derived from each WT signal:
Pullback 50% → Midpoint of the signal candle (high+low)/2
Close → Close price of the signal candle
Next Open → Open of the following bar (ideal for system testing)
📈 How to Interpret the Indicator
Market Condition WT Event Meaning
WT1 < −53 & CrossUp Long Signal Potential reversal / buy zone
WT1 > +53 & CrossDown Short Signal Potential exhaustion / sell zone
Price revisits LonLev Support Re-entry or bounce zone
Price revisits ShoLev Resistance Profit-taking or short setup zone
This makes the tool highly effective for:
Swing traders
Zone-based trading strategies
Systematic re-entries
Identifying structural turning points
🧠 Advantages
No repainting (signals confirmed only after bar close)
Works on all timeframes (from intraday to weekly)
Clean overview without clutter or excessive chart markers
Excellent as a filter to confirm market context
💬 Best Use Case
Use WTC_StepBuyStep_Edition as a contextual confirmation tool.
It does not replace a full trading system — but it gives you objective, repeatable, and statistically relevant zones where the market has reacted before.
Combine it with price action, volume analysis, or trend tools for even stronger setups.
© Step Buy Step • Step-Buy-Step.com
Educational trading tool intended for market analysis.
Not financial advice.
IDRV – Market Structure & Projection ("cup and handle")1. Market Context
1. IDRV has completed a multi-month bottoming structure resembling a rounded accumulation base.
2. Price has broken above local resistance, confirming a bullish shift in trend.
3. RSI signals alternating bear/bull divergences, showing momentum compression before expansion.
2. Accumulation & Breakout Structure
4. Multiple higher lows since early 2024 indicate sustained accumulation.
5. The breakout above the neckline marks the beginning of an upward trend cycle.
6. Volume and structure support continuation rather than a fake-out.
3. Bullish Continuation Zone
7. The chart highlights a bullish expansion zone between $38 and $42.
8. Holding above this zone confirms trend strength and supports further upside.
9. A clean retest in this area offers a high-probability reload opportunity.
4. Projection Target
10. The projected upside shows a potential +56% move, targeting the $48–$52 region.
11. This aligns with previous supply zones and Fibonacci extension symmetry.
12. Price is expected to follow an ascending impulse pattern into 2026.
5. Risk Management
13. Invalidations occur below the $34–$35 support band where trend structure breaks.
14. A loss of this zone signals a likely return to the accumulation range.
15. Watch RSI bear signals during the climb for early signs of exhaustion.
6. Summary
16. Rounded base → Breakout → Retest → Expansion.
17. Structure supports continued bullish momentum into 2026.
18. Target zone remains $48–$52 if support is maintained.
