Broadview Delta (ROC)The Broadview Delta (ROC) is a trading indicator designed to provide insights into significant price changes in financial markets. ROC stands for Rate of Change, and it measures the percentage difference between the current price and a price from a specific number of periods ago. The Broadview Delta takes the concept of ROC a step further by incorporating bands of significance based on the highest and lowest price values within a defined time window. This allows traders to identify significant changes in price that are directly correlated with recent highs and lows.
The ROC indicator is widely used by traders and investors to assess the momentum and strength of price movements. It is particularly helpful in identifying potential trend reversals, overbought or oversold conditions, and divergences between price and momentum. By comparing the current price to a historical price point, ROC provides a normalized measurement of price change, enabling traders to gauge the speed and magnitude of market movements.
The Broadview Delta builds upon the traditional ROC by setting bands of significance based on recent highs and lows. These bands provide a contextual reference point for evaluating the significance of price changes. When the current price exceeds a significant upper band, it suggests a potential overbought condition, indicating that the price may be due for a correction. Conversely, if the current price falls below a significant lower band, it signals a potential oversold condition, implying that the price may be primed for a rebound. The bands of significance allow traders to identify crucial price levels where significant market reactions are likely to occur.
By mapping significant changes in price in relation to recent highs and lows, the Broadview Delta offers traders a clearer picture of market dynamics. It helps traders identify critical inflection points where price action is likely to encounter resistance or support. This information empowers traders to make informed decisions about entering or exiting trades, setting profit targets, and placing stop-loss orders.
The Broadview Delta indicator can be applied to various financial instruments, such as stocks, commodities, currencies, and indices. It can be used on different timeframes, ranging from intraday charts to longer-term charts, depending on the trader's preferred trading style and objectives.
The Broadview Delta (ROC) is a powerful trading indicator that combines the principles of the Rate of Change with bands of significance based on recent highs and lows. By providing a direct correlation between significant price changes and recent price extremes, it enhances the ability of traders to identify crucial market turning points. Incorporating the Broadview Delta into trading strategies can improve decision-making, increase the accuracy of trade entries and exits, and ultimately contribute to more profitable trading outcomes.
التقلب
Volatility Adjusted ADX (VADX)I sincerely wish to express my heartfelt gratitude to the vast community of coders on TradingView who have previously crafted various Average Directional Index (ADX) scripts. Their innovative approaches have laid a solid foundation, and I'm incredibly grateful for their inspiring work. In essence, their accomplishments have ignited the creative spark that led to the development of the Volatility Adjusted ADX (VADX) script.
VADX is not your run-of-the-mill script. It distinguishes itself from the myriad of ADX indicators on TradingView due to its unique volatility-adjustment mechanism. The primary purpose of this script is to augment the ADX's ability to quantify trend strength by introducing a layer of sensitivity to volatility shifts through the Average True Range (ATR). The interaction between these two crucial market measurements is where the novelty lies.
While the standard ADX does an excellent job of diagnosing the trend's vigor, its evaluation can sometimes be skewed when markets oscillate between periods of high and low volatility. Integrating the ATR – a reliable indicator of market volatility – into the ADX calculation mitigates this limitation, resulting in a more robust, volatility-adjusted trend strength measurement.
The specifics of the mathematical adjustment, our secret ingredient, will remain undisclosed for proprietary reasons. Nevertheless, I assure you that it creates a dynamic and balanced interplay between the trend strength and volatility, enabling a more nuanced understanding of the market.
The VADX script is user-friendly and includes three main inputs: ADX Smoothing, DI Length, and ATR Length. The ADX Smoothing parameter refines the ADX calculation, DI Length determines the period for the Directional Movement System calculation, and the ATR Length sets the period for the Average True Range.
Using this indicator is as easy as pie. After adding it to your chart, VADX will manifest itself as a separate panel beneath your price chart. When the VADX is escalating, it indicates that the strength of the trend is intensifying. Conversely, a declining VADX suggests diminishing trend strength. Two horizontal lines at the 25 and 75 levels provide a simple interpretation guide – they denote weak and strong trend phases, respectively.
This robust indicator is adaptable and can be effectively applied across multiple markets - from stocks, forex, and futures to cryptocurrencies. It also delivers valuable insights on any timeframe. However, as with any new indicator, I highly recommend initial testing and optimization to match your unique trading style and objectives.
To wrap up, the VADX indicator sets itself apart with its novel volatility adjustment, a feature not commonly found in existing TradingView scripts. This distinctive capability affords traders a more comprehensive view of the trend's strength by accounting for market volatility, adding an extra layer of depth to traditional ADX interpretation. I sincerely hope that this script enriches your trading arsenal and assists you in navigating the market with enhanced precision. As always, happy trading!
SMI Momentum Bollinger Squeeze Signals - TradeUIMomentum Bollinger Squeeze Signals - TradeUI
The Squeeze Momentum Indicator (SMI) uses the principles of the Squeeze Indicator, which is a volatility indicator, and combines them with a momentum calculation to provide a more comprehensive view of the market.
The original Squeeze Indicator uses the relationship between the Bollinger Bands and Keltner Channels to identify periods of low volatility, known as "Squeezes", and potential breakout points. The SMI takes this one step further by adding a momentum calculation, making it a more dynamic tool for trading.
The momentum calculation is based on the rate of change of the asset's price. When the price increases rapidly, it signifies positive momentum, and when the price decreases rapidly, it signifies negative momentum.
VISION 1.0Introducing the VISION Indicator:
The VISION Indicator is an advanced tool that empowers users to analyze and predict market trends by utilizing three distinct boxes: Box A, Box B, and Box C. Each box represents a specific time range, allowing users to customize their analysis based on their preferred intervals.
Located at the top panel of the indicator, users can easily identify which boxes have a higher likelihood of representing the high or low points of the day. This information assists traders in focusing their attention on the specific boxes that are more likely to contain significant market turning points.
To provide additional insights, the indicator incorporates color-coded panels on the right side. These panels enhance the usability of the indicator by offering valuable information on accuracy and volume characteristics.
The red panel indicates the most accurate predictions for the low of the day. By examining this panel, traders can quickly determine which box historically demonstrates a higher probability of correctly predicting the market's lowest points.
Similarly, the green panel highlights the most accurate predictions for the high of the day. This panel provides traders with a visual representation of which box has historically shown a higher probability of correctly predicting the market's highest points.
Additionally, the blue panel showcases the box with the highest volume percentage. Traders can leverage this information to gauge the intensity of trading activity within different time intervals. By understanding volume patterns, traders can make informed decisions about optimal entry and exit points.
Overall, the VISION Indicator offers a comprehensive visual representation of different time intervals and their respective probabilities for market highs, lows, and trading volume. With this valuable tool, traders can gain insights into potential market trends and make informed trading decisions based on historical patterns and volume analysis.
Damage Indicator by Scipio ProScipio Pro's Damage Indicator detects strong momentum on tops and bottoms. It is intended for swing trading.
The script analyzes both recent and less-recent price action and performs candle stick analysis. It also uses SDs and multiple Bollinger Bands to find dynamic levels for entries.
A Bears Damaged signal emerges whenever there is convincing proof of strength at a bottom. Often, when the market reverses quickly, traders are caught offside and are forced to buy higher. The reverse goes for Bulls Damaged signals, which mean there is convincing proof of bearish strength at a (local?) top.
Whether the move gets legs depends in large part on the structure in which the show of momentum takes place. It is sensible to wonder after each signal whether the market structure (and other relevant context such as the majority of cash having been sidelined) dictates that risk-reward is skewed to the upside or to the downside. If, for example, a Bears Damaged signal emerges on the daily and risk-reward on the weekly is skewed to the upside, go 4x larger (again, just an example). If, on the other hand, the same signal emerges on the daily while the risk-reward is skewed to the downside on the weekly, bet much smaller and tighten your stop-loss. For best results, I suggest you always check one timeframe higher for your long-term risk-reward bias. (No financial advice, of course.)
Under Settings you'll find the so-called Noise Protection , which is switched "on" by default. We recommend you keep this switched on. Noise Protection ensures you do not see Damage signals on timeframes lower than the 4 hour. After all, chasing momentum on low timeframes is a losing game. The amount of noise increases exponentially as you move lower down the timeframes. Again, this indicator is for swing trades. Don't use it for scalping.
It should be useful for all assets, but is of course more useful on some than on others. As with all indicators, signals tend to be more meaningful if the asset in question is at least somewhat liquid, for instance.
As always, use at your own risk. Using indicators is no substitute for using one's brain.
Excess Invites Punishment (EIP) by Scipio ProScipio Pro's EIP is a reversal indicator. It is based on two types of evidence.
1) Proof of Fatigue -- The move that triggers the signal is losing momentum
2) Proof of Excess -- The move that triggers the signal is excessive
If both are the case, we get a signal.
The script uses standard deviations and Bollinger Bands for measuring excess and the ATR for the Breakout Continuation Protection (see below). For fatigue, the EIP detects divergences from indicators like OBV, MACD, RSI and more. It expresses these with a number. For example, if the EIP detects 9 bullish divergences, it prints the number 9 below the corresponding candle.
Hesitant Buy and Hesitant Sell mean there may have been a breakout recently, as measured with the ATR, meaning there is an increased likelihood of continuation. These can provide good buys or sells but more caution is warranted. You can adjust the so-called Breakout Continuation Protection in Settings. Doing so may lead to either more or less "hesitant" signals.
The signals don't repaint. Of course, the divergences get recalculated as the market evolves, as they should. But signals like Buy, Sell, Hesitant Buy, and Hesitant Sell never repaint.
The EIP is useful on many different time-frames and with many different assets, be they in stocks or crypto. The images below show results from BTC, MATIC, and S&P 500 over multiple years, both on small and large time-frames.
As always, use at your own risk. Using indicators is no substitute for using one's brain.
L&S Volatility IndexOverview
L&S Volatility Index is a tool designed to helps traders identify overpriced or underpriced moments in the market and adjust their trading strategies accordingly.
Calculations
This tool calculates how far the price is from the 21-period simple moving average as a ratio of the average historical volatility calculated over the last 21 candles.
How It Works
A L&S Volatility Index with a value greater than 30% may indicate that the asset is overpriced or underpriced relative to its average price.
How To Use
If the L&S Volatility Index > 30, the asset is overpriced or underpriced. This means that there is a good probability of initiating a mean reversion.
If the L&S Volatility Index < 30, the asset is in a fair price region. This means that it is acceptable to buy or sell in that price region.
Where To Use
Mean Reversion Strategy
Breakout Strategy
What Makes it Original
There is already an indicator that use a normalized calculation and a different approach to calculate historical volatility, whereas this script calculation is non-normalized and historical volatility is calculated using Don Fishback's formula. All calculations are used as originally described.
Credits
The L&S Volatility Index indicator was originally written by L&S Educação Financeira.
Historical Volatility calculation is based on the book "Odds: The Key to 90% Winners" written by Don Fishback.
Limit Order + ATR Stop-Loss [TANHEF]This indicator enables interactive placement of limit or stop-limit orders with a trailing ATR stop-loss and optional profit target (with alerts). Refer to the images below for further clarification.
Why use a trailing stop-loss?
A trailing stop-loss serves as an exit strategy when price moves against you, while also allowing you to adjust the exit point further into profit when price moves favorably. The ATR (Average True Range), a reliable measure of volatility, acts as an effective risk management tool, functioning as a trailing stop-loss.
Indicator Explanation
Initial indicator placement: Select Long Limit or Long-Stop Limit order.
Change Entry Type: Switch between Long and Short within settings.
Modify entry price: Drag circle, adjust in settings, or re-add indicator to chart.
Optional Profit Target: Use Risk/Reward ratio or specify price.
Entry anticipation: Estimated ATR stop-loss and profit target as blue circles (fluctuates with volatility changes).
Entry triggered: Actual ATR stop-loss and profit target plotted.
Exit conditions: Stop-loss or profit target hit, exit entry.
Update Frequency: Continuously, Bar Open, or Bar Open on entry then continuously.
ATR Overlap: no entry occurs if the ATR overlaps with price (stop-loss 'hit' already on entry bar)
Table: Displays input settings selected.
Show Only On Ticker: Ability to hide indicator on other tickers.
Long Limit
Long Stop-Limit
Short Limit
Short Stop-Limit
Alerts
1. 'Check' alerts to use within indicator settings (entry, trailing stop hit, profit target hit, and failed entry).
2. Select 'Create Alert'
3. Set the condition to 'Limit Order + ATR Stop-Loss''
4. Select create.
Additional details can be added to the alert message using these words in between Curly (Brace) Brackets:
{{trail}} = ATR trailing stop-loss (price)
{{target}} = Price target (price)
{{type}} = Long or Short stop-loss (word)
{{traildistance}} = Trailing Distance (%)
{{targetdistance}} = Target Distance (%)
{{starttime}} = Start time of position (day:hr:min)
{{maxdrawdown}} = max loss
{{maxprofit}} = max profit
{{update}} = stoploss update frequency
{{entrysource}} = entry as 1st bar source (yes/no)
{{triggerentry}} = Wick/Close Trigger entry input
{{triggerexit}} = Wick/Close Trigger exit input
{{triggertarget}} = Wick/Close Trigger target input
{{atrlength}} = ATR length input
{{atrmultiplier}} = ATR multiplier input
{{atrtype}} = ATR type input
{{ticker}} = Ticker of chart (word)
{{exchange}} = Exchange of chart (word)
{{description}} = Description of ticker (words)
{{close}} = Bar close (price)
{{open}} = Bar open (price)
{{high}} = Bar high (price)
{{low}} = Bar low (price)
{{hl2}} = Bar HL2 (price)
{{volume}} = Bar volume (value)
{{time}} = Current time (day:hr:min)
{{interval}} = Chart timeframe
{{newline}} = New line for text
5EMA BollingerBand Nifty Stock Scanner
What ?
We all heard about (well: over-heard) 5-EMA strategy. Which falls into the broader category of mean reversal type of trading setup.
What is mean reversal?
Price (or any time series, in fact) tries to follow a mean . Whenever price diverges from the mean it tries to meet it back.
It is empirically observed by some traders (I honestly don't know who first time observed it) that in Indian context specially, 5 Exponential Moving Average (5-EMA) works pretty good as that mean.
So whenever price moves away from that 5-EMA, it ultimately comes back and attain total nirvana :) Means: if price moved way higher than the 5EMA without touching it, then price will correct to meet it's 5-EMA and if price moved way lower, it will be uplifted to meet it's 5-EMA. Funny - but it works !
Now there are already enough social media coverage on this 5-EMA strategy/setup. Even TradingView has some excellent work done on these setups. Kudos to all those great souls.
So when we came to know about this, we were thinking what we should do for the community. Because it is well cover topic (specially in Indian context). Also, there are public indicators.
Then we thought why not come up with a scanner which will scan all the Nifty-50 constituent stocks and find out on the fly, real-time which all stocks are matching this 5-EMA setup and causing a Buy/Sell trade recommendation.
Hence here we are with the first version of our first scanner on the 5EMA setup (well it has some more masala than merely a 5-EMA setup).
Why?
Parts of why is already covered up.
Now instead of blindly following 5-EMA setup, we added the Bollinger band as well. Again: it's also not new. There are enough coverage in social media about the 5-EMA+BB strategy/setup. We mercilessly borrowed from all of these.
Suppose you have an indicator.
Now you apply the indicator in your chart. And then you need to (rock) and roll through your watchlist of Nifty-50 stocks (note: TradingView has no default watchlist of Nifty-50 stock by default - you have to create one custom watchlist to list all manually) to find out which all are matching the setup, need to take a note about the trade recomendations (entry, SL, target) and other stuffs like VWAP, Volume, volatility (Bollinger Band Width).
Not any more.
This scanner will track all the Nifty-50 stocks (technically: 40 stocks other than Banking stocks) and provide which one to Buy or Sell (if any), what's the entry, SL, target, where is the VWAP of the day, what's the picture in volume (high, low, rising, falling) and the implied volatility (using Bolling band width). Also it has a naive alerting mechanism as well.
In fact the code is there to monitor the (Future) OI also and all the OI drama (OI vs price and all the 4 stuffs like long build up, long unwinding, short covering, short buildup). But unfortunately, due to some limitations of the TradingView (that one can not monitor more than 40 `ta.security` call) we have to comment out the code. If you wish you can monitor only 20 stocks and enable the OI monitoring also (20 for stocks + 20 for their OI monitoring .. total 40 `ta.security` call).
How?
To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB.
Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB.
Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low.
Present bar's volume is compared with the previous bar's volume to know if it's rising or falling.
VWAP is also determined using `ta.vwap` built-in support of TradingView.
The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle).
Simple, but effective.
Customization
As usual the EMA setup (5 default), the BB setup (20 SMA with 1.5 standard deviation), we provided option wherther to include or exclude BB role in the 5-EMA setup (as we found out there are two schools of thought .. some people use BB some don't. Lets make all happy :))
We also provide options to choose other symbols using Settings if they wish so. We have the default 40 non banking Nifty stocks (why non-banking? - Bank Nifty is in ATH :) .. enough :)). But if user wishes can monitor others too (provided the symbol is there in TradingView).
Although we strongly recommend the timeframe as 30 minutes , you can choose what's fit you most.
The output of the scanner is a table. By default the table is placed in the right-bottom (as we are most comfortable with that). However you can change per your wish. We have the option to choose that.
What is unique in it ?
This is more of an indicator. This is a scanner (of Nifty-50 stocks). So you can apply (our recommendation is in 30m timeframe) it to any chart (does not matter which chart it is) and it will show every 30 mins (which is also configurable) which all stocks (along with trade levels) to Buy and Sell according to the setup.
It will ease your trading activity.
You can concentrate only on the execution, the filtering you can leave it to this one.
Limitations
There is a build in limitation of the TradingView platform is that one can call only upto 40 securities API. Not beyond that. So naturally we are constraint by that. Otherwise we could monitor 190 Nifty F&O stocks itself.
30m is the recommended timeframe. In very lower (say 5m) this script tends to go out of heap (out of memory). Please note that also.
How to trade using this?
Put any chart in 30m (recommended) timeframe.
Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard).
This will provide the Buy (shown in green color) or Sell (shown in red color) recommendations in a table, at every 30m candle closing.
Note the volume and BB width as well.
Wait for at least 2 5-minutes candles to close above/below the recommended level .
Take the trade with the SL and target mentioned.
Mentions
@QuantNomad. The whole implementation concept we mercilessly borrowed from him, even some of his code snippet we took it (after asking him through one of his videos comment section and seeking explicit permission which he readily granted within an hour). Thank You sir @QuantNomad. Indebted to you.
Monika (Rawat) ji: for reviewing, correcting, providing real time examples during live market hours, often compromising her own trading activities, about the effectiveness and usefulness of this setup. Thank You madam ji. Indebted to you.
There are innumerable contents in social media about this. Don't even know whom all we checked. Thanks to all of them.
Happy Trading (in stocks - isn't enough of Indices already?)
Disclaimer
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
mrD-Smart RangesmrD-Smart Ranges aims to offer a complete strategy based on Order Blocks. Ranges signals based on order volume are highlighted, from which smart ranges are suggested to provide potential entries.
This script also includes warnings for each signal marked.
🔶 SETTINGS
Pair Strategy: Select the desired from the list. Change the chart to the one specified in the Strategy.
Current TF Order Blocks: Allows the user to select how many most recent Internal Order Blocks appear in the current time frame on the chart.
Order Block Filter: Allows the user to select how the script mitigates an Order Block.
Hide Overlap: Allows the user to display overlapping Order Blocks.
Show Metrics: Allows the user to display volume % metrics within the Order Blocks.
Show Volume Box: Allows the user to display buy/sell activity within Order Blocks.
High Timeframe: Allows the user to choose a higher or lower timeframe to find the Signals.
Show Failed Buy Sell: Allows the user to display the Signals.
Show HTF Box: Allows the user to display a higher or lower timeframe Order Blocks.
🔶 DETAILS
Order blocks are formed after a slight bearish order block, these can provide an opportunity to change polarity, thus acting as a potential support/resistance level.
A retest/retrace on the order block, combined with order volume between the current timeframe and from the higher timeframe will establish the conditions for smart ranges are suggested to provide potential entries.
🔶 USAGE
mrD-Smart Ranges aims to provide users with a minimalistic screen next to the optimal ranges to keep in mind to find trading setups as shown below.
Here we can see a suggested Sell range and display a label to confirm this range
Signal(s) that can be used for potential entries only during range retest are order blocks.
Users can search for more potential entry ranges based on larger timeframes in the settings: High Timeframe
In the image above, we can see that the price has generated potential orange and bearish entry signals. A confirmation signal with a red label is displayed on the chart when the price retests the Sell range.
Note: While range retests can still work well if they occur later in price action, it's best to look for signals only when price retests the range at the outset rather than retesting it. second price.
The logic of generating signal ranges using different rules is described below:
- Define order blocks in the current timeframe.
- Define the order blocks with the largest volume in the current timeframe.
- Define order blocks in larger timeframes in High Timeframe settings
- Define order blocks with the largest volume in larger timeframes in High Timeframe settings
Entry Range: The combination of the highest volume order blocks in the current timeframe and the highest volume order blocks in the larger timeframe.
🔶General disclaimer:
Trading stocks, futures, forex, options, ETFs, cryptocurrency, or any other financial instrument has huge potential rewards and risks.
You must be aware of the risks and willing to accept them to invest in stocks, futures, forex, options, ETFs, or cryptocurrencies.
Don't trade with money you can't afford to lose.
This is not an offer or an offer to Buy/Sell stocks, futures, Forex, options, ETFs, cryptocurrencies, or any other financial instrument.
Do not represent that any account will or is likely to achieve profit or loss of any kind.
The past performance of any trading system or method is not necessarily indicative of future results.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
MCumulativeDelta* MCumulativeDelta Indicator *
The MCumulativeDelta Indicator shows the Buying / Selling pressure that is happening in the market. The Delta is powered by the *MBox Precision Delta* Algorithm. This indicator serves to show overall Accumulation and Distribution of the BUYERS and the SELLERS. It becomes possible to gauge if the market is overall Bullish or Bearish. This helps determine trade direction and keeping out of other trades that are counter to what the overall Buying / Selling is showing.
* WHAT THE SCRIPT DOES *
The script draws a histogram that can either be positive or negative. When the histogram is positive it means there are more Buyers in the Market. When the histogram is negative it means there are more sellers in the market. The more positive the histogram gets, the more BUYERS are flooding the market. The more negative the histogram gets, the more SELLERS are flooding the market. When the histogram switches over from negative to positive it is a Bullish sign of Buying. When the histogram switches over from positive to negative, it is a Bearish sign of Selling.
* HOW TO USE IT *
As the histogram becomes more negative, this shows that the SELLERS have taken control of the markets. Conversely, as the histogram becomes more positive, this shows that the Buyers have taken control of the markets. The side that is in control is the direction to generally place trades in, and at the same time filter out trades of the opposite direction.
* HOW IT WORKS *
The MCumulativeDelta histogram on the chart represents overall Buying / Selling. This is the DELTA (difference) between the BUYING and the SELLING. Taking the total BUYING and subtracting the total of SELLING, we produce the DELTA (difference) between the Buying / Selling and this is what is drawn by the histogram.
Unlike other Cumulative Delta indicators which determine delta from the Up / Down wick and just multiply by volume (not a true delta), the MCumulativeDelta indicator uses a sophisticated algorithm that analyzes price movement corresponding to volume movement.
The way the DELTA, BUYING, and SELLING is calculated is computed by the *MBox Precision Delta* Algorithm. The algorithm considers the following data points when making it's computation
1. Price moving up on increasing volume
2. Price moving up on decreasing volume
3. Price moving horizontally on increasing volume
4. Price moving horizontally on decreasing volume
5. Price moving down on increasing volume
6. Price moving down on decreasing volume
Using these data points allows MCumulativeDelta to effectively compute and define the following scenarios
1. Accumulation / Distribution
2. Buying / Selling Exhaustion
3. Buying / Selling EFFORT / NO RESULT
Once the scenario is determined, it will greatly aid in trade decision making. These scenarios are explained in the examples below
* EXAMPLE AND USE CASES *
- Accumulation Example -
When you see a large amount of BUYING (large positive histogram) and price entering an up trend, this is indicative of Accumulation and you would be looking for PULLBACKS to get into the up trend move.
- Distribution Example -
When you see a large amount of SELLING (large negative histogram) and price entering a down trend, this is indicative of Distribution and you would be looking for pullbacks to get into the down trend move.
- Buying EXHAUSTION Divergence -
As price makes higher highs, but the MCumulativeDelta histogram drops (becomes less positive) on the higher highs, it means BUYERS are exhausted. Potentially a reversal or change in behavior in the markets.
- Selling EXHAUSTION Divergence -
As price makes lower lows, but the MCumulativeDelta histogram contracts (becomes less negative) on the lower lows, it means SELLERS are exhausted. Potentially a reversal or change in behavior in the markets.
- BUYING EFFORT / NO RESULT -
As the MCumulativeDelta histogram increases positively, but price fails to make higher highs, it is a sign of EFFORT / NO RESULT on behalf of the Buyers. In this case Buyers are pushing hard to move price up, but are unable to, due to being OVERBOUGHT. If this is accompanied by visible SELLING, it would be a good short entry.
- SELLING EFFORT / NO RESULT -
As the MCumulativeDelta histogram increases negatively, but price fails to make lower lows, it is a sign of EFFORT / NO RESULT on behalf of the Sellers. In this case Sellers are pushing hard to move price down, but are unable to, due to being OVERSOLD. If this is accompanied by visible BUYING, it would be a good long entry.
* SETTING ALERTS *
- FOR CROSSING FROM BUYING TO SELLING OR SELLING TO BUYING -
To be alerted when the histogram crosses over from Buying to Selling (Positive to Negative) or Selling to Buying (Negative to Positive)
1. Right Click Chart -> Add Alert...
2. Select Condition to be "MCumulativeDelta"
3. Select "Crossing" with Value = 0
4. Options set "Once Per Bar Close"
5. Customize Any other Alert Options you want
* AUTHOR *
This script is published by MBoxWave LLC
Intraday Mean Reversion Money Performance indicatorThe diagram shows Money Performance when buying stocks for 10 000 at every buy signal from the Intraday Mean Reversion indicator.
The indicator is best used in combination with Intraday Mean Reversion Main Indicator
The rules for trading are: Buy on Open price if the Intraday Mean Reversion Main indicator gives a buy signal. Sell on the daily close price.
According to my knowledge it is not possible to create a PineScript strategy based on these rules, because the indicator is used on Day to Day graph. Therefore this indicator can be used to analyze Money performance of this strategy.
The lines show the performance of the Intraday Mean Reversion Strategy, based on the different levels in the strategy (from 0.5 Standard deviation to 1.1 standard deviation)
Using this indicator it is possible to find stocks that often reverse towards mean after open.
Use this strategy on stocks with high positive performance. Do not use on stocks with negative performance.
Session KillZones [7Bridges]Session Killzones by 7Bridges indicator display the killzones of asian, LND and NY sessions. There is also a custom session of your choice.
The times of each killzone are GMT time and you can adjust it in the settings.
You have also the beginning of the day, GMT and EST timezones.
By default the killzones are set like that on the GMT/UTC timezone :
-> Asia : 00:00 - 06:00
-> Pre London : 06:00 - 07:00
-> London : 07:00 - 10:00
-> New York : 12:00 - 15:00
-> Custom session : choose your own time
What makes the indicator very different is that the session is not overlapping the price but you have bars below and above the price.
Settings:
-> you can chose to display the Killzones (Asia, pre LND, LND and NY)
-> you can manages the time of the sessions
-> you can chose to display the start of the day (GMT/UTC and EST )
The indicator is displayed by default only for all the timeframes below 60min.
Intraday Mean Reversion MainThe Intraday Mean Reversion Indicator works well on certain stocks. It should be used for day trading stocks but need to be applied on the Day to Day timeframe.
The logic behind the indicator is that stocks that opens substantially lower than yesterdays close, very often bounces back during the day and closes higher than the open price, thus the name Intraday Mean reversal. The stock so to speak, reverses to the mean.
The indicator has 7 levels to choose from:
0.5 * standard deviation
0.6 * standard deviation
0.7 * standard deviation
0.8 * standard deviation
0.9 * standard deviation
1.0 * standard deviation
1.1 * standard deviation
The script can easily be modified to test other levels as well, but according to my experience these levels work the best.
The info box shows the performance of one of these levels, chosen by the user.
Every Yellow bar in the graph shows a buy signal. That is: The stocks open is substantially lower (0.5 - 1.1 standard deviations) than yesterdays close. This means we have a buy signal.
The Multiplier shows which multiplier is chosen, the sum shows the profit following the strategy if ONE stock is bought on every buy signal. The Ratio shows the ratio between winning and losing trades if we followed the strategy historically.
We want to find stocks that have a high ratio and a positive sum. That is More Ups than downs. A ratio over 0.5 is good, but of course we want a margin of safety so, 0.75 is a better choice but harder to find.
If we find a stock that meets our criteria then the strategy will be to buy as early as possible on the open, and sell as close as possible on the close!
GKD-M Accuracy Alchemist [Loxx]Giga Kaleidoscope GKD-M Accuracy Alchemist is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-M Accuracy Alchemist
What is the Accuracy Alchemist?
The Accuracy Alchemist is designed to process up to 10 GKD-C indicators and create a compound signal that can be utilized in a GKD-BT backtest. It achieves this by applying an individual Solo Confirmation Simple backtest to each GKD-C indicator provided. The compound signal is derived from the cumulative accuracy rate of each candle within a specified date range.
To illustrate this process, consider the following scenario:
The Fisher Transform indicator has a 65% win rate for long positions on the current ticker.
The Vortex indicator has a 45% success rate on the current candle.
Suppose a long signal is generated by the Vortex indicator. However, this signal is disregarded because its accuracy is lower than that of the Fisher Transform. Now, imagine that the subsequent candle produces a long signal from the Fisher Transform indicator. This signal will be exported to the backtest. The GKD-C indicator that exhibits the highest accuracy for the current candle is chosen to generate the signal. The dominant indicator, determined by its accuracy, will always be used to generate signals. However, it is important to note that the current dominant indicator might not retain its dominance in the future if its accuracy rate falls below that of other indicators connected within the Accuracy Alchemist indicator.
The Accuracy Alchemist provides a comprehensive table that displays the dominant indicator based on accuracy, highlighted in green for the highest long accuracy rate and in red for the highest short accuracy rate. Additionally, the table presents the cumulative long and short accuracy rates for all indicators.
The functionality of the Accuracy Alchemist extends to several GKD-BT backtests, allowing for seamless integration. These backtests include:
-Solo Confirmation Simple
-Solo Confirmation Complex
-Solo Confirmation Super Complex
-Full GKD (as a Confirmation 1 indicator only)
-Confirmation Stack (as a Confirmation 1 indicator only)
By incorporating the Accuracy Alchemist, you gain the ability to evaluate and compare GKD-C Confirmation indicators within your full GKD trading system. It serves as an ideal tool to assess the performance of different confirmation indicators and aids in the selection process for determining which indicators to incorporate into your trading strategy.
Take Profit and Stoploss
The GKD system utilizes volatility-based take profits and stop losses, where each take profit and stop loss is calculated as a multiple of volatility. Users have the flexibility to adjust the multiplier values in the settings to suit their preferences. Accuracy Alchemist tests the accuracy of GKD-C Confirmation indicators and therefore has only 1 take profit and 1 stoploss. You can adjust the multipliers of both in the settings
Setting up Accuracy Alchemist
To use this indicator, you must import GKD-C Confirmation indicators and then activate them in the Accuracy Alchemist settings. Import the value "Input into NEW GKD-BT Backtest" from a GKD-C indicator and then activate it by checking the box next to the import. See below:
Volatility Types Included
17 types of volatility are included in this indicator
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
Static Percent
Static Percent allows the user to insert their own constant percent that will then be used to create take profits and stoploss
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Composite RSI
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Fisher Transform, Universal Oscillator, Aroon, Vortex .. combined
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
PhenomIt is a simple and effective tool for trading on moving averages.
The main advantage is that an ATR-based risk management system is included here. The system is based on the work of FullTimeTradingRu and the FBMA indicator
How to use the system:
1. I recommend using a daily timeframe.
2. Look for a rebound from the moving average, the most effective 20 Ema. For convenience, the colors of the bars are painted green in an uptrend.
3. Enter the transaction using hints. The recommended number of shares to buy is indicated in the table, taking into account your deposit and the risk per transaction from the deposit (by default 1%). Stop 1.5 ATR. Everything is the same for opening short positions.
4. I recommend entering the second trade only if the previous one passed 0.5 ATR, thereby confirming the trend and the fact that you correctly guessed the movement.
There are ATR settings in the script
Last bar show — How many bars to show
ATR lines ATR Step — For a more convenient view, ATR lines can be turned into a ladder.
