Multi-Time-Frame Divergence Labels?

CashPrince

New member
Hey Guys--

I thought of an idea that i think would be gold if someone could code it. I day-trade pullbacks and divergences. I am able to spot divergences on MACD and RSI on any time frame and they work pretty well. Could you guys work on an AIO (All In One) divergence TOS script/indicator that is time frame agnostic and can display three colors that spots divergence and reports it in color on a study label as: Potential=Yellow; Positive=Green and Negative=Grey. The labels could include time frames such as 1Minute/1M; 5M; 10M; 15M; 30M; 60M; 1D and 1WK. And the divergence setting can be set individually or AIO for RSI, MACD and Stochastics-Full.

Thank you!
 
Last edited:

diazlaz

Well-known member
2019 Donor
VIP
Hey Guys--

I thought of an idea that i think would be gold if someone could code it. I day-trade pullbacks and divergences. I am able to spot divergences on MACD and RSI on any time frame and they work pretty well. Could you guys work on an AIO (All In One) divergence TOS script/indicator that is time frame agnostic and can display three colors that spots divergence and reports it in color on a study label as: Potential=Yellow; Positive=Green and Negative=Grey. The labels could include time frames such as 1Minute/1M; 5M; 10M; 15M; 30M; 60M; 1D and 1WK. And the divergence setting can be set individually or AIO for RSI, MACD and Stochastics-Full.

Thank you!
Thank you for the idea. Does anyone have a benchmark study that folks think will work well as a benchmark and adopt?

I don't trade divergences at the moment.
 

CashPrince

New member
The study below Identifies Squeeze in 15 Minute time frame:
Code:
#Begin Squeeze Code


input dStr ="15 min";

script Squeeze{
def length  = 20;
def AtrMult = 1.5;
def SdMult  = 2.0;

input period ="Daily";
def valueClose   =  close(period = period);
def valueHigh   =  high(period = period);
def valueLow   =  low(period = period);
def SD = StDev(valueClose, length);
def Avg = Average(valueClose, length);
def ATR = Average(TrueRange(valueHigh, valueClose, valueLow), length);
def SDup = Avg + (SdMult * SD);
def ATRup = Avg + (AtrMult * ATR);
plot Squeeze = if SDup < ATRup
               then 1
               else 0;
}
def dSQ= Squeeze(dStr);
AddLabel(yes, dStr, if dSQ
then  Color.RED else  Color.GREEN); # display label red if has squeeze


#End Squeeze Code

Below is a nice RSI divergence written by Mobius edited by BenTen:
Code:
# RSI_With_Divergence
# Mobius
# V01.01.2013
# 4.15.2019
#hint:<b>RSI with Divergence</b>

# Note: Install this as a new study. Save this study using the name above (the first line of code RSI_With_Divergence).

# To use this study as a scan; DO NOT TRY TO LOAD IT DIRECTLY IN THE SCANNER, IT WILL THROW AN ERROR MESSAGE. Go to the scan tab. Delete any existing scan criteria. Click Add Study Filter. Click the window under Criteria. In that drop down menu click Custom. Delete the existing study. Click Add Condition. Click the down arrow in the Select A Condition window. Click Study. Scroll down the List till you find RSI_With_Divergence and click it. Click on the Plot window and you can choose Dhigh or Dlow in addition to the default plot RSI. If you choose either of the divergence siganls choose is True from the center column. Click on the aggregation period at the top left and set the aggregation period you want scaned. Then click Save and when the popup window shows the warning that this is a custom scan chose OK. Now put the list of stocks you wish to scan in the Scan In box and chose any list you want that to intersect with. If you wish to make this a Dynamic WatchList, save this scan with a name such as RSI_With_Div_WL then in your Gadgets box click the little gear icon, locate the name of the scan you just saved and click it. As equities match the scan criteria they will populate the list.

declare lower;

input n = 14;        #hint nRSI: Periods or length for RSI

input Over_Bought = 70; #hint Over_Bought: Over Bought line

input Over_Sold = 30;   #hint Over_Sold: Over Sold line

def o = open;

def h = high;

def l = low;

def c = close;

def x = BarNumber();

def MidLine = 50;

def NetChgAvg = ExpAverage(c - c[1], n);

def TotChgAvg = ExpAverage(AbsValue(c - c[1]), n);

def ChgRatio = if TotChgAvg != 0

                  then NetChgAvg / TotChgAvg

                  else 0;

plot RSI = 50 * (ChgRatio + 1);

RSI.AssignValueColor(if RSI < Over_Sold

                     then color.yellow

                     else if RSI > Over_Bought

                     then color.yellow

                     else createColor(25, 75, 250));

plot OverSold = Over_Sold;

plot OverBought = Over_Bought;

def bar = BarNumber();

def Currh = if RSI > OverBought

                then fold i = 1 to Floor(n / 2)

                with p = 1

                while p

                do RSI > getValue(RSI, -i)

                else 0;

def CurrPivotH = if (bar > n and

                         RSI == highest(RSI, Floor(n/2)) and

                         Currh)

                     then RSI

                     else double.NaN;

def Currl = if RSI < OverSold

                then fold j = 1 to Floor(n / 2)

                with q = 1

                while q

                do RSI < getValue(RSI, -j)

                else 0;

def CurrPivotL = if (bar > n and

                         RSI == lowest(RSI, Floor(n/2)) and

                         Currl)

                     then RSI

                     else double.NaN;

def CurrPHBar = if !isNaN(CurrPivotH)

                then bar

                else CurrPHBar[1];

def CurrPLBar = if !isNaN(CurrPivotL)

                then bar

                else CurrPLBar[1];

def PHpoint = if !isNaN(CurrPivotH)

              then CurrPivotH

              else PHpoint[1];

def priorPHBar = if PHpoint != PHpoint[1]

                 then CurrPHBar[1]

                 else priorPHBar[1];

def PLpoint = if !isNaN(CurrPivotL)

              then CurrPivotL

              else PLpoint[1];

def priorPLBar = if PLpoint != PLpoint[1]

                 then CurrPLBar[1]

                 else priorPLBar[1];

def HighPivots = bar >= highestAll(priorPHBar);

def LowPivots = bar >= highestAll(priorPLBar);

def pivotHigh = if HighPivots

                then CurrPivotH

                else double.NaN;

plot PlotHline = pivotHigh;

    PlotHline.enableApproximation();

    PlotHline.SetDefaultColor(GetColor(7));

    PlotHline.SetStyle(Curve.Short_DASH);

plot pivotLow = if LowPivots

                then CurrPivotL

                else double.NaN;

    pivotLow.enableApproximation();

    pivotLow.SetDefaultColor(GetColor(7));

    pivotLow.SetStyle(Curve.Short_DASH);

plot PivotDot = if !isNaN(pivotHigh)

                then pivotHigh

                else if !isNaN(pivotLow)

                     then pivotLow

                     else double.NaN;

    pivotDot.SetDefaultColor(GetColor(7));

    pivotDot.SetPaintingStrategy(PaintingStrategy.POINTS);

    pivotDot.SetLineWeight(3);

# End Code RSI with Divergence

For MACD, the code below should have all the logic as well:
Code:
#Begin Code MACD Divergence

input bar = 2;

input fastLength = 12;

input slowLength = 26;

input MACDLength = 9;

input averageType = AverageType.EXPONENTIAL;

plot Diff = MACD(fastLength, slowLength, MACDLength, averageType).Diff;

def SwingHigh = Diff > 0 and Diff >= highest(Diff[1], bar) and Diff >= highest(Diff[-bar], bar);

def SHprice = if SwingHigh then Diff else SHprice[1];

def SHBar = if SwingHigh then BarNumber() else SHBar[1];

def CrossBarL = if Diff crosses below 0 then BarNumber() else CrossBarL[1];

def SwingLow = Diff < 0 and Diff <= lowest(Diff[1], bar) and Diff <= lowest(Diff[-bar], bar);

def SLprice = if SwingLow then Diff else SLprice[1];

def SLBar = if SwingLow then BarNumber() else SLBar[1];

def CrossBarH = if Diff crosses above 0 then BarNumber() else CrossBarH[1];

def SHSP = if SwingHigh then high else SHSP[1];

def SLSP = if SwingLow then low else SLSP[1];

def BearDiv = Diff > 0 and CrossBarL[1] > SHBar[1] and Diff < SHprice[1] and high > SHSP[1] and SHprice[1] - Diff > 0.005;

def BullDiv = Diff < 0 and CrossBarH[1] > SLBar[1] and Diff > SLprice[1] and low < SLSP[1] and Diff - SLprice[1] > 0.005;

def HiddenBearDiv = Diff > 0 and Diff > SHprice[1] and high < SHSP[1] and Diff - SHprice[1] > 0.005;

def HiddenBullDiv = Diff < 0 and Diff < SLprice[1] and low > SLSP[1] and SLprice[1] - Diff > 0.005;

plot BearD = if BearDiv then high else Double.NaN;

        BearD.SetPaintingStrategy(PaintingStrategy.ARROW_DOWN);

        BearD.AssignValueColor(Color.RED);

        BearD.SetLineWeight(3);

plot BullD = if BullDiv then low else Double.NaN;

        BullD.SetPaintingStrategy(PaintingStrategy.ARROW_UP);

        BullD.AssignValueColor(Color.UPTICK);

        BullD.SetLineWeight(3);

plot HiddenBearD = if HiddenBearDiv then high else Double.NaN;

        HiddenBearD.SetPaintingStrategy(PaintingStrategy.ARROW_DOWN);

        HiddenBearD.AssignValueColor(Color.PINK);

        HiddenBearD.SetLineWeight(1);

plot HiddenBullD = if HiddenBullDiv then low else Double.NaN;

        HiddenBullD.SetPaintingStrategy(PaintingStrategy.ARROW_UP);

        HiddenBullD.AssignValueColor(Color.LIME);

        HiddenBullD.SetLineWeight(1);

Alert(BearDiv[1], "Short MACD divergence", Alert.BAR, Sound.Ring);

Alert(BullDiv[1], "Long MACD divergence", Alert.BAR, Sound.Ring);

Alert(HiddenBearDiv[1], "Short hidden MACD divergence", Alert.BAR, Sound.Ring);

Alert(HiddenBullDiv[1], "Long hidden MACD divergence", Alert.BAR, Sound.Ring);


#End Code MACD Divergence
 
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