888 BOT #backtest█ 888 BOT #backtest (open source)
This is an Expert Advisor 'EA' or Automated trading script for ‘longs’ and ‘shorts’, which uses only a Take Profit or, in the worst case, a Stop Loss to close the trade.
It's a much improved version of the previous ‘Repanocha’. It doesn`t use 'Trailing Stop' or 'security()' functions (although using a security function doesn`t mean that the script repaints) and all signals are confirmed, therefore the script doesn`t repaint in alert mode and is accurate in backtest mode.
Apart from the previous indicators, some more and other functions have been added for Stop-Loss, re-entry and leverage.
It uses 8 indicators, (many of you already know what they are, but in case there is someone new), these are the following:
1. Jurik Moving Average
It's a moving average created by Mark Jurik for professionals which eliminates the 'lag' or delay of the signal. It's better than other moving averages like EMA , DEMA , AMA or T3.
There are two ways to decrease noise using JMA . Increasing the 'LENGTH' parameter will cause JMA to move more slowly and therefore reduce noise at the expense of adding 'lag'
The 'JMA LENGTH', 'PHASE' and 'POWER' parameters offer a way to select the optimal balance between 'lag' and over boost.
Green: Bullish , Red: Bearish .
2. Range filter
Created by Donovan Wall, its function is to filter or eliminate noise and to better determine the price trend in the short term.
First, a uniform average price range 'SAMPLING PERIOD' is calculated for the filter base and multiplied by a specific quantity 'RANGE MULTIPLIER'.
The filter is then calculated by adjusting price movements that do not exceed the specified range.
Finally, the target ranges are plotted to show the prices that will trigger the filter movement.
Green: Bullish , Red: Bearish .
3. Average Directional Index ( ADX Classic) and ( ADX Masanakamura)
It's an indicator designed by Welles Wilder to measure the strength and direction of the market trend. The price movement is strong when the ADX has a positive slope and is above a certain minimum level 'ADX THRESHOLD' and for a given period 'ADX LENGTH'.
The green color of the bars indicates that the trend is bullish and that the ADX is above the level established by the threshold.
The red color of the bars indicates that the trend is down and that the ADX is above the threshold level.
The orange color of the bars indicates that the price is not strong and will surely lateralize.
You can choose between the classic option and the one created by a certain 'Masanakamura'. The main difference between the two is that in the first it uses RMA () and in the second SMA () in its calculation.
4. Parabolic SAR
This indicator, also created by Welles Wilder, places points that help define a trend. The Parabolic SAR can follow the price above or below, the peculiarity that it offers is that when the price touches the indicator, it jumps to the other side of the price (if the Parabolic SAR was below the price it jumps up and vice versa) to a distance predetermined by the indicator. At this time the indicator continues to follow the price, reducing the distance with each candle until it is finally touched again by the price and the process starts again. This procedure explains the name of the indicator: the Parabolic SAR follows the price generating a characteristic parabolic shape, when the price touches it, stops and turns ( SAR is the acronym for 'stop and reverse'), giving rise to a new cycle. When the points are below the price, the trend is up, while the points above the price indicate a downward trend.
5. RSI with Volume
This indicator was created by LazyBear from the popular RSI .
The RSI is an oscillator-type indicator used in technical analysis and also created by Welles Wilder that shows the strength of the price by comparing individual movements up or down in successive closing prices.
LazyBear added a volume parameter that makes it more accurate to the market movement.
A good way to use RSI is by considering the 50 'RSI CENTER LINE' centerline. When the oscillator is above, the trend is bullish and when it is below, the trend is bearish .
6. Moving Average Convergence Divergence ( MACD ) and ( MAC-Z )
It was created by Gerald Appel. Subsequently, the histogram was added to anticipate the crossing of MA. Broadly speaking, we can say that the MACD is an oscillator consisting of two moving averages that rotate around the zero line. The MACD line is the difference between a short moving average 'MACD FAST MA LENGTH' and a long moving average 'MACD SLOW MA LENGTH'. It's an indicator that allows us to have a reference on the trend of the asset on which it is operating, thus generating market entry and exit signals.
We can talk about a bull market when the MACD histogram is above the zero line, along with the signal line, while we are talking about a bear market when the MACD histogram is below the zero line.
There is the option of using the MAC-Z indicator created by LazyBear, which according to its author is more effective, by using the parameter VWAP ( volume weighted average price ) 'Z-VWAP LENGTH' together with a standard deviation 'STDEV LENGTH' in its calculation.
7. Volume Condition
Volume indicates the number of participants in this war between bulls and bears, the more volume the more likely the price will move in favor of the trend. A low trading volume indicates a lower number of participants and interest in the instrument in question. Low volumes may reveal weakness behind a price movement.
With this condition, those signals whose volume is less than the volume SMA for a period 'SMA VOLUME LENGTH' multiplied by a factor 'VOLUME FACTOR' are filtered. In addition, it determines the leverage used, the more volume , the more participants, the more probability that the price will move in our favor, that is, we can use more leverage. The leverage in this script is determined by how many times the volume is above the SMA line.
The maximum leverage is 8.
8. Bollinger Bands
This indicator was created by John Bollinger and consists of three bands that are drawn superimposed on the price evolution graph.
The central band is a moving average, normally a simple moving average calculated with 20 periods is used. ('BB LENGTH' Number of periods of the moving average)
The upper band is calculated by adding the value of the simple moving average X times the standard deviation of the moving average. ('BB MULTIPLIER' Number of times the standard deviation of the moving average)
The lower band is calculated by subtracting the simple moving average X times the standard deviation of the moving average.
the band between the upper and lower bands contains, statistically, almost 90% of the possible price variations, which means that any movement of the price outside the bands has special relevance.
In practical terms, Bollinger bands behave as if they were an elastic band so that, if the price touches them, it has a high probability of bouncing.
Sometimes, after the entry order is filled, the price is returned to the opposite side. If price touch the Bollinger band in the same previous conditions, another order is filled in the same direction of the position to improve the average entry price, (% MINIMUM BETTER PRICE ': Minimum price for the re-entry to be executed and that is better than the price of the previous position in a given %) in this way we give the trade a chance that the Take Profit is executed before. The downside is that the position is doubled in size. 'ACTIVATE DIVIDE TP': Divide the size of the TP in half. More probability of the trade closing but less profit.
█ STOP LOSS and RISK MANAGEMENT.
A good risk management is what can make your equity go up or be liquidated.
The % risk is the percentage of our capital that we are willing to lose by operation. This is recommended to be between 1-5%.
% Risk: (% Stop Loss x % Equity per trade x Leverage) / 100
First the strategy is calculated with Stop Loss, then the risk per operation is determined and from there, the amount per operation is calculated and not vice versa.
In this script you can use a normal Stop Loss or one according to the ATR. Also activate the option to trigger it earlier if the risk percentage is reached. '% RISK ALLOWED'
'STOP LOSS CONFIRMED': The Stop Loss is only activated if the closing of the previous bar is in the loss limit condition. It's useful to prevent the SL from triggering when they do a ‘pump’ to sweep Stops and then return the price to the previous state.
█ BACKTEST
The objective of the Backtest is to evaluate the effectiveness of our strategy. A good Backtest is determined by some parameters such as:
- RECOVERY FACTOR: It consists of dividing the 'net profit' by the 'drawdown’. An excellent trading system has a recovery factor of 10 or more; that is, it generates 10 times more net profit than drawdown.
- PROFIT FACTOR: The ‘Profit Factor’ is another popular measure of system performance. It's as simple as dividing what win trades earn by what loser trades lose. If the strategy is profitable then by definition the 'Profit Factor' is going to be greater than 1. Strategies that are not profitable produce profit factors less than one. A good system has a profit factor of 2 or more. The good thing about the ‘Profit Factor’ is that it tells us what we are going to earn for each dollar we lose. A profit factor of 2.5 tells us that for every dollar we lose operating we will earn 2.5.
- SHARPE: (Return system - Return without risk) / Deviation of returns.
When the variations of gains and losses are very high, the deviation is very high and that leads to a very poor ‘Sharpe’ ratio. If the operations are very close to the average (little deviation) the result is a fairly high 'Sharpe' ratio. If a strategy has a 'Sharpe' ratio greater than 1 it is a good strategy. If it has a 'Sharpe' ratio greater than 2, it is excellent. If it has a ‘Sharpe’ ratio less than 1 then we don't know if it is good or bad, we have to look at other parameters.
- MATHEMATICAL EXPECTATION: (% winning trades X average profit) + (% losing trades X average loss).
To earn money with a Trading system, it is not necessary to win all the operations, what is really important is the final result of the operation. A Trading system has to have positive mathematical expectation as is the case with this script: ME = (0.87 x 30.74$) - (0.13 x 56.16$) = (26.74 - 7.30) = 19.44$ > 0
The game of roulette, for example, has negative mathematical expectation for the player, it can have positive winning streaks, but in the long term, if you continue playing you will end up losing, and casinos know this very well.
PARAMETERS
'BACKTEST DAYS': Number of days back of historical data for the calculation of the Backtest.
'ENTRY TYPE': For '% EQUITY' if you have $ 10,000 of capital and select 7.5%, for example, your entry would be $ 750 without leverage. If you select CONTRACTS for the 'BTCUSDT' pair, for example, it would be the amount in 'Bitcoins' and if you select 'CASH' it would be the amount in $ dollars.
'QUANTITY (LEVERAGE 1X)': The amount for an entry with X1 leverage according to the previous section.
'MAXIMUM LEVERAGE': It's the maximum allowed multiplier of the quantity entered in the previous section according to the volume condition.
The settings are for Bitcoin at Binance Futures (BTC: USDTPERP) in 15 minutes.
For other pairs and other timeframes, the settings have to be adjusted again. And within a month, the settings will be different because we all know the market and the trend are changing.
Cerca negli script per "profit"
Fibonacci-Trading-Indikator_3Daily (weekly, monthly) profits with the Fibonacci trading indicator_3
Quotes move in Fibonacci ratios in liquid markets. With this indicator you receive information for daily trades or for position trades based on a week or on a monthly basis, in which area you should ideally enter the market and where the minimum achievable price target is. This price target is 61.8% of yesterday's trading range, or the trading range of the previous week, or the trading range of the previous month, depending on the time frame for which the indicator should calculate the minimum achievable high / low. This is also where you realize your profit.
For this calculation, the following entries must be made in the properties window of the indicator:
• Preselection uptrend / downtrend.
• Time frame (day, week, ...) of the price bar for the possible high / low to be determined.
• Trading range of the previous day, or the previous week, or the previous month.
• Current lowest low of the selected time frame when trading has started and prices are rising.
• Current highest high of the selected time frame when trading has started and prices are falling.
Important areas for trading are:
• The entry range 0% - 23.6% for long or short.
• The target price level 61.8%.
Choose a suitable time frame to detect the direction of movement while the quotes are still moving in the entry area. The camelback indicator can be of great help. Also test the resolution setting of the camelback indicator. With a resolution of 1 hour in the 6 or 12 minute chart, you get a perspective for the broader direction. Movement patterns of corrections or consolidations, if they last more than a day or a week, also give clues to the coming direction of movement for the trade. So look back to see what happened yesterday, a week ago, or a month ago. Pay attention to the market anatomy, find out how the market works, count the price bars in consolidations and trends.
After entering the values the indicator will show the Fibonacci expansion price levels for the possible high or low for the selected time frame. Buy / sell within the entry range between 0% and 23.6% as the market moves towards the last long / or short entry point. This is the course range up to the 23.6% course level. The 61.8% price level is the minimum expected price target. We assume that the current bar will reach at least 61.8% of the trading range of the previous day, week or month. Depending on the set time frame. You should therefore realize the profits you have made with 50% of the position when the prices have reached the 61.8% level. With a suitable trailing stop you can be stopped with the rest of the position, but do not risk more than 50% of the profits.
With the quarter or year preselection and the corresponding entries, the minimum expected quarterly high / quarterly low or annual high / annual low can be determined.
The Fibonacci price levels can be shown and hidden. In the chart click on the gear wheel for “Chart Settings”. In the “Scaling” menu, the price levels can be displayed with the preselection “Label for indicator names” and “Label for last indicator value”. Slide the chart to the right to find possible support and resistance at the price levels that could provide confirmation of the target.
In the event of input errors or missing entries for a time frame, the indicator is hidden.
Pay attention to your trade management to avoid losses.
The new Fibonacci Trading Indicator_3 has the following additions and changes:
Area code for the quarter time frame has been added.
The entry area received a 23.6% and a 50% subdivision. Two envelope lines above the 23.6% entry level in the case of an upward trend and below the 23.6% entry level in the case of a downtrend, with a width of 23.6% and 14.6% of the entry level, are intended to indicate that the closing price is higher the quotations have broken out of the entry-level area.
A volatility stop for upward and downward trends can be activated.
A factor is added to the fluctuation range of each price bar for the stop. Then a moving average is calculated with an adjustable period. The period setting should be set between 5 and 10. The result can be smoothed adjustable.
Presetting:
Periods = 10
Factor = 1.4
Smoothing = 7
With the assumption that the market entry in an upward trend occurs when the prices break out above a bar high, the result of the stop calculation is subtracted from the bar high. In the case of a downward trend, the result of the stop calculation is added to the price bar low.
When entering the market, set the factor to 2.4. If inside bars follow a trend movement, the stop should be brought closer. Try the factor setting 0.4 or less. The smallest adjustable factor is 0.1.
For the entry into an established trend, as described in an idea contribution by me, there are two switchable moving averages. The application for the (MA_H) takes place on high and for the (MA_L) adjustable on high, low, shot, h + 1/2 etc. Period and offset (shift) are adjustable. With this idea, the entry into the market occurs between a 618% correction (the Fibonacci entry point) and the DEP (average entry point). The DEP in this case is the MA_H with period = 4 and an offset = 1 in the case of a downward trend, or the MA_L with the same setting and application to lows in an upward trend.
Also test the MA_L in trends with the settings (period, offset) 3.3 or 5, 3 or 7.5 and applying it to closing prices for a close encompassing of the highs / lows.
Tägliche (wöchentliche, monatliche) Gewinne mit dem Fibonacci-Trading Indikator_3
Kursnotierungen bewegen sich in liquiden Märkten in Fibonacci-Verhältnisse. Mit diesem Indikator erhalten Sie für Tagesgeschäfte, oder für Positionstrades auf Basis einer Woche, oder auf Basis eines Monats Informationen, in welchem Bereich Sie idealerweise in den Markt einsteigen sollten und wo das mindeste erreichbare Kursziel liegt. Dieses Kursziel liegt bei 61,8% der gestrigen Handelspanne, oder der Handelspanne der Vorwoche, oder der Handelspanne des Vormonats, also abhängig davon für welchen Zeitrahmen der Indikator das mindeste erreichbare Hoch/Tief berechnen soll. Dort realisieren Sie auch Ihren Gewinn.
Für diese Berechnung sind folgende Eingaben im Eigenschaftenfenster des Indikators einzustellen:
• Vorwahl Aufwärtstrend/ Abwärtstrend.
• Zeitrahmen (Tag, Woche, …) des Kursbalkens für das zu ermittelnde mögliche Hoch/ Tief.
• Handelspanne des vorherigen Tages, oder der vorherigen Woche, oder des vorherigen Monats.
• Aktuell tiefstes Tief des vorgewählten Zeitrahmens, wenn der Handel begonnen hat und die Notierungen steigen.
• Aktuell höchstes Hoch des vorgewählten Zeitrahmens, wenn der Handel begonnen hat und die Notierungen fallen.
Wichtige Bereiche für das Trading sind:
• Der Einstiegsbereich 0% - 23,6% für long oder short.
• Der Kursziellevel 61,8%.
Wählen Sie für die Erkennung der Bewegungsrichtung einen geeigneten Zeitrahmen, während sich die Notierungen noch im Einstiegsbereich bewegen. Der Camelback-Indikator kann eine gute Hilfe sein. Testen Sie auch die Auflösung-Einstellung des Camelback-Indikators. Mit der Auflösung 1 Stunde Im 6- oder 12 Minuten-Chart erhalten Sie einen Blickwinkel für die große Richtung. Auch Bewegungsmuster von Korrekturen oder Konsolidierungen, wenn sie mehr als einen Tag oder eine Woche andauern geben Hinweise auf die kommende Bewegungsrichtung für den Trade. Schauen Sie also zurück um zu prüfen, was sich gestern, vor einer Woche oder vor einem Monat abgespielt hat. Achten sie auf die Marktanatomie, finden Sie heraus wie der Markt funktioniert, zählen Sie Kursstäbe in Konsolidierungen und Trends.
Nach Eingabe der Werte zeigt der Indikator die Fibonacci-Ausweitungskurslevels für das mögliche Hoch oder Tief für den ausgewählten Zeitrahmen. Kaufen/ verkaufen Sie innerhalb des Einstiegsbereichs zwischen 0% und 23,6%, während sich der Markt in Richtung des letzten long-/ oder short-Einstiegspunktes bewegt. Das ist der Kursbereich bis zum 23,6%- Kurslevel. Der 61,8%-Kurslevel ist das mindeste erwartbare Kursziel. Wir gehen davon aus, dass der aktuelle Kursbalken mindestens 61,8% der Handelsspanne des vorherigen Tages, der vorherigen Woche oder des vorherigen Monats erreichen wird. Abhängig vom eingestellten Zeitrahmen. Realisieren Sie deshalb die angelaufenen Gewinne mit 50% der Position, wenn die Notierungen den 61,8% - Level erreicht haben. Mit einem geeigneten Trailing-Stopp lassen Sie sich mit der restlichen Position ausstoppen, riskieren Sie dafür aber nicht mehr als 50 % der angelaufenen Gewinne.
Mit der Vorwahl Quartal oder Jahr und den entsprechenden Eingaben kann auch das mindeste erwartbare Quartalshoch/ Quartalstief bzw. Jahreshoch/ Jahrestief ermittelt werden.
Die Fibonacci-Kurslevels lassen sich ein- und ausblenden. Klicken Sie im Chart auf das Zahnrad für „Chart Einstellungen“. Im Menü „Skalierungen“ kann mit der Vorwahl „Label für Indikatornahmen“ und „Label für letzten Indikatorwert“ die Kurslevels angezeigt werden. Schieben Sie den Chart nach rechts um mögliche Unterstützungen und Widerstände an den Kurslevels zu finden, die Bestätigung für das Ziel geben könnten.
Bei Eingabefehlern oder fehlenden Eingaben zu einem Zeitrahmen wird der Indikator ausgeblendet.
Achten Sie zur Vermeidung von Verlusten auf ihr Handelsmanagement.
Der neue Fibonacci-Trading-Indikator_3 besitz folgende Zusätze und Änderungen:
Vorwahl für den Zeitrahmen Quartal wurde hinzugefügt.
Der Einstiegsbereich erhielt eine 23,6% und eine 50% Unterteilung. Zwei Umschlagslinien über dem 23,6%-Einstiegslevel bei einem Aufwärtstrend, bzw. unter dem 23,6%-Einstiegslevel bei einem Abwärtstrend, mit der Breite 23,6% und 14,6% vom Einstiegsbereich, sollen bei höherem Schlusskurs signalisieren, dass die Notierungen aus dem Einstiegsbereich ausgebrochen sind.
Ein Volatilitätsstopp jeweils für Aufwärts- und Abwärtstrend kann zugeschaltet werden.
Für den Stopp wird die Schwankungsbreite jedes Kursbalkens wird mit einem Faktor beaufschlagt. Danach erfolgt die Berechnung eines gleitenden Durchschnitts mit einstellbarer Periode. Die Periodeneinstellung sollte zwischen 5 und 10 eingestellt werden. Das Ergebnis kann einstellbar geglättet werden.
Voreinstellung:
Perioden = 10
Faktor = 1,4
Glättung = 7
Mit der Annahme, dass der Markteinstieg in einem Aufwärtstrend bei Ausbruch der Notierungen über ein Kursbalkenhoch erfolgt, wird das Ergebnis der Stoppberechnung vom Kursbalkenhoch subtrahiert. Bei einem Abwärtstrend wird das Ergebnis der Stoppberechnung zum Kursbalkentief addiert.
Stellen Sie bei Markteintritt den Faktor auf 2,4. Folgen nach einer Trendbewegung Innenstäbe sollte der Stopp näher herangeführt werden. Probieren Sie die Faktoreinstellung 0,4 oder kleiner. Der kleinste einstellbare Faktor ist 0,1.
Für den Einstieg in einen etablierten Trend, wie in einem Ideenbeitrag von mir beschrieben, gibt es zwei zuschaltbare gleitende Durchschnitte. Die Anwendung für den (MA_H) erfolgt auf Hochs und für den (MA_L) einstellbar auf Hoch, Tief, Schuss, h+l/2 usw.. Periode und Offset (Verschiebung) sind einstellbar. Bei dieser Idee erfolgt der Einstieg in den Markt zwischen einer 618%-Korrektur (dem Fibonacci-Einstiegspunkt) und dem DEP (Durchschnittlicher Einstiegspunkt). Der DEP ist in diesem Fall der MA_H mit Periode = 4 und einem Offset = 1, bei einem Abwärtstrend, oder der MA_L mit identischer Einstellung und Anwendung auf Tiefs in einem Aufwärtstrend.
Testen Sie den MA_L auch in Trends mit den Einstellungen (Periode, Offset) 3,3 oder 5, 3 oder 7,5 und Anwendung auf Schlusskurse für eine enge Umfassung der Hochs/ Tiefs.
Grid System With Fake MartingaleThe proposed strategy is based on a grid system with a money management that tries to replicate the effect of a martingale without having to double your position size after each loss, hence the name "fake martingale". Note that a balance using this strategy is still subject to exponential decay, the risk is not minimized, as such, it would be dangerous to use this strategy.
For more information on the martingale and grid systems see:
Strategy Settings
Point determines the "grid" size and should be adjusted accordingly to the scale of the security you are applying the strategy to. Higher value would require larger price movements in order to trigger a trade, generating fewer trades as a result.
The order size determines the number of contracts/shares to purchase.
The martingale multiplier determines the factor by which the position size is multiplied after a loss, using values higher to 2 will "squarify" your balance, while a value of 1 would use a constant position sizing.
Finally, the anti-martingale parameter determines whether the strategy uses a reverse martingale or not, if set to true then the position size is multiplied after each win.
How It Works
Let's illustrate how we replicate a martingale without doubling our exposure with a simple casino example. Imagine you are playing roulette, and that you are betting on colors (black/red), your payout is 1 to 1, in the case you win, you will have your initial stake back plus a profit equal to your initial stake.
If your strategy is to recover any previous losses, you can double your stake each time you lose, once you win you will get back the previous losses plus a profit equal to your original stake, this is the martingale system. So how can we win back previous losses without having to double our stake? We could do that by doubling the payout ratio after a loss, so after a loss, we must use a payout ratio of 2:1, if we lose once again we must use a payout of 4:1...etc, our payout ratio would be subject to exponential growth instead of our stake.
Of course, the payout ratio is fixed with casino games, but in trading, we can manipulate the position of our take profit in order to replicate such effect, this is what this strategy is doing. So after a loss, we place our take profit such that a win recover our losses back plus generate a profit.
Advantages
The advantage of this approach is that unlike the martingale we don't double our position size, which instead can remain constant, this is a huge advantage as a martingale will require a significant capital in order to tank a series of losses.
Disadvantages
The main disadvantage of this method is that the price might never reach our take profit after a long losing streak, our balance would remain in the red and we couldn't do anything about it except reset the strategy.
Frictional costs are still a disadvantage, as such, we would need to place our take profits in order to account for them, while this is still better than purchasing additional shares, it minimizes the chances of the price reaching the take profit.
Conclusions
An alternative money management system replicating the effect of a martingale as been presented, we can see that such a system is far from being perfect, and it would be foolish to use it, however, it stills offer a convenient alternative to less aggressive progressive position sizing systems.
I have been receiving some messages from users criticizing me for exposing the martingale money management system, and I understand why but I can't agree, talking about it allow me to warn users against it, the grid-martingale methodology is will create more harm than anything else, the reward is only one side of the story and should always be compared against the risk, so always take a look at all the statics in a backtest.
Thanks for reading!
Shout-Out
This post was made possible thanks to my patrons:
@Happymono, @AmariMars, @kkhaial, @Nugehe, @LucF, @Nosmok, @iflostio, @DankBeans, @ecletv, @Neverstorm, @alex.crown.jr, @uk503, @xkingshotss, @vsov, @jbelka, @yatrader2, @hughza, @ganh
Trading Psychology - Fear & Greed Index by DGTPsychology of a Market Cycle - Where are we in the cycle?
Before proceeding with the question "where", let's first have a quick look at "What is market psychology?"
Market psychology is the idea that the movements of a market reflect the emotional state of its participants. It is one of the main topics of behavioral economics - an interdisciplinary field that investigates the various factors that precede economic decisions. Many believe that emotions are the main driving force behind the shifts of financial markets and that the overall fluctuating investor sentiment is what creates the so-called psychological market cycles - which is also dynamic.
Stages of Investor Emotions:
* Optimism – A positive outlook encourages us about the future, leading us to buy stocks.
* Excitement – Having seen some of our initial ideas work, we begin considering what our market success could allow us to accomplish.
* Thrill – At this point we investors cannot believe our success and begin to comment on how smart we are.
* Euphoria – This marks the point of maximum financial risk. Having seen every decision result in quick, easy profits, we begin to ignore risk and expect every trade to become profitable.
* Anxiety – For the first time the market moves against us. Having never stared at unrealized losses, we tell ourselves we are long-term investors and that all our ideas will eventually work.
* Denial – When markets have not rebounded, yet we do not know how to respond, we begin denying either that we made poor choices or that things will not improve shortly.
* Fear – The market realities become confusing. We believe the stocks we own will never move in our favor.
* Desperation – Not knowing how to act, we grasp at any idea that will allow us to get back to breakeven.
* Panic – Having exhausted all ideas, we are at a loss for what to do next.
* Capitulation – Deciding our portfolio will never increase again, we sell all our stocks to avoid any future losses.
* Despondency – After exiting the markets we do not want to buy stocks ever again. This often marks the moment of greatest financial opportunity.
* Depression – Not knowing how we could be so foolish, we are left trying to understand our actions.
* Hope – Eventually we return to the realization that markets move in cycles, and we begin looking for our next opportunity.
* Relief – Having bought a stock that turned profitable, we renew our faith that there is a future in investing.
It's hard to predict with certainty where we exactly are in the market cycle, we can only make an educated guess as to the rough stage based on data available. And here comes the study "Trading Psychology - Fear & Greed Index"
Factors taken into account in this study include:
1-Price Momentum : Price Divergence/Convergence versus its Slow Moving Average
2-Strenght : Rate of Return (RoR) also called Return on Investment (ROI) is a performance measure used to evaluate the efficiency of an investment, net gain or loss of an investment over a specified time period, the rate of change in price movement over a period of time to help investors determine the strength
3-Money Flow : Chaikin Money Flow (CMF) is a technical analysis indicator used to measure Money Flow Volume over a set period of time. CMF can be used as a way to further quantify changes in buying and selling pressure and can help to anticipate future changes and therefore trading opportunities. CMF calculations is based on Accumulation/Distribution
4-Market Volatility : CBOE Volatility Index (VIX), the Volatility Index, or VIX, is a real-time market index that represents the market's expectation of 30-day forward-looking volatility. Derived from the price inputs of the S&P 500 index options, it provides a measure of market risk and investors' sentiments. It is also known by other names like "Fear Gauge" or "Fear Index." Investors, research analysts and portfolio managers look to VIX values as a way to measure market risk, fear and stress before they take investment decisions
5-Safe Haven Demand : in this study GOLD demand is assumed
What to look for :
*Fear and Greed Index as explained above,
*Divergencies
Tool tip of the label displayed provides details of references
Conclusion:
As investors, we always get caught up in the day to day price movements, and lose sight of the bigger picture. The biggest crashes happen not when investors are cautious and fearful, it's when they're euphoric and expecting financial instruments to continue going higher. So as we continue investing, don’t forget to stop and ask yourself, where in the chart do you think we are right now? The Market Psychology Cycle shines light on how emotions evolve, fear and greed index can come in handy, provided that it is not the only tool used to make investment decisions. It is easy to look back at market cycles and recognize how the overall psychology changed. Analyzing previous data makes it obvious what actions and decisions would have been the most profitable. However, it is much harder to understand how the market is changing as it goes - and even harder to predict what comes next. Many investors use technical analysis (TA) to attempt to anticipate where the market is likely to go. Investors are advised to keep tabs on fear for potential buying the dips opportunities and view periods of greed as a potential indicator that financial instruments might be overvalued.
Warren Buffett's quote, buy when others are fearful, and sell when others are greedy
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
Disclaimer : The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Underworld Hunter Backtesting AlgorhitmThis strategy is built to prove the profitability of my Underworld Hunter indicator . It tests two different strategies. I won't be going into the calculation again since it is part of the original script. I just made a few adjustments.
First one is clearly visual. It plots slimmer twin-coloured lines now and has a different colour for every extreme level. Second is less obvious - I switched Relative Strength Index for Commodity Channel Index.
Extreme levels are as follows: green 100 -► 120, yellow 120 -► 140, orange 140 -► 160, red 160 -► 180 and purple above 180, I will have a special separate algorithm for testing optimal CCI levels someday, in this script, these values are only meant to help you with manual operations and do not influence results of the strategy in any way.
#Trending strategy
The trending strategy opens a position whenever the price leaves the bands and holds it until two consecutive bars are closed within the bands. The picture shows one winning position that hasn't yet been resulted. It also shows a few fakeouts. For this strategy, you want to keep the length below 110, the deviation should be below 2 and you probably want to play lower timeframes.
#Within the bands
The second strategy is pretty much the opposite. It opens a position when the price reaches outer bands and holds it until two consecutive bars are closed within the bands and current bar closes below previous bars low in case of long. It is working on hourly timeframes and you need higher length and deviation to succeed. The picture shows a few positions on EURUSD. Each of them is profitable but would be much higher if you closed it manually when it was time. You need to enable this strategy, which automatically disables the other one.
When using my script, you need to bear in mind that the first strategy doesn't detect optimal levels to close the price. A trend is often followed by a less volatile and boring correction which causes bands to shrink and lower your profits if you don't close manually as it will take longer till bands are reached.
On the other hand, second script literally has no stop-loss. As long as the price is outside the range, it will never close which will cause major drawdowns, unless you control the trade manually. CCI is here to help you with both.
I also recommend combining this with Market Profile (on TW, there is only Volume Profile, which can be used in a similar way) and trading day theory (trending with multiple distributions, trending day, normal day, a variation on a normal day, non-trending day or neutral day). Always keep in mind that it is up to traders to be profitable, indicators can support a good trader, but they will not fix a bad one.
Patient Trendfollower (7)(alpha)Patient Trendfollower consists of 21 and 55 EMA, Commodity Channel Index and Supertrend indicator. It confirms a trend and gives you a signal on a pullback. Original creation worked on 1h EURUSD chart.
►Long setup:
• 21 EMA is above 55 EMA, which is above the Supertrend indicator.
• Commodity Channel Index is an oscillator, which prints into the chart if extreme levels are reached. Green is for a level above 100 or below -100, red is above 140 or below -140 and black is above 180 or below -180.
• If 21 EMA > 55EMA > Supertrend and an oversold signal appear, you can buy into the trend.
• When backtesting on 1h EURUSD, profit target 400 pips worked best with a stop-loss below Supertrend's bottom and the size of your spread.
• A picture shows two valid entries.
: This part still malfunctions and shows red dots over some green ones. It is important to disable red ones in the settings to see green ones.
Some more long signals:
Some short signals:
►Backtesting data with default settings and trading only green CCI signals with mentioned risk management strategy:
• 212 closed trades
• 58.96% profitable with average win trade 348 USD and average loss trade 263 USD when only green signals are followed.
• Profit factor 1.903, Sharpee 0.792
• 20 bars is average for all trades, short trades were 18 bars long on average.
With given data, you can see the strategy is profitable by itself. However, original risk management settings do work only on 1h charts of EURUSD and would need to be adjusted for other instruments based on average volatility.
Even though the profitability is low, you can increase your odds by a great margin, if you properly use price action (impulsive and corrective moves, patterns, bar analysis), if you trade when major exchanges are open, you may also use wave analysis such as Elliot Waves or Market Profiles to predict whether the next day might be a trending day. My backtesting program didn't consider these ideas.
Unfortunately, I won't be making backtesting strategy public with it anytime soon, because it still has some parts that do not work. I am ok with that since I understand the code and know what does malfunction and how. Then, there are parts which I am not sure how to fix yet. This is why the indicator is still considered alpha.
In the future when a strategy is published, you will also be able to set your own overbought/oversold values without entering the code itself and probably some other features. But I am not in a hurry for that. You can give me feedback on UX and try to figure out the best setups for other symbols, it might help to improve the automatic testing script when I know what I should achieve. My main point is to make this public for friends who can already be using it on EURUSD at least.
Close doesn't always have to be 400 pips, you might want to close on a logical level such as strong resistance or a trendline too.
Thanks to:
• @everget for providing Supertrend solution.
• Satik FX who hand-tested the system by hand and reported results in this article . He is my main inspiration for creating the complete indicator as one because I want to be able to show and hide it with a single click. My future scripts will also work as a whole strategy each by itself.
• The number in the script's name comes from Satik's numbering. A mentioned article was his seventh shared strategy.
Efficient PriceTrading The Movements That Matters
Inspired by the Price Volume Trend indicator the Efficient Price aim to create a better version of the price containing only the information a trend trader must need.
Calculation
This indicator use the Efficiency Ratio as a smoothing constant, it is calculated as follow :
ER = abs(change(close,length))/sum(abs(change(close)),length)
The goal of the Efficiency Ratio is to show if the market is trending or ranging.If ER is high then the market is considered to be trending, if ER is low then the market is considered to be ranging.
Then the Efficient Price is calculated :
EP = cum(change(close)*ER)
When the price is trending, the indicator will show movements of the price with unchanged volatility, but if the price is not trending then the indicator will flatten those movements.Think of this indicator as both a filter and a compressor and the Efficient Price as some kind of threshold.
The Efficient Price As Input For Indicators/Strategies
If the indicator show the movement of the trending price, it can be interesting to use it as input in order to reduce the number of false signals in a strategy.
We will test 2 MACD strategy provided by tradingview, one using the closing price (In Red) and one with the efficient price (In White) as input
with both the following parameters :
fastLength = 50
slowlength = 200
MACDLength = 20
length = 50
Where length is the parameter of the Efficient Price.A spread of 2 pips is used.
Without Efficient Price : 26.88% of profitability, 69 pips of profit.
With Efficient Price : 38.46% of profitability, 336 pips of profit.
The difference of profitability is of 11.58%, the strategy with the Efficient Price made few trades and its equity have a lower variance than the equity of the MACD strategy using closing price.
Smoothed Version
It is possible to smooth the indicator output by using the following code :
EP = cum(change(close,length)*ER)
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
Gold/Silver 30m Only Strategy Buy/Sell SignalsIn my free time I felt like coding this strategy, and after backtesting it, it appears that the 30m time frame is the most profitable.
I only have been working on it for gold, but it should work similarly for silver as well.
This includes no pyramiding, and with pyramiding orders of 5, this strategy is upwards of 100% profitable.
Buy order - when price is above the 162 day EMA and RSI is less than 35
Sell order - when price is below the 162 day EMA and RSI is greater than 65
I will probably be adjusting it to increase the profitability and %success rate.
IU Martingale StrategyDESCRIPTION
This strategy is a Martingale-based trading system that enters a long position based on simple candle patterns and doubles the position size after each loss. It tracks the worst-case drawdown using a live risk matrix table to help traders visualize the downside. With clear profit and loss points, auto position sizing, and a risk visualization table, it’s perfect for backtesting the Martingale concept directly on charts.
WHAT IS MARTINGALE SYSTEM?
The Martingale system is a position-sizing strategy where you double your trade size after every loss, aiming to recover all previous losses with a single profitable trade. It assumes that a winning trade will eventually occur. While it can be high-risk, it’s often used in controlled environments or with high probability setups.
USER INPUTS
📦 Starting Position: Initial position size for the first trade
📈 Profit Points: Target profit in price points
📉 Loss Points: Stop loss in price points
📊 Show Risk Matrix Table: Enable or disable a live table showing current streak and risk stats
LONG CONDITION
A long trade is triggered when the current candle closes higher than it opened, and no open position exists. The condition is simple and used to simulate market entry for testing the Martingale logic.
// Entry Condition:
close > open and no existing position
LONG EXIT
Each trade has a fixed stop-loss and take-profit, based on the user's input:
Stop Loss = Entry Price − Loss Points
Take Profit = Entry Price + Profit Points
The exit is handled using strategy.exit() with these dynamic values.
WHY IT IS UNIQUE
🔁 Implements a dynamic Martingale position sizing system
📊 Includes a visual Risk Matrix Table tracking losing streaks, max size, and risk
📈 Automatically resets position size after a win
🧠 Smart use of array to manage loss history and control logic
🎯 Customizable SL and TP for each entry
🎨 Beautiful chart visuals for entry, stop loss, and target levels
HOW USER CAN BENEFIT FROM IT
🧪 Test the sustainability of a Martingale system with real chart data
👁️ Visualize the risks and impact of consecutive losses
📈 Explore risk vs. reward scenarios before deploying in real markets
🧰 Use it as a base template to build more advanced Martingale or grid-based systems
📚 Great for educational purposes to understand the mathematical drawdowns involved in doubling strategies
Disclaimer :
This Video is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
All SMAs Bullish/Bearish Screener (Enhanced)All SMAs Bullish/Bearish Screener Enhanced: Uncover High-Conviction Trend Alignments with Confidence
Description:
Are you ready to elevate your trading from mere guesswork to precise, data-driven decisions? The "All SMAs Bullish/Bearish Screener Enhanced" is not just another indicator; it's a sophisticated, yet user-friendly, trend-following powerhouse designed to cut through market noise and pinpoint high-probability trading opportunities. Built on the foundational strength of comprehensive Moving Average confluence and fortified with critical confirmation signals from Momentum, Volume, and Relative Strength, this script empowers you to identify truly robust trends and manage your trades with unparalleled clarity.
The Power of Multi-Factor Confluence: Beyond Simple Averages
In the unpredictable world of financial markets, true strength or weakness is rarely an isolated event. It's the harmonious alignment of multiple technical factors that signals a high-conviction move. While our original "All SMAs Bullish/Bearish Screener" intelligently identified stocks where price was consistently above or below a full spectrum of Simple Moving Averages (5, 10, 20, 50, 100, 200), this Enhanced version takes it a crucial step further.
We've integrated a powerful three-pronged confirmation system to filter out weaker signals and highlight only the most compelling setups:
Momentum (Rate of Change - ROC): A strong trend isn't just about price direction; it's about the speed and intensity of that movement. Positive momentum confirms that buyers are still aggressively pushing price higher (for bullish signals), while negative momentum validates selling pressure (for bearish signals).
Volume: No trend is truly trustworthy without the backing of smart money. Above-average volume accompanying an "All SMAs" alignment signifies strong institutional participation and conviction behind the move. It separates genuine trend starts from speculative whims.
Relative Strength Index (RSI): This versatile oscillator ensures the trend isn't just "there," but that it's developing healthily. We use RSI to confirm a bullish bias (above 50) or a bearish bias (below 50), adding another layer of confidence to the direction.
When the price aligns above ALL six critical SMAs, and is simultaneously confirmed by robust positive momentum, healthy volume, and a bullish RSI bias, you have an exceptionally strong "STRONGLY BULLISH" signal. This confluence often precedes sustained upward moves, signaling prime accumulation phases. Conversely, a "STRONGLY BEARISH" signal, where price is below ALL SMAs with negative momentum, confirming volume, and a bearish RSI bias, indicates powerful distribution and potential for significant downside.
How to Use This Enhanced Screener:
Add to Chart: Go to TradingView's Pine Editor, paste the script, and click "Add to Chart."
Customize Parameters: Fine-tune the lengths of your SMAs, RSI, Momentum, and Volume averages via the indicator's settings. Experiment to find what best suits your trading style and the assets you trade.
Choose Your Timeframe Wisely:
Daily (1D) and 4-Hour (240 min) are highly recommended. These timeframes cut through intraday noise and provide more reliable, actionable signals for swing and position trading.
Shorter timeframes (e.g., 15min, 60min) can be used by advanced day traders for very short-term entries, but be aware of increased volatility and noise.
Visual Confirmation:
Green/Red Triangles: Appear on your chart, indicating confirmed bullish or bearish signals.
Background Color: The chart background will subtly turn lime green for "STRONGLY BULLISH" and red for "STRONGLY BEARISH" conditions.
On-Chart Status Table: A clear table displays the current signal status ("STRONGLY BULLISH/BEARISH," or "SMAs Mixed") for immediate feedback.
Set Up Alerts (Your Primary Screener Tool): This is the game-changer! Create custom alerts on TradingView based on the "Confirmed Bullish Trade" and "Confirmed Bearish Trade" conditions. Receive instant notifications (email, pop-up, mobile) for any stock in your watchlist that meets these stringent criteria. This allows you to scan the entire market effortlessly and act decisively.
Strategic Stop-Loss Placement: The Trader's Lifeline
Even the most robust signals can fail. Protecting your capital is paramount. For this trend-following strategy, your stop-loss should be placed where the underlying trend structure is broken.
For a "STRONGLY BULLISH" Trade: Place your stop-loss just below the most recent significant swing low (higher low). This is the last point where buyers stepped in to support the price. If price breaks below this, your bullish thesis is invalidated.
For a "STRONGLY BEARISH" Trade: Place your stop-loss just above the most recent significant swing high (lower high). If price breaks above this, your bearish thesis is invalidated.
Alternatively, consider placing your stop-loss just below the 20-period SMA (for bullish trades) or above the 20-period SMA (for bearish trades). A significant close beyond this intermediate-term average often indicates a critical shift in momentum. Always ensure your chosen stop-loss adheres to your pre-defined risk per trade (e.g., 1-2% of capital).
Disciplined Profit Booking: Maximizing Gains
Just as important as knowing when you're wrong is knowing when to take profits.
Trailing Stop-Loss: As your trade moves into profit, trail your stop-loss upwards (for longs) or downwards (for shorts). You can trail it using:
Previous Swing Lows/Highs: Move your stop to just below each new higher low (for longs) or just above each new lower high (for shorts).
A Moving Average (e.g., 10-period or 20-period SMA): If price closes below your chosen trailing SMA, exit. This allows you to ride the trend while protecting accumulated profits.
Target Levels: Identify potential resistance levels (for longs) or support levels (for shorts) using pivot points, previous highs/lows, or Fibonacci extensions. Consider taking partial profits at these levels and letting the rest run with a trailing stop.
Loss of Confluence: If the "STRONGLY BULLISH/BEARISH" condition ceases to be met (e.g., RSI crosses below 50, or volume drops significantly), this can be a signal to reduce or exit your position, even if your stop-loss hasn't been hit.
The "All SMAs Bullish/Bearish Screener Enhanced" is your comprehensive partner in navigating the markets. By combining robust trend identification with critical confirmation signals and disciplined risk management, you're equipped to make smarter, more confident trading decisions. Add it to your favorites and unlock a new level of precision in your trading journey!
#PineScript #TradingView #SMA #MovingAverage #TrendFollowing #StockScreener #TechnicalAnalysis #Bullish #Bearish #QQQ #Momentum #Volume #RSI #SPY #TradingStrategy #Enhanced #Signals #Analysis #DayTrading #SwingTrading
TitanGrid L/S SuperEngineTitanGrid L/S SuperEngine
Experimental Trend-Aligned Grid Signal Engine for Long & Short Execution
🔹 Overview
TitanGrid is an advanced, real-time signal engine built around a tactical grid structure.
It manages Long and Short trades using trend-aligned entries, layered scaling, and partial exits.
Unlike traditional strategy() -based scripts, TitanGrid runs as an indicator() , but includes its own full internal simulation engine.
This allows it to track capital, equity, PnL, risk exposure, and trade performance bar-by-bar — effectively simulating a custom backtest, while remaining compatible with real-time alert-based execution systems.
The concept was born from the fusion of two prior systems:
Assassin’s Grid (grid-based execution and structure) + Super 8 (trend-filtering, smart capital logic), both developed under the AssassinsGrid framework.
🔹 Disclaimer
This is an experimental tool intended for research, testing, and educational use.
It does not provide guaranteed outcomes and should not be interpreted as financial advice.
Use with demo or simulated accounts before considering live deployment.
🔹 Execution Logic
Trend direction is filtered through a custom SuperTrend engine. Once confirmed:
• Long entries trigger on pullbacks, exiting progressively as price moves up
• Short entries trigger on rallies, exiting as price declines
Grid levels are spaced by configurable percentage width, and entries scale dynamically.
🔹 Stop Loss Mechanism
TitanGrid uses a dual-layer stop system:
• A static stop per entry, placed at a fixed percentage distance matching the grid width
• A trend reversal exit that closes the entire position if price crosses the SuperTrend in the opposite direction
Stops are triggered once per cycle, ensuring predictable and capital-aware behavior.
🔹 Key Features
• Dual-side grid logic (Long-only, Short-only, or Both)
• SuperTrend filtering to enforce directional bias
• Adjustable grid spacing, scaling, and sizing
• Static and dynamic stop-loss logic
• Partial exits and reset conditions
• Webhook-ready alerts (browser-based automation compatible)
• Internal simulation of equity, PnL, fees, and liquidation levels
• Real-time dashboard for full transparency
🔹 Best Use Cases
TitanGrid performs best in structured or mean-reverting environments.
It is especially well-suited to assets with the behavioral profile of ETH — reactive, trend-intraday, and prone to clean pullback formations.
While adaptable to multiple timeframes, it shows strongest performance on the 15-minute chart , offering a balance of signal frequency and directional clarity.
🔹 License
Published under the Mozilla Public License 2.0 .
You are free to study, adapt, and extend this script.
🔹 Panel Reference
The real-time dashboard displays performance metrics, capital state, and position behavior:
• Asset Type – Automatically detects the instrument class (e.g., Crypto, Stock, Forex) from symbol metadata
• Equity – Total simulated capital: realized PnL + floating PnL + remaining cash
• Available Cash – Capital not currently allocated to any position
• Used Margin – Capital locked in open trades, based on position size and leverage
• Net Profit – Realized gain/loss after commissions and fees
• Raw Net Profit – Gross result before trading costs
• Floating PnL – Unrealized profit or loss from active positions
• ROI – Return on initial capital, including realized and floating PnL. Leverage directly impacts this metric, amplifying both gains and losses relative to account size.
• Long/Short Size & Avg Price – Open position sizes and volume-weighted average entry prices
• Leverage & Liquidation – Simulated effective leverage and projected liquidation level
• Hold – Best-performing hold side (Long or Short) over the session
• Hold Efficiency – Performance efficiency during holding phases, relative to capital used
• Profit Factor – Ratio of gross profits to gross losses (realized)
• Payoff Ratio – Average profit per win / average loss per loss
• Win Rate – Percent of profitable closes (including partial exits)
• Expectancy – Net average result per closed trade
• Max Drawdown – Largest recorded drop in equity during the session
• Commission Paid – Simulated trading costs: maker, taker, funding
• Long / Short Trades – Count of entry signals per side
• Time Trading – Number of bars spent in active positions
• Volume / Month – Extrapolated 30-day trading volume estimate
• Min Capital – Lowest equity level recorded during the session
🔹 Reference Ranges by Strategy Type
Use the following metrics as reference depending on the trading style:
Grid / Mean Reversion
• Profit Factor: 1.2 – 2.0
• Payoff Ratio: 0.5 – 1.2
• Win Rate: 50% – 70% (based on partial exits)
• Expectancy: 0.05% – 0.25%
• Drawdown: Moderate to high
• Commission Impact: High
Trend-Following
• Profit Factor: 1.5 – 3.0
• Payoff Ratio: 1.5 – 3.5
• Win Rate: 30% – 50%
• Expectancy: 0.3% – 1.0%
• Drawdown: Low to moderate
Scalping / High-Frequency
• Profit Factor: 1.1 – 1.6
• Payoff Ratio: 0.3 – 0.8
• Win Rate: 80% – 95%
• Expectancy: 0.01% – 0.05%
• Volume / Month: Very high
Breakout Strategies
• Profit Factor: 1.4 – 2.2
• Payoff Ratio: 1.2 – 2.0
• Win Rate: 35% – 60%
• Expectancy: 0.2% – 0.6%
• Drawdown: Can be sharp after failed breakouts
🔹 Note on Performance Simulation
TitanGrid includes internal accounting of fees, slippage, and funding costs.
While its logic is designed for precision and capital efficiency, performance is naturally affected by exchange commissions.
In frictionless environments (e.g., zero-fee simulation), its high-frequency logic could — in theory — extract substantial micro-edges from the market.
However, real-world conditions introduce limits, and all results should be interpreted accordingly.
(Mustang Algo) Stochastic RSI + Triple EMAStochastic RSI + Triple EMA (StochTEMA)
Overview
The Stochastic RSI + Triple EMA indicator combines the Stochastic RSI oscillator with a Triple Exponential Moving Average (TEMA) overlay to generate clear buy and sell signals on the price chart. By measuring RSI overbought/oversold conditions and confirming trend direction with TEMA, this tool helps traders identify high-probability entries and exits while filtering out noise in choppy markets.
Key Features
Stochastic RSI Calculation
Computes a standard RSI over a user-defined period (default 50).
Applies a Stochastic oscillator to the RSI values over a second user-defined period (default 50).
Smooths the %K line by taking an SMA over a third input (default 3), and %D is an SMA of %K over another input (default 3).
Defines oversold when both %K and %D are below 20, and overbought when both are above 80.
Triple EMA (TEMA)
Calculates three successive EMAs on the closing price with the same length (default 9).
Combines them using TEMA = 3×(EMA1 – EMA2) + EMA3, producing a fast-reacting trend line.
Bullish trend is identified when price > TEMA and TEMA is rising; bearish trend when price < TEMA and TEMA is falling; neutral/flat when TEMA change is minimal.
Signal Logic
Strong Buy: Previous bar’s Stoch RSI was oversold (both %K and %D < 20), %K crosses above %D, and TEMA is in a bullish trend.
Medium Buy: %K crosses above %D (without requiring oversold), TEMA is bullish, and previous %K < 50.
Weak Buy: Previous bar’s %K and %D were oversold, %K crosses above %D, TEMA is flat or bullish (not bearish).
Strong Sell: Previous bar’s Stoch RSI was overbought (both %K and %D > 80), %K crosses below %D, and TEMA is bearish.
Medium Sell: %K crosses below %D (without requiring overbought), TEMA is bearish, and previous %K > 50.
Weak Sell: Previous bar’s %K and %D were overbought, %K crosses below %D, TEMA is flat or bearish (not bullish).
Visual Elements on Chart
TEMA Line: Plotted in cyan (#00BCD4) with a medium-thick line for clear trend visualization.
Buy/Sell Markers:
BUY STRONG: Lime label below the candle
BUY MEDIUM: Green triangle below the candle
BUY WEAK: Semi-transparent green circle below the candle
SELL STRONG: Red label above the candle
SELL MEDIUM: Orange triangle above the candle
SELL WEAK: Semi-transparent orange circle above the candle
Candle & Background Coloring: When a strong buy or sell signal occurs, the candle body is tinted (semi-transparent lime/red) and the chart background briefly flashes light green (buy) or light red (sell).
Dynamic Support/Resistance:
On a strong buy signal, a green dot is plotted under that bar’s low as a temporary support marker.
On a strong sell signal, a red dot is plotted above that bar’s high as a temporary resistance marker.
Alerts
Strong Buy Alert: Triggered when Stoch RSI is oversold, %K crosses above %D, and TEMA is bullish.
Strong Sell Alert: Triggered when Stoch RSI is overbought, %K crosses below %D, and TEMA is bearish.
General Buy Alert: Triggered on any bullish crossover (%K > %D) when TEMA is not bearish.
General Sell Alert: Triggered on any bearish crossover (%K < %D) when TEMA is not bullish.
Inputs
Stochastic RSI Settings (group “Stochastic RSI”):
K (smoothK): Period length for smoothing the %K line (default 3, minimum 1)
D (smoothD): Period length for smoothing the %D line (default 3, minimum 1)
RSI Length (lengthRSI): Number of bars used for the RSI calculation (default 50, minimum 1)
Stochastic Length (lengthStoch): Number of bars for the Stochastic oscillator applied to RSI (default 50, minimum 1)
RSI Source (src): Price source for the RSI (default = close)
TEMA Settings (group “Triple EMA”):
TEMA Length (lengthTEMA): Number of bars used for each of the three EMAs (default 9, minimum 1)
How to Use
Add the Script
Copy and paste the indicator code into TradingView’s Pine Editor (version 6).
Save the script and add it to your chart as “Stochastic RSI + Triple EMA (StochTEMA).”
Adjust Inputs
Choose shorter lengths for lower timeframes (e.g., intraday scalping) and longer lengths for higher timeframes (e.g., swing trading).
Fine-tune the Stochastic RSI parameters (K, D, RSI Length, Stochastic Length) to suit the volatility of the instrument.
Modify TEMA Length if you prefer a faster or slower moving average response.
Interpret Signals
Primary Entries/Exits: Focus on “BUY STRONG” and “SELL STRONG” signals, as they require both oversold/overbought conditions and a confirming TEMA trend.
Confirmation Signals: Use “BUY MEDIUM”/“BUY WEAK” to confirm or add to an existing position when the market is trending. Similarly, “SELL MEDIUM”/“SELL WEAK” can be used to scale out or confirm bearish momentum.
Support/Resistance Dots: These help identify recent swing lows (green dots) and swing highs (red dots) that were tagged by strong signals—useful to place stop-loss or profit-target orders.
Set Alerts
Open the Alerts menu (bell icon) in TradingView, choose this script, and select the desired alert condition (e.g., “BUY Signal Strong”).
Configure notifications (popup, email, webhook) according to your trading workflow.
Notes & Best Practices
Filtering False Signals: By combining Stoch RSI crossovers with TEMA trend confirmation, most false breakouts during choppy price action are filtered out.
Timeframe Selection: This indicator works on all timeframes, but shorter timeframes may generate frequent signals—consider higher-timeframe confirmation when trading lower timeframes.
Risk Management: Always use proper position sizing and stop-loss placement. An “oversold” or “overbought” reading can remain extended for some time in strong trends.
Backtesting/Optimization: Before live trading, backtest different parameter combinations on historical data to find the optimal balance between sensitivity and reliability for your chosen instrument.
No Guarantee of Profits: As with any technical indicator, past performance does not guarantee future results. Use in conjunction with other forms of analysis (volume, price patterns, fundamentals).
Author: Your Name or Username
Version: 1.0 (Pine Script v6)
Published: June 2025
Feel free to customize input values and visual preferences. If you find bugs or have suggestions for improvements, open an issue or leave a comment below. Trade responsibly!
Options Risk Manager v2.2.0 - Priority 7 CompleteScript Description for TradingView Publication
Options Risk Manager v2.2.0 - Priority 7 Complete
What does this script do?
Options Risk Manager v2.2.0 is a comprehensive position management system designed specifically for options traders. The indicator calculates precise stop loss levels, risk/reward targets, and position sizing based on user-defined risk parameters. It provides real-time profit/loss tracking, options Greeks monitoring, and automated alert systems for critical price levels.
The script displays entry points, stop losses, and profit targets directly on the chart while continuously calculating position metrics including dollar risk, account exposure, and probability of success. Version 2.2.0 introduces Priority 7 advanced alerts with dynamic risk warnings and multi-condition notifications.
How does it do it?
The script performs several key calculations:
1. Risk-Based Stop Loss Calculation - Determines stop loss levels based on percentage of entry price, automatically adjusting for calls versus puts. Put positions place stops above entry, while calls place stops below.
2. Position Sizing Algorithm - Calculates optimal contract quantities using account size, risk
percentage, and stop distance to ensure consistent risk per trade regardless of underlying price.
3. Options-Specific P&L Tracking - Incorporates Delta, Gamma, Vega, and Theta to provide accurate profit/loss calculations for options positions, including time decay effects.
4. Three-Phase Trade Management - Implements systematic position management through Entry
Phase (initial risk), Profit Phase (approaching target), and Trailing Phase (EMA-based exit
management).
5. Multi-Level Alert System - Monitors price action, Greeks thresholds, time decay acceleration, and account risk levels to generate context-aware notifications.
How to use it?
Initial Setup:
1. Apply indicator to any optionable security
2. Toggle "In Position" ON when entering a trade
3. Set Direction (Call/Put) and Side (Long/Short)
4. Enter the underlying price at position entry
5. Specify number of contracts and risk percentage
Position Management:
Blue line shows entry price
Red line indicates stop loss level
Orange line displays risk/reward target
Purple EMA line activates after target hit
Monitor real-time P&L in trade panels
Alert Configuration:
Enable Advanced Alerts in settings
Set profit/loss notification thresholds
Configure Greek-based warnings
Activate time decay alerts for expiration
Risk Parameters:
Risk % determines stop distance from entry
Account Value sets position sizing limits
Contract Multiplier (standard = 100)
R:R Ratio defines profit targets
What makes it unique?
Options Risk Manager addresses the specific challenges of options trading that generic indicators miss. The script accounts for the inverse relationship in put options (profiting from price declines), incorporates Greeks for accurate P&L calculations, and provides options-specific limit orders for TradeStation integration.
The three-phase management system removes emotional decision-making by defining clear rules for position management. Phase transitions occur automatically based on price action, shifting from initial risk management to profit protection to trend-following modes.
Version 2.2.0's Priority 7 alert system provides intelligent notifications that include live metrics, risk warnings, and market context rather than simple price crosses.
Key Features Summary
Options-Specific Calculations - Proper handling of calls/puts with inverse relationships
Risk-Based Position Sizing - Consistent risk regardless of underlying price
Greeks Integration - Delta, Gamma, Vega, Theta for accurate tracking
Phase Management System - Systematic three-stage position handling
Advanced Alert System - Context-aware notifications with metrics
TradeStation Integration - Option limit orders for execution
Visual Risk Display - Clear chart overlays for all levels
Probability Calculator - Win/loss probability with expected value
Multi-Account Support - Scales from small to large accounts
Important Notes
This indicator requires manual input of option prices and Greeks (available from your broker's option chain). It functions as a risk management overlay and does not generate entry signals. The calculations assume standard options contracts of 100 shares.
Designed for TradeStation platform with full functionality. Basic features available on other platforms
without options data integration. Always verify calculations with your broker's risk system before placing
trades.
Strategy Builder With IndicatorsThis strategy script is designed for traders who enjoy building systems using multiple indicators.
Please note: This script does not include any built-in indicators. Instead, it works by referencing the plot outputs of the indicators you’ve already added to your chart.
For example, if you add a MACD and an ATR indicator to your chart, you can assign their plot values as inputs in the settings panel of this strategy.
• MACD as a trigger
• ATR as a filter
How Filters Work
Filters check whether certain conditions are met before a trade can be opened. For instance, if you set a filter like ATR > 30, then no trade will be executed unless that condition is true — even if the trigger fires.
All filters are linked, meaning every active filter must be satisfied for a trade to occur.
How Triggers Work
Triggers are what actually fire a trade signal — such as a moving average crossover or RSI breaking above a specific level. Unlike filters, triggers are independent. Only one active trigger needs to be true for the trade to execute.
Thanks to its modular structure, this strategy can be used with any indicator of your choice.
⸻
Risk Management Features
In the settings, you’ll find flexible options for:
• Stop Loss (SL)
• Trailing Stop Loss (TSL)
• Multi Take-Profit (TP)
These features enhance trade safety and let you tailor your risk management.
SL types available:
• Tick-based SL
• Percent-based SL
• ATR-based SL
Once you select your preferred SL type, you can fine-tune its distance using the offset field.
Trailing SL allows your stop to follow price as it moves in your favor — helping to lock in profits.
Multi-TP lets you take profits at two different levels, helping you secure gains while leaving room for extended moves.
Breakeven option is also available to automatically move your SL to entry after reaching a profit threshold.
⸻
How to Build a Solid Strategy
Let’s break down a good setup into three key components:
1. Trend Filter
Avoid trading against the trend — that’s like swimming against the current.
Use a filter like:
• Supertrend
• Momentum indicators
• Candlestick bias, etc.
Example: In this case, I used Supertrend and filtered for trades only if the price is above the uptrend line.
2. Trigger Condition
Once we confirm the trend is on our side, we need a trigger to execute at the right moment. This can be:
• RSI cross
• Candlestick patterns
• Trendline breaks
• Moving average crossovers, etc.
Example: I used RSI crossing above 50 as the entry trigger.
3. Risk Management
Even in the right trend at the right time — anything can happen. That’s why you should always define Stop Loss and Take Profit levels.
⸻
And there you have it! Your strategy is ready to backtest, refine, and deploy with alerts for live trading.
Questions or suggestions? Feel free to reach out
Dr.Avinash Talele quarterly earnings, VCP and multibagger trakerDr. Avinash Talele Quarterly Earnings, VCP and Multibagger Tracker.
📊 Comprehensive Quarterly Analysis Tool for Multibagger Stock Discovery
This advanced Pine Script indicator provides a complete financial snapshot directly on your chart, designed to help traders and investors identify potential multibagger stocks and VCP (Volatility Contraction Pattern) setups with precision.
🎯 Key Features:
📈 8-Quarter Financial Data Display:
EPS (Earnings Per Share) - Track profitability trends
Sales Revenue - Monitor business growth
QoQ% (Quarter-over-Quarter Growth) - Spot acceleration/deceleration
ROE (Return on Equity) - Assess management efficiency
OPM (Operating Profit Margin) - Evaluate operational excellence
💰 Market Metrics:
Market Cap - Current company valuation
P/E Ratio - Valuation assessment
Free Float - Liquidity indicator
📊 Technical Positioning:
% Down from 52-Week High - Identify potential bottoming patterns
% Up from 52-Week Low - Track momentum from lows
Turnover Data (1D & 50D Average) - Volume analysis
ADR% (Average Daily Range) - Volatility measurement
Relative Volume% - Institutional interest indicator
🚀 How It Helps Find Multibaggers:
1. Growth Acceleration Detection:
Consistent EPS Growth: Identifies companies with accelerating earnings
Revenue Momentum: Tracks sales growth patterns quarter-over-quarter
Margin Expansion: Spots improving operational efficiency through OPM trends
2. VCP Pattern Recognition:
Volatility Contraction: ADR% helps identify tightening price ranges
Volume Analysis: Relative volume shows institutional accumulation
Distance from Highs: Tracks healthy pullbacks in uptrends
3. Fundamental Strength Validation:
ROE Trends: Ensures management is efficiently using shareholder capital
Debt-Free Growth: High ROE with growing margins indicates quality growth
Scalability: Revenue growth vs. margin expansion analysis
4. Entry Timing Optimization:
52-Week Positioning: Enter near lows, avoid near highs
Volume Confirmation: High relative volume confirms breakout potential
Valuation Check: P/E ratio helps avoid overvalued entries
💡 Multibagger Characteristics to Look For:
✅ Consistent 15-20%+ EPS growth across multiple quarters
✅ Accelerating revenue growth with QoQ% improvements
✅ ROE above 15% and expanding
✅ Operating margins improving over time
✅ Low debt (indicated by high ROE with growing profits)
✅ Strong cash generation (reflected in consistent growth metrics)
✅ 20-40% down from 52-week highs (ideal entry zones)
✅ Above-average volume during consolidation phases
🎨 Visual Design:
Clean white table with black borders for maximum readability
Color-coded QoQ% changes (Green = Growth, Red = Decline)
Centered positioning for easy chart analysis
8-quarter historical view for trend identification
📋 Perfect For:
Long-term investors seeking multibagger opportunities
Growth stock enthusiasts tracking earnings acceleration
VCP pattern traders looking for breakout candidates
Fundamental analysts requiring quick financial snapshots
Swing traders timing entries in growth stocks
⚡ Quick Setup:
Simply add the indicator to any NSE/BSE stock chart and instantly view comprehensive quarterly data. The table updates automatically with the latest financial information, making it perfect for screening and monitoring your watchlist.
🔍 Start identifying your next multibagger today with this powerful combination of fundamental analysis and technical positioning data!
Disclaimer: This indicator is for educational and analysis purposes. Always conduct thorough research and consider risk management before making investment decisions.
Chaikin Momentum Scalper🎯 Overview
The Chaikin Momentum Scalper is a powerful trading strategy designed to identify momentum shifts in the market and ride the trend for maximum profits. This strategy is ideal for trading the USD/JPY currency pair on a 15-minute chart, making it perfect for high-frequency trading (HFT). Whether you’re starting with a small account of $1,000 or managing a larger portfolio, this strategy can scale to suit your needs.
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🔑 How the Strategy Works
Here’s how the Chaikin Momentum Scalper identifies trade opportunities:
1️⃣ Momentum Detection
The core of this strategy is the Chaikin Oscillator, a tool that measures the flow of money into or out of a market. It helps us understand whether buyers (bulls) or sellers (bears) are in control.
• When the indicator crosses above zero, it signals that buying momentum is picking up – a buying opportunity.
• When the indicator crosses below zero, it signals that selling momentum is increasing – a selling opportunity.
2️⃣ Trend Confirmation
We don’t just jump into trades based on momentum alone. We also use a 200-period simple moving average (SMA) to confirm the overall trend.
• If the price is above the SMA, it confirms an uptrend, so we look for buy trades.
• If the price is below the SMA, it confirms a downtrend, so we look for sell trades.
This way, we align our trades with the broader market direction for higher success rates.
3️⃣ Volatility & Risk Management
We use a tool called the Average True Range (ATR) to measure market volatility. This helps us:
• Set a stop-loss (where we’ll exit the trade if the market moves against us) at a safe distance from our entry point.
• Set a take-profit (where we’ll lock in profits) at a target that’s larger than the stop-loss, ensuring a good reward-to-risk ratio.
This approach adapts to the market’s behavior, tightening stops in calmer conditions and widening them when volatility increases.
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📈 Why This Strategy Works
✅ It combines momentum and trend-following principles, increasing the chances of trading in the right direction.
✅ It dynamically adjusts risk levels based on market volatility, keeping losses small and profits big.
✅ It’s scalable – perfect for both small accounts (like $1,000) and larger, corporate-sized portfolios.
✅ It has been deep-backtested on USD/JPY 15-minute charts, proving its consistency across different market conditions.
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📝 Important Notes
📌 This strategy is best used for USD/JPY on a 15-minute chart, making it great for high-frequency trading while you continue to build and refine your trading system.
📌 It’s designed to work on both small ($1,000+) and large accounts, so it can grow with you as your capital increases.
📌 While it has passed deep backtesting on this pair and timeframe, remember that no strategy is perfect. It’s crucial to test it yourself, start with a demo account, and apply proper risk management before trading real money.
🌟 Final Thoughts
The Chaikin Momentum Scalper is a solid, adaptable trading approach combining momentum, trend direction, and volatility awareness. If you’re looking for a strategy to kick-start your trading journey—or to add to your existing system—it offers a strong foundation.
Grid Tendence V1The “Grid Tendence V1” strategy is based on the classic Grid strategy, only in this case the entries and exits are made in favor of the trend, which allows to take advantage of large movements to maximize profits, since it is also possible to enter and exit with the balance with a controlled risk, because precisely the distance between each Grid works as a natural and adaptable stop loss and take profit. This fact helps to avoid overlapping entries and exits that would result from using stop loss and take profit as limit orders.
In this version of the script the entries and exits are always at market, and based on the percentage change of the price, not on the profit or loss of the current position.
The user will notice that the strategy setup is based on a controlled risk, risking 5% on each trade, a fairly standard commission and a modest initial capital, all this in order to protect the user of the strategy from unexpected or unrealistic results.
However, it is always recommended to optimize the parameters so that the strategy is effective for each asset and for each time frame.
[blackcat] L2 Multi-Level Price Condition TrackerOVERVIEW
The L2 Multi-Level Price Condition Tracker represents an innovative approach to analyzing financial markets by simultaneously monitoring multiple price levels, thus providing traders with a holistic view of market dynamics. By combining dynamic calculations based on moving averages and price deviations, this tool aims to deliver precise and actionable insights into potential entry and exit points. It leverages sophisticated statistical measures to identify key thresholds that signify shifts in market sentiment, thereby aiding traders in making well-informed decisions. 🎯
Key benefits encompass:
• Comprehensive calculation of midpoints and average prices indicating short-term trend directions.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by precise condition evaluations.
TECHNICAL ANALYSIS COMPONENTS
📉 Midpoint Calculations:
Computes central reference points derived from high-low ranges establishing baseline supports/resistances.
Utilizes Simple Moving Averages (SMAs) along with standardized deviation formulas smoothing out volatility while preserving long-term trends accurately.
Facilitates identification of directional biases reflecting underlying market forces dynamically.
🕵️♂️ Advanced Price Level Detection:
Derives upper/lower bounds adjusting sensitivities adaptively responding to changing conditions flexibly.
Employs proprietary logic distinguishing between bullish/bearish sentiments promptly signaling transitions effectively.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy robustly.
🎥 Dynamic Signal Generation:
Detects crossovers indicating dominance shifts between buyers/sellers promptly triggering timely alerts.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations systematically.
Supports adaptive thresholds tuning sensitivities based on evolving market conditions flexibly accommodating varying scenarios.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages alongside standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time midpoint markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively highlighting key activations clearly.
Background shading emphasizing proximity to crucial threshold activations enhancing visibility focusing attention on vital signals promptly.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals assessing concurrent market sentiment factors.
Validate entry decisions considering alignment between calculated midpoints and broader trend directions ensuring coherence.
Monitor cumulative breaches signifying potential trend reversals executing partial/total closes contingent upon predetermined loss limits preserving capital efficiently.
🚫 Exit Mechanisms:
Trigger exits upon hitting predefined thresholds derived from historical analyses promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement implementing corrective actions iteratively enhancing performance metrics steadily.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Lookback Period: Governs responsiveness versus stability balancing sensitivity/stability governing moving averages aligning with preferred granularity.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately tailoring strategies accordingly.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts evaluating adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity sustaining balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches preserving capital efficiently.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines managing exposures prudently.
Mandatorily apply trailing stop-loss orders conforming to script outputs enforcing discipline rigorously preventing adverse consequences.
Allocate positions proportionately relative to available capital reserves conducting periodic reviews gauging effectiveness continuously identifying improvement opportunities steadily.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously preparing contingency plans proactively mitigating risks effectively.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically implementing corrective actions reliably.
Prepare proactive responses amid adverse movements ensuring seamless functionality amidst fluctuating conditions fortifying resilience against anomalies robustly.
PERFORMANCE MONITORING METRICS
🔍 Evaluation Criteria:
Assess win percentages consistently across diverse trading instruments gauging reliability measuring profitability efficiency accurately evaluating downside risks comprehensively uncovering systematic biases potentially skewing outcomes.
Calculate average profit ratios per successful execution benchmarking actual vs expected performances documenting results meticulously tracking progress dynamically addressing identified shortcomings proactively fostering continuous improvements.
📈 Historical Data Analysis Tools:
Maintain detailed logs capturing every triggered event recording realized profits/losses comparing simulated projections accurately identifying discrepancies warranting investigation implementing iterative refinements steadily enhancing performance metrics progressively.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily addressing identified shortcomings proactively fostering continuous enhancements dynamically improving robustness resiliently.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes enhancing signal integrity excluding low-liquidity assets prone to erratic movements effectively.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities introducing buffer intervals safeguarding major news/event impacts mitigating distortions seamlessly verifying reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably.
💡 Effective Resolution Pathways:
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently recalibrating parameters periodically adapting strategies flexibly responding appropriately amidst varying conditions dynamically improving robustness resiliently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably bolstering overall efficacy systematically addressing identified shortcomings dynamically fostering continuous advancements.
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights regarding multi-level price condition-based trading methodologies! ✨
[blackcat] L1 Net Volume DifferenceOVERVIEW
The L1 Net Volume Difference indicator serves as an advanced analytical tool designed to provide traders with deep insights into market sentiment by examining the differential between buying and selling volumes over precise timeframes. By leveraging these volume dynamics, it helps identify trends and potential reversal points more accurately, thereby supporting well-informed decision-making processes. The key focus lies in dissecting intraday changes that reflect short-term market behavior, offering critical input for both swing and day traders alike. 📊
Key benefits encompass:
• Precise calculation of net volume differences grounded in real-time data.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by dynamic volume shifts.
TECHNICAL ANALYSIS COMPONENTS
📉 Volume Accumulation Mechanisms:
Monitors cumulative buy/sell volumes derived from comparative closing prices.
Periodically resets accumulation counters aligning with predefined intervals (e.g., 5-minute bars).
Facilitates identification of directional biases reflecting underlying market forces accurately.
🕵️♂️ Sentiment Detection Algorithms:
Employs proprietary logic distinguishing between bullish/bearish sentiments dynamically.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
Supports adaptive thresholds adjusting sensitivities based on changing market conditions flexibly.
🎯 Dynamic Signal Generation:
Detects transitions indicating dominance shifts between buyers/sellers promptly.
Triggers timely alerts enabling swift reactions to evolving market dynamics effectively.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages along with standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time net volume markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between net volume readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Reset Interval: Governs responsiveness versus stability balancing sensitivity/stability.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights about volume-based trading methodologies! ✨
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
[blackcat] L2 Z-Score of PriceOVERVIEW
The L2 Z-Score of Price indicator offers traders an insightful perspective into how current prices diverge from their historical norms through advanced statistical measures. By leveraging Z-scores, it provides a robust framework for identifying potential reversals in financial markets. The Z-score quantifies the number of standard deviations that a data point lies away from the mean, thus serving as a critical metric for recognizing overbought or oversold conditions. 🎯
Key benefits encompass:
• Precise calculation of Z-scores reflecting true price deviations.
• Interactive plotting features enhancing visual clarity.
• Real-time generation of buy/sell signals based on crossover events.
STATISTICAL ANALYSIS COMPONENTS
📉 Mean Calculation:
Utilizes Simple Moving Averages (SMAs) to establish baseline price references.
Provides smooth representations filtering short-term noise preserving long-term trends.
Fundamental for deriving subsequent deviation metrics accurately.
📈 Standard Deviation Measurement:
Quantifies dispersion around established means revealing underlying variability.
Crucial for assessing potential volatility levels dynamically adapting strategies accordingly.
Facilitates precise Z-score derivations ensuring statistical rigor.
🕵️♂️ Z-SCORE DETECTION:
Measures standardized distances indicating relative positions within distributions.
Helps pinpoint extreme conditions signaling impending reversals proactively.
Enables early identification of trend exhaustion phases prompting timely actions.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Integrates SMAs along with standardized deviation formulas generating precise Z-scores.
Employs Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
🖱️ User Interface Elements:
Dedicated plots displaying real-time Z-score markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between Z-score readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Length: Governs responsiveness versus smoothing trade-offs balancing sensitivity/stability.
Price Source: Dictates primary data series driving Z-score computations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
Best SMA FinderThis script, Best SMA Finder, is a tool designed to identify the most robust simple moving average (SMA) length for a given chart, based on historical backtest performance. It evaluates hundreds of SMA values (from 10 to 1000) and selects the one that provides the best balance between profitability, consistency, and trade frequency.
What it does:
The script performs individual backtests for each SMA length using either "Long Only" or "Buy & Sell" logic, as selected by the user. For each tested SMA, it computes:
- Total number of trades
- Profit Factor (total profits / total losses)
- Win Rate
- A composite Robustness Score, which integrates Profit Factor, number of trades (log-scaled), and win rate.
Only SMA configurations that meet the user-defined minimum trade count are considered valid. Among all valid candidates, the script selects the SMA length with the highest robustness score and plots it on the chart.
How to use it:
- Choose the strategy type: "Long Only" or "Buy & Sell"
- Set the minimum trade count to filter out statistically irrelevant results
- Enable or disable the summary stats table (default: enabled)
The selected optimal SMA is plotted on the chart in blue. The optional table in the top-right corner shows the corresponding SMA length, trade count, Profit Factor, Win Rate, and Robustness Score for transparency.
Key Features:
- Exhaustive SMA optimization across 991 values
- Customizable trade direction and minimum trade filters
- In-chart visualization of results via table and plotted optimal SMA
- Uses a custom robustness formula to rank SMA lengths
Use cases:
Ideal for traders who want to backtest and auto-select a historically effective SMA without manual trial-and-error. Useful for swing and trend-following strategies across different timeframes.
📌 Limitations:
- Not a full trading strategy with position sizing or stop-loss logic
- Only one entry per direction at a time is allowed
- Designed for exploration and optimization, not as a ready-to-trade system
This script is open-source and built entirely from original code and logic. It does not replicate any closed-source script or reuse significant external open-source components.
