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Statistics

GraphLibrary "Graph" Library to collect data and draw scatterplot and heatmap as graph method init(this)   Initialise Quadrant Data   Namespace types: Quadrant   Parameters:      this (Quadrant) : Quadrant object that needs to be initialised   Returns: current Quadrant object method init(this)   Initialise Graph Data   Namespace types: Graph   Parameters:      this (Graph) : Graph object that needs to be initialised with 4 Quadrants   Returns: current Graph object method add(this, data)   Add coordinates to graph   Namespace types: Graph   Parameters:      this (Graph) : Graph object      data (Coordinate) : Coordinates containing x, y data   Returns: current Graph object method calculate(this)   Calculation required for plotting the graph   Namespace types: Graph   Parameters:      this (Graph) : Graph object   Returns: current Graph object method paint(this)   Draw graph   Namespace types: Graph   Parameters:      this (Graph) : Graph object   Returns: current Graph object Coordinate   Coordinates of sample data   Fields:      xValue (series float) : x value of the sample data      yValue (series float) : y value of the sample data Quadrant   Data belonging to particular quadrant   Fields:      coordinates (array) : Coordinates present in given quadrant GraphProperties   Properties of Graph that needs to be drawn   Fields:      rows (series int) : Number of rows (y values) in each quadrant      columns (series int) : number of columns (x values) in each quadrant      graphtype (series GraphType) : Type of graph - scatterplot or heatmap      plotColor (series color) : color of plots or heatmap      plotSize (series string) : size of cells in the table      plotchar (series string) : Character to be printed for display of scatterplot      outliers (series int) : Excude the outlier percent of data from calculating the min and max      position (series string) : Table position      bgColor (series color) : graph background color PlotRange   Range of a plot in terms of x and y values and the number of data points that fall within the Range   Fields:      minX (series float) : min range of X value      maxX (series float) : max range of X value      minY (series float) : min range of Y value      maxY (series float) : max range of Y value      count (series int) : number of samples in the range Graph   Graph data and properties   Fields:      properties (GraphProperties) : Graph Properties object associated      quadrants (array) : Array containing 4 quadrant data      plotRanges (matrix) : range and count for each cell      xArray (array) : array of x values      yArray (array) : arrray of y values
Biblioteca Pine Script®
por Trendoscope
PubLibPatternLibrary "PubLibPattern" pattern conditions for indicator and strategy development bear_5_0(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bearish 5-0 harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bull_5_0(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bullish 5-0 harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bear_abcd(bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bearish abcd harmonic pattern condition   Parameters:      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bull_abcd(bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bullish abcd harmonic pattern condition   Parameters:      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bear_alt_bat(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bearish alternate bat harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bull_alt_bat(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bullish alternate bat harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bear_bat(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bearish bat harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bull_bat(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bullish bat harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bear_butterfly(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bearish butterfly harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bull_butterfly(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bullish butterfly harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bear_cassiopeia_a(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bearish cassiopeia a harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bull_cassiopeia_a(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bullish cassiopeia a harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bear_cassiopeia_b(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bearish cassiopeia b harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bull_cassiopeia_b(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bullish cassiopeia b harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bear_cassiopeia_c(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bearish cassiopeia c harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bull_cassiopeia_c(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol)   bullish cassiopeia c harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)   Returns: bool bear_crab(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bearish crab harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bull_crab(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bullish crab harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bear_deep_crab(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bearish deep crab harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bull_deep_crab(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bullish deep crab harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bear_cypher(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, xc_low_tol, xc_up_tol)   bearish cypher harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      xc_low_tol (float)      xc_up_tol (float)   Returns: bool bull_cypher(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, xc_low_tol, xc_up_tol)   bullish cypher harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      xc_low_tol (float)      xc_up_tol (float)   Returns: bool bear_gartley(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bearish gartley harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bull_gartley(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, cd_low_tol, cd_up_tol, ad_low_tol, ad_up_tol)   bullish gartley harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      cd_low_tol (float)      cd_up_tol (float)      ad_low_tol (float)      ad_up_tol (float)   Returns: bool bear_shark(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, xc_low_tol, xc_up_tol)   bearish shark harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      xc_low_tol (float)      xc_up_tol (float)   Returns: bool bull_shark(ab_low_tol, ab_up_tol, bc_low_tol, bc_up_tol, xc_low_tol, xc_up_tol)   bullish shark harmonic pattern condition   Parameters:      ab_low_tol (float)      ab_up_tol (float)      bc_low_tol (float)      bc_up_tol (float)      xc_low_tol (float)      xc_up_tol (float)   Returns: bool bear_three_drive(x1_low_tol, a1_low_tol, a1_up_tol, a2_low_tol, a2_up_tol, b2_low_tol, b2_up_tol, b3_low_tol, b3_upt_tol)   bearish three drive harmonic pattern condition   Parameters:      x1_low_tol (float)      a1_low_tol (float)      a1_up_tol (float)      a2_low_tol (float)      a2_up_tol (float)      b2_low_tol (float)      b2_up_tol (float)      b3_low_tol (float)      b3_upt_tol (float)   Returns: bool bull_three_drive(x1_low_tol, a1_low_tol, a1_up_tol, a2_low_tol, a2_up_tol, b2_low_tol, b2_up_tol, b3_low_tol, b3_upt_tol)   bullish three drive harmonic pattern condition   Parameters:      x1_low_tol (float)      a1_low_tol (float)      a1_up_tol (float)      a2_low_tol (float)      a2_up_tol (float)      b2_low_tol (float)      b2_up_tol (float)      b3_low_tol (float)      b3_upt_tol (float)   Returns: bool asc_broadening()   ascending broadening pattern condition   Returns: bool broadening()   broadening pattern condition   Returns: bool desc_broadening()   descending broadening pattern condition   Returns: bool double_bot(low_tol, up_tol)   double bottom pattern condition   Parameters:      low_tol (float)      up_tol (float)   Returns: bool double_top(low_tol, up_tol)   double top pattern condition   Parameters:      low_tol (float)      up_tol (float)   Returns: bool triple_bot(low_tol, up_tol)   triple bottom pattern condition   Parameters:      low_tol (float)      up_tol (float)   Returns: bool triple_top(low_tol, up_tol)   triple top pattern condition   Parameters:      low_tol (float)      up_tol (float)   Returns: bool bear_elliot()   bearish elliot wave pattern condition   Returns: bool bull_elliot()   bullish elliot wave pattern condition   Returns: bool bear_alt_flag(ab_ratio, bc_ratio)   bearish alternate flag pattern condition   Parameters:      ab_ratio (float)      bc_ratio (float)   Returns: bool bull_alt_flag(ab_ratio, bc_ratio)   bullish alternate flag pattern condition   Parameters:      ab_ratio (float)      bc_ratio (float)   Returns: bool bear_flag(ab_ratio, bc_ratio, be_ratio)   bearish flag pattern condition   Parameters:      ab_ratio (float)      bc_ratio (float)      be_ratio (float)   Returns: bool bull_flag(ab_ratio, bc_ratio, be_ratio)   bullish flag pattern condition   Parameters:      ab_ratio (float)      bc_ratio (float)      be_ratio (float)   Returns: bool bear_asc_head_shoulders()   bearish ascending head and shoulders pattern condition   Returns: bool bull_asc_head_shoulders()   bullish ascending head and shoulders pattern condition   Returns: bool bear_desc_head_shoulders()   bearish descending head and shoulders pattern condition   Returns: bool bull_desc_head_shoulders()   bullish descending head and shoulders pattern condition   Returns: bool bear_head_shoulders()   bearish head and shoulders pattern condition   Returns: bool bull_head_shoulders()   bullish head and shoulders pattern condition   Returns: bool bear_pennant(ab_ratio, bc_ratio)   bearish pennant pattern condition   Parameters:      ab_ratio (float)      bc_ratio (float)   Returns: bool bull_pennant(ab_ratio, bc_ratio)   bullish pennant pattern condition   Parameters:      ab_ratio (float)      bc_ratio (float)   Returns: bool asc_wedge()   ascending wedge pattern condition   Returns: bool desc_wedge()   descending wedge pattern condition   Returns: bool wedge()   wedge pattern condition   Returns: bool
Biblioteca Pine Script®
por theEccentricTrader
5
PubLibTrendLibrary "PubLibTrend" trend, multi-part trend, double trend and multi-part double trend conditions for indicator and strategy development rlut()   return line uptrend condition   Returns: bool dt()   downtrend condition   Returns: bool ut()   uptrend condition   Returns: bool rldt()   return line downtrend condition   Returns: bool dtop()   double top condition   Returns: bool dbot()   double bottom condition   Returns: bool rlut_1p()   1-part return line uptrend condition   Returns: bool rlut_2p()   2-part return line uptrend condition   Returns: bool rlut_3p()   3-part return line uptrend condition   Returns: bool rlut_4p()   4-part return line uptrend condition   Returns: bool rlut_5p()   5-part return line uptrend condition   Returns: bool rlut_6p()   6-part return line uptrend condition   Returns: bool rlut_7p()   7-part return line uptrend condition   Returns: bool rlut_8p()   8-part return line uptrend condition   Returns: bool rlut_9p()   9-part return line uptrend condition   Returns: bool rlut_10p()   10-part return line uptrend condition   Returns: bool rlut_11p()   11-part return line uptrend condition   Returns: bool rlut_12p()   12-part return line uptrend condition   Returns: bool rlut_13p()   13-part return line uptrend condition   Returns: bool rlut_14p()   14-part return line uptrend condition   Returns: bool rlut_15p()   15-part return line uptrend condition   Returns: bool rlut_16p()   16-part return line uptrend condition   Returns: bool rlut_17p()   17-part return line uptrend condition   Returns: bool rlut_18p()   18-part return line uptrend condition   Returns: bool rlut_19p()   19-part return line uptrend condition   Returns: bool rlut_20p()   20-part return line uptrend condition   Returns: bool rlut_21p()   21-part return line uptrend condition   Returns: bool rlut_22p()   22-part return line uptrend condition   Returns: bool rlut_23p()   23-part return line uptrend condition   Returns: bool rlut_24p()   24-part return line uptrend condition   Returns: bool rlut_25p()   25-part return line uptrend condition   Returns: bool rlut_26p()   26-part return line uptrend condition   Returns: bool rlut_27p()   27-part return line uptrend condition   Returns: bool rlut_28p()   28-part return line uptrend condition   Returns: bool rlut_29p()   29-part return line uptrend condition   Returns: bool rlut_30p()   30-part return line uptrend condition   Returns: bool dt_1p()   1-part downtrend condition   Returns: bool dt_2p()   2-part downtrend condition   Returns: bool dt_3p()   3-part downtrend condition   Returns: bool dt_4p()   4-part downtrend condition   Returns: bool dt_5p()   5-part downtrend condition   Returns: bool dt_6p()   6-part downtrend condition   Returns: bool dt_7p()   7-part downtrend condition   Returns: bool dt_8p()   8-part downtrend condition   Returns: bool dt_9p()   9-part downtrend condition   Returns: bool dt_10p()   10-part downtrend condition   Returns: bool dt_11p()   11-part downtrend condition   Returns: bool dt_12p()   12-part downtrend condition   Returns: bool dt_13p()   13-part downtrend condition   Returns: bool dt_14p()   14-part downtrend condition   Returns: bool dt_15p()   15-part downtrend condition   Returns: bool dt_16p()   16-part downtrend condition   Returns: bool dt_17p()   17-part downtrend condition   Returns: bool dt_18p()   18-part downtrend condition   Returns: bool dt_19p()   19-part downtrend condition   Returns: bool dt_20p()   20-part downtrend condition   Returns: bool dt_21p()   21-part downtrend condition   Returns: bool dt_22p()   22-part downtrend condition   Returns: bool dt_23p()   23-part downtrend condition   Returns: bool dt_24p()   24-part downtrend condition   Returns: bool dt_25p()   25-part downtrend condition   Returns: bool dt_26p()   26-part downtrend condition   Returns: bool dt_27p()   27-part downtrend condition   Returns: bool dt_28p()   28-part downtrend condition   Returns: bool dt_29p()   29-part downtrend condition   Returns: bool dt_30p()   30-part downtrend condition   Returns: bool ut_1p()   1-part uptrend condition   Returns: bool ut_2p()   2-part uptrend condition   Returns: bool ut_3p()   3-part uptrend condition   Returns: bool ut_4p()   4-part uptrend condition   Returns: bool ut_5p()   5-part uptrend condition   Returns: bool ut_6p()   6-part uptrend condition   Returns: bool ut_7p()   7-part uptrend condition   Returns: bool ut_8p()   8-part uptrend condition   Returns: bool ut_9p()   9-part uptrend condition   Returns: bool ut_10p()   10-part uptrend condition   Returns: bool ut_11p()   11-part uptrend condition   Returns: bool ut_12p()   12-part uptrend condition   Returns: bool ut_13p()   13-part uptrend condition   Returns: bool ut_14p()   14-part uptrend condition   Returns: bool ut_15p()   15-part uptrend condition   Returns: bool ut_16p()   16-part uptrend condition   Returns: bool ut_17p()   17-part uptrend condition   Returns: bool ut_18p()   18-part uptrend condition   Returns: bool ut_19p()   19-part uptrend condition   Returns: bool ut_20p()   20-part uptrend condition   Returns: bool ut_21p()   21-part uptrend condition   Returns: bool ut_22p()   22-part uptrend condition   Returns: bool ut_23p()   23-part uptrend condition   Returns: bool ut_24p()   24-part uptrend condition   Returns: bool ut_25p()   25-part uptrend condition   Returns: bool ut_26p()   26-part uptrend condition   Returns: bool ut_27p()   27-part uptrend condition   Returns: bool ut_28p()   28-part uptrend condition   Returns: bool ut_29p()   29-part uptrend condition   Returns: bool ut_30p()   30-part uptrend condition   Returns: bool rldt_1p()   1-part return line downtrend condition   Returns: bool rldt_2p()   2-part return line downtrend condition   Returns: bool rldt_3p()   3-part return line downtrend condition   Returns: bool rldt_4p()   4-part return line downtrend condition   Returns: bool rldt_5p()   5-part return line downtrend condition   Returns: bool rldt_6p()   6-part return line downtrend condition   Returns: bool rldt_7p()   7-part return line downtrend condition   Returns: bool rldt_8p()   8-part return line downtrend condition   Returns: bool rldt_9p()   9-part return line downtrend condition   Returns: bool rldt_10p()   10-part return line downtrend condition   Returns: bool rldt_11p()   11-part return line downtrend condition   Returns: bool rldt_12p()   12-part return line downtrend condition   Returns: bool rldt_13p()   13-part return line downtrend condition   Returns: bool rldt_14p()   14-part return line downtrend condition   Returns: bool rldt_15p()   15-part return line downtrend condition   Returns: bool rldt_16p()   16-part return line downtrend condition   Returns: bool rldt_17p()   17-part return line downtrend condition   Returns: bool rldt_18p()   18-part return line downtrend condition   Returns: bool rldt_19p()   19-part return line downtrend condition   Returns: bool rldt_20p()   20-part return line downtrend condition   Returns: bool rldt_21p()   21-part return line downtrend condition   Returns: bool rldt_22p()   22-part return line downtrend condition   Returns: bool rldt_23p()   23-part return line downtrend condition   Returns: bool rldt_24p()   24-part return line downtrend condition   Returns: bool rldt_25p()   25-part return line downtrend condition   Returns: bool rldt_26p()   26-part return line downtrend condition   Returns: bool rldt_27p()   27-part return line downtrend condition   Returns: bool rldt_28p()   28-part return line downtrend condition   Returns: bool rldt_29p()   29-part return line downtrend condition   Returns: bool rldt_30p()   30-part return line downtrend condition   Returns: bool dut()   double uptrend condition   Returns: bool ddt()   double downtrend condition   Returns: bool dut_1p()   1-part double uptrend condition   Returns: bool dut_2p()   2-part double uptrend condition   Returns: bool dut_3p()   3-part double uptrend condition   Returns: bool dut_4p()   4-part double uptrend condition   Returns: bool dut_5p()   5-part double uptrend condition   Returns: bool dut_6p()   6-part double uptrend condition   Returns: bool dut_7p()   7-part double uptrend condition   Returns: bool dut_8p()   8-part double uptrend condition   Returns: bool dut_9p()   9-part double uptrend condition   Returns: bool dut_10p()   10-part double uptrend condition   Returns: bool dut_11p()   11-part double uptrend condition   Returns: bool dut_12p()   12-part double uptrend condition   Returns: bool dut_13p()   13-part double uptrend condition   Returns: bool dut_14p()   14-part double uptrend condition   Returns: bool dut_15p()   15-part double uptrend condition   Returns: bool dut_16p()   16-part double uptrend condition   Returns: bool dut_17p()   17-part double uptrend condition   Returns: bool dut_18p()   18-part double uptrend condition   Returns: bool dut_19p()   19-part double uptrend condition   Returns: bool dut_20p()   20-part double uptrend condition   Returns: bool dut_21p()   21-part double uptrend condition   Returns: bool dut_22p()   22-part double uptrend condition   Returns: bool dut_23p()   23-part double uptrend condition   Returns: bool dut_24p()   24-part double uptrend condition   Returns: bool dut_25p()   25-part double uptrend condition   Returns: bool dut_26p()   26-part double uptrend condition   Returns: bool dut_27p()   27-part double uptrend condition   Returns: bool dut_28p()   28-part double uptrend condition   Returns: bool dut_29p()   29-part double uptrend condition   Returns: bool dut_30p()   30-part double uptrend condition   Returns: bool ddt_1p()   1-part double downtrend condition   Returns: bool ddt_2p()   2-part double downtrend condition   Returns: bool ddt_3p()   3-part double downtrend condition   Returns: bool ddt_4p()   4-part double downtrend condition   Returns: bool ddt_5p()   5-part double downtrend condition   Returns: bool ddt_6p()   6-part double downtrend condition   Returns: bool ddt_7p()   7-part double downtrend condition   Returns: bool ddt_8p()   8-part double downtrend condition   Returns: bool ddt_9p()   9-part double downtrend condition   Returns: bool ddt_10p()   10-part double downtrend condition   Returns: bool ddt_11p()   11-part double downtrend condition   Returns: bool ddt_12p()   12-part double downtrend condition   Returns: bool ddt_13p()   13-part double downtrend condition   Returns: bool ddt_14p()   14-part double downtrend condition   Returns: bool ddt_15p()   15-part double downtrend condition   Returns: bool ddt_16p()   16-part double downtrend condition   Returns: bool ddt_17p()   17-part double downtrend condition   Returns: bool ddt_18p()   18-part double downtrend condition   Returns: bool ddt_19p()   19-part double downtrend condition   Returns: bool ddt_20p()   20-part double downtrend condition   Returns: bool ddt_21p()   21-part double downtrend condition   Returns: bool ddt_22p()   22-part double downtrend condition   Returns: bool ddt_23p()   23-part double downtrend condition   Returns: bool ddt_24p()   24-part double downtrend condition   Returns: bool ddt_25p()   25-part double downtrend condition   Returns: bool ddt_26p()   26-part double downtrend condition   Returns: bool ddt_27p()   27-part double downtrend condition   Returns: bool ddt_28p()   28-part double downtrend condition   Returns: bool ddt_29p()   29-part double downtrend condition   Returns: bool ddt_30p()   30-part double downtrend condition   Returns: bool
Biblioteca Pine Script®
por theEccentricTrader
2
PubLibSwingLibrary "PubLibSwing" swing high and swing low conditions, prices, bar indices and range ratios for indicator and strategy development sh()   swing high condition   Returns: bool sl()   swing low condition   Returns: bool shbi(occ)   swing high bar index, condition occurrence n   Parameters:      occ (simple int)   Returns: int slbi(occ)   swing low bar index, condition occurrence n   Parameters:      occ (simple int)   Returns: int shcp(occ)   swing high close price, condition occurrence n   Parameters:      occ (simple int)   Returns: float slcp(occ)   swing low close price, condition occurrence n   Parameters:      occ (simple int)   Returns: float shp(occ)   swing high price, condition occurrence n   Parameters:      occ (simple int)   Returns: float slp(occ)   swing low price, condition occurrence n   Parameters:      occ (simple int)   Returns: float shpbi(occ)   swing high price bar index, condition occurrence n   Parameters:      occ (simple int)   Returns: int slpbi(occ)   swing low price bar index, condition occurrence n   Parameters:      occ (simple int)   Returns: int shrr(occ)   swing high range ratio, condition occurrence n   Parameters:      occ (simple int)   Returns: float slrr(occ)   swing low range ratio, condition occurrence n   Parameters:      occ (simple int)   Returns: float
Biblioteca Pine Script®
por theEccentricTrader
2
PubLibCandleTrendLibrary "PubLibCandleTrend" candle trend, multi-part candle trend, multi-part green/red candle trend, double candle trend and multi-part double candle trend conditions for indicator and strategy development chh()   candle higher high condition   Returns: bool chl()   candle higher low condition   Returns: bool clh()   candle lower high condition   Returns: bool cll()   candle lower low condition   Returns: bool cdt()   candle double top condition   Returns: bool cdb()   candle double bottom condition   Returns: bool gc()   green candle condition   Returns: bool gchh()   green candle higher high condition   Returns: bool gchl()   green candle higher low condition   Returns: bool gclh()   green candle lower high condition   Returns: bool gcll()   green candle lower low condition   Returns: bool gcdt()   green candle double top condition   Returns: bool gcdb()   green candle double bottom condition   Returns: bool rc()   red candle condition   Returns: bool rchh()   red candle higher high condition   Returns: bool rchl()   red candle higher low condition   Returns: bool rclh()   red candle lower high condition   Returns: bool rcll()   red candle lower low condition   Returns: bool rcdt()   red candle double top condition   Returns: bool rcdb()   red candle double bottom condition   Returns: bool chh_1p()   1-part candle higher high condition   Returns: bool chh_2p()   2-part candle higher high condition   Returns: bool chh_3p()   3-part candle higher high condition   Returns: bool chh_4p()   4-part candle higher high condition   Returns: bool chh_5p()   5-part candle higher high condition   Returns: bool chh_6p()   6-part candle higher high condition   Returns: bool chh_7p()   7-part candle higher high condition   Returns: bool chh_8p()   8-part candle higher high condition   Returns: bool chh_9p()   9-part candle higher high condition   Returns: bool chh_10p()   10-part candle higher high condition   Returns: bool chh_11p()   11-part candle higher high condition   Returns: bool chh_12p()   12-part candle higher high condition   Returns: bool chh_13p()   13-part candle higher high condition   Returns: bool chh_14p()   14-part candle higher high condition   Returns: bool chh_15p()   15-part candle higher high condition   Returns: bool chh_16p()   16-part candle higher high condition   Returns: bool chh_17p()   17-part candle higher high condition   Returns: bool chh_18p()   18-part candle higher high condition   Returns: bool chh_19p()   19-part candle higher high condition   Returns: bool chh_20p()   20-part candle higher high condition   Returns: bool chh_21p()   21-part candle higher high condition   Returns: bool chh_22p()   22-part candle higher high condition   Returns: bool chh_23p()   23-part candle higher high condition   Returns: bool chh_24p()   24-part candle higher high condition   Returns: bool chh_25p()   25-part candle higher high condition   Returns: bool chh_26p()   26-part candle higher high condition   Returns: bool chh_27p()   27-part candle higher high condition   Returns: bool chh_28p()   28-part candle higher high condition   Returns: bool chh_29p()   29-part candle higher high condition   Returns: bool chh_30p()   30-part candle higher high condition   Returns: bool chl_1p()   1-part candle higher low condition   Returns: bool chl_2p()   2-part candle higher low condition   Returns: bool chl_3p()   3-part candle higher low condition   Returns: bool chl_4p()   4-part candle higher low condition   Returns: bool chl_5p()   5-part candle higher low condition   Returns: bool chl_6p()   6-part candle higher low condition   Returns: bool chl_7p()   7-part candle higher low condition   Returns: bool chl_8p()   8-part candle higher low condition   Returns: bool chl_9p()   9-part candle higher low condition   Returns: bool chl_10p()   10-part candle higher low condition   Returns: bool chl_11p()   11-part candle higher low condition   Returns: bool chl_12p()   12-part candle higher low condition   Returns: bool chl_13p()   13-part candle higher low condition   Returns: bool chl_14p()   14-part candle higher low condition   Returns: bool chl_15p()   15-part candle higher low condition   Returns: bool chl_16p()   16-part candle higher low condition   Returns: bool chl_17p()   17-part candle higher low condition   Returns: bool chl_18p()   18-part candle higher low condition   Returns: bool chl_19p()   19-part candle higher low condition   Returns: bool chl_20p()   20-part candle higher low condition   Returns: bool chl_21p()   21-part candle higher low condition   Returns: bool chl_22p()   22-part candle higher low condition   Returns: bool chl_23p()   23-part candle higher low condition   Returns: bool chl_24p()   24-part candle higher low condition   Returns: bool chl_25p()   25-part candle higher low condition   Returns: bool chl_26p()   26-part candle higher low condition   Returns: bool chl_27p()   27-part candle higher low condition   Returns: bool chl_28p()   28-part candle higher low condition   Returns: bool chl_29p()   29-part candle higher low condition   Returns: bool chl_30p()   30-part candle higher low condition   Returns: bool clh_1p()   1-part candle lower high condition   Returns: bool clh_2p()   2-part candle lower high condition   Returns: bool clh_3p()   3-part candle lower high condition   Returns: bool clh_4p()   4-part candle lower high condition   Returns: bool clh_5p()   5-part candle lower high condition   Returns: bool clh_6p()   6-part candle lower high condition   Returns: bool clh_7p()   7-part candle lower high condition   Returns: bool clh_8p()   8-part candle lower high condition   Returns: bool clh_9p()   9-part candle lower high condition   Returns: bool clh_10p()   10-part candle lower high condition   Returns: bool clh_11p()   11-part candle lower high condition   Returns: bool clh_12p()   12-part candle lower high condition   Returns: bool clh_13p()   13-part candle lower high condition   Returns: bool clh_14p()   14-part candle lower high condition   Returns: bool clh_15p()   15-part candle lower high condition   Returns: bool clh_16p()   16-part candle lower high condition   Returns: bool clh_17p()   17-part candle lower high condition   Returns: bool clh_18p()   18-part candle lower high condition   Returns: bool clh_19p()   19-part candle lower high condition   Returns: bool clh_20p()   20-part candle lower high condition   Returns: bool clh_21p()   21-part candle lower high condition   Returns: bool clh_22p()   22-part candle lower high condition   Returns: bool clh_23p()   23-part candle lower high condition   Returns: bool clh_24p()   24-part candle lower high condition   Returns: bool clh_25p()   25-part candle lower high condition   Returns: bool clh_26p()   26-part candle lower high condition   Returns: bool clh_27p()   27-part candle lower high condition   Returns: bool clh_28p()   28-part candle lower high condition   Returns: bool clh_29p()   29-part candle lower high condition   Returns: bool clh_30p()   30-part candle lower high condition   Returns: bool cll_1p()   1-part candle lower low condition   Returns: bool cll_2p()   2-part candle lower low condition   Returns: bool cll_3p()   3-part candle lower low condition   Returns: bool cll_4p()   4-part candle lower low condition   Returns: bool cll_5p()   5-part candle lower low condition   Returns: bool cll_6p()   6-part candle lower low condition   Returns: bool cll_7p()   7-part candle lower low condition   Returns: bool cll_8p()   8-part candle lower low condition   Returns: bool cll_9p()   9-part candle lower low condition   Returns: bool cll_10p()   10-part candle lower low condition   Returns: bool cll_11p()   11-part candle lower low condition   Returns: bool cll_12p()   12-part candle lower low condition   Returns: bool cll_13p()   13-part candle lower low condition   Returns: bool cll_14p()   14-part candle lower low condition   Returns: bool cll_15p()   15-part candle lower low condition   Returns: bool cll_16p()   16-part candle lower low condition   Returns: bool cll_17p()   17-part candle lower low condition   Returns: bool cll_18p()   18-part candle lower low condition   Returns: bool cll_19p()   19-part candle lower low condition   Returns: bool cll_20p()   20-part candle lower low condition   Returns: bool cll_21p()   21-part candle lower low condition   Returns: bool cll_22p()   22-part candle lower low condition   Returns: bool cll_23p()   23-part candle lower low condition   Returns: bool cll_24p()   24-part candle lower low condition   Returns: bool cll_25p()   25-part candle lower low condition   Returns: bool cll_26p()   26-part candle lower low condition   Returns: bool cll_27p()   27-part candle lower low condition   Returns: bool cll_28p()   28-part candle lower low condition   Returns: bool cll_29p()   29-part candle lower low condition   Returns: bool cll_30p()   30-part candle lower low condition   Returns: bool gc_1p()   1-part green candle condition   Returns: bool gc_2p()   2-part green candle condition   Returns: bool gc_3p()   3-part green candle condition   Returns: bool gc_4p()   4-part green candle condition   Returns: bool gc_5p()   5-part green candle condition   Returns: bool gc_6p()   6-part green candle condition   Returns: bool gc_7p()   7-part green candle condition   Returns: bool gc_8p()   8-part green candle condition   Returns: bool gc_9p()   9-part green candle condition   Returns: bool gc_10p()   10-part green candle condition   Returns: bool gc_11p()   11-part green candle condition   Returns: bool gc_12p()   12-part green candle condition   Returns: bool gc_13p()   13-part green candle condition   Returns: bool gc_14p()   14-part green candle condition   Returns: bool gc_15p()   15-part green candle condition   Returns: bool gc_16p()   16-part green candle condition   Returns: bool gc_17p()   17-part green candle condition   Returns: bool gc_18p()   18-part green candle condition   Returns: bool gc_19p()   19-part green candle condition   Returns: bool gc_20p()   20-part green candle condition   Returns: bool gc_21p()   21-part green candle condition   Returns: bool gc_22p()   22-part green candle condition   Returns: bool gc_23p()   23-part green candle condition   Returns: bool gc_24p()   24-part green candle condition   Returns: bool gc_25p()   25-part green candle condition   Returns: bool gc_26p()   26-part green candle condition   Returns: bool gc_27p()   27-part green candle condition   Returns: bool gc_28p()   28-part green candle condition   Returns: bool gc_29p()   29-part green candle condition   Returns: bool gc_30p()   30-part green candle condition   Returns: bool rc_1p()   1-part red candle condition   Returns: bool rc_2p()   2-part red candle condition   Returns: bool rc_3p()   3-part red candle condition   Returns: bool rc_4p()   4-part red candle condition   Returns: bool rc_5p()   5-part red candle condition   Returns: bool rc_6p()   6-part red candle condition   Returns: bool rc_7p()   7-part red candle condition   Returns: bool rc_8p()   8-part red candle condition   Returns: bool rc_9p()   9-part red candle condition   Returns: bool rc_10p()   10-part red candle condition   Returns: bool rc_11p()   11-part red candle condition   Returns: bool rc_12p()   12-part red candle condition   Returns: bool rc_13p()   13-part red candle condition   Returns: bool rc_14p()   14-part red candle condition   Returns: bool rc_15p()   15-part red candle condition   Returns: bool rc_16p()   16-part red candle condition   Returns: bool rc_17p()   17-part red candle condition   Returns: bool rc_18p()   18-part red candle condition   Returns: bool rc_19p()   19-part red candle condition   Returns: bool rc_20p()   20-part red candle condition   Returns: bool rc_21p()   21-part red candle condition   Returns: bool rc_22p()   22-part red candle condition   Returns: bool rc_23p()   23-part red candle condition   Returns: bool rc_24p()   24-part red candle condition   Returns: bool rc_25p()   25-part red candle condition   Returns: bool rc_26p()   26-part red candle condition   Returns: bool rc_27p()   27-part red candle condition   Returns: bool rc_28p()   28-part red candle condition   Returns: bool rc_29p()   29-part red candle condition   Returns: bool rc_30p()   30-part red candle condition   Returns: bool cdut()   candle double uptrend condition   Returns: bool cddt()   candle double downtrend condition   Returns: bool cdut_1p()   1-part candle double uptrend condition   Returns: bool cdut_2p()   2-part candle double uptrend condition   Returns: bool cdut_3p()   3-part candle double uptrend condition   Returns: bool cdut_4p()   4-part candle double uptrend condition   Returns: bool cdut_5p()   5-part candle double uptrend condition   Returns: bool cdut_6p()   6-part candle double uptrend condition   Returns: bool cdut_7p()   7-part candle double uptrend condition   Returns: bool cdut_8p()   8-part candle double uptrend condition   Returns: bool cdut_9p()   9-part candle double uptrend condition   Returns: bool cdut_10p()   10-part candle double uptrend condition   Returns: bool cdut_11p()   11-part candle double uptrend condition   Returns: bool cdut_12p()   12-part candle double uptrend condition   Returns: bool cdut_13p()   13-part candle double uptrend condition   Returns: bool cdut_14p()   14-part candle double uptrend condition   Returns: bool cdut_15p()   15-part candle double uptrend condition   Returns: bool cdut_16p()   16-part candle double uptrend condition   Returns: bool cdut_17p()   17-part candle double uptrend condition   Returns: bool cdut_18p()   18-part candle double uptrend condition   Returns: bool cdut_19p()   19-part candle double uptrend condition   Returns: bool cdut_20p()   20-part candle double uptrend condition   Returns: bool cdut_21p()   21-part candle double uptrend condition   Returns: bool cdut_22p()   22-part candle double uptrend condition   Returns: bool cdut_23p()   23-part candle double uptrend condition   Returns: bool cdut_24p()   24-part candle double uptrend condition   Returns: bool cdut_25p()   25-part candle double uptrend condition   Returns: bool cdut_26p()   26-part candle double uptrend condition   Returns: bool cdut_27p()   27-part candle double uptrend condition   Returns: bool cdut_28p()   28-part candle double uptrend condition   Returns: bool cdut_29p()   29-part candle double uptrend condition   Returns: bool cdut_30p()   30-part candle double uptrend condition   Returns: bool cddt_1p()   1-part candle double downtrend condition   Returns: bool cddt_2p()   2-part candle double downtrend condition   Returns: bool cddt_3p()   3-part candle double downtrend condition   Returns: bool cddt_4p()   4-part candle double downtrend condition   Returns: bool cddt_5p()   5-part candle double downtrend condition   Returns: bool cddt_6p()   6-part candle double downtrend condition   Returns: bool cddt_7p()   7-part candle double downtrend condition   Returns: bool cddt_8p()   8-part candle double downtrend condition   Returns: bool cddt_9p()   9-part candle double downtrend condition   Returns: bool cddt_10p()   10-part candle double downtrend condition   Returns: bool cddt_11p()   11-part candle double downtrend condition   Returns: bool cddt_12p()   12-part candle double downtrend condition   Returns: bool cddt_13p()   13-part candle double downtrend condition   Returns: bool cddt_14p()   14-part candle double downtrend condition   Returns: bool cddt_15p()   15-part candle double downtrend condition   Returns: bool cddt_16p()   16-part candle double downtrend condition   Returns: bool cddt_17p()   17-part candle double downtrend condition   Returns: bool cddt_18p()   18-part candle double downtrend condition   Returns: bool cddt_19p()   19-part candle double downtrend condition   Returns: bool cddt_20p()   20-part candle double downtrend condition   Returns: bool cddt_21p()   21-part candle double downtrend condition   Returns: bool cddt_22p()   22-part candle double downtrend condition   Returns: bool cddt_23p()   23-part candle double downtrend condition   Returns: bool cddt_24p()   24-part candle double downtrend condition   Returns: bool cddt_25p()   25-part candle double downtrend condition   Returns: bool cddt_26p()   26-part candle double downtrend condition   Returns: bool cddt_27p()   27-part candle double downtrend condition   Returns: bool cddt_28p()   28-part candle double downtrend condition   Returns: bool cddt_29p()   29-part candle double downtrend condition   Returns: bool cddt_30p()   30-part candle double downtrend condition   Returns: bool
Biblioteca Pine Script®
por theEccentricTrader
2
1000SATS and ORDI Market Cap RatioSure! Here is a detailed description and usage guide for your TradingView indicator: ### Indicator Description **Title**: 1000SATS/ORDI Market Cap Ratio **Description**: The "1000SATS/ORDI Market Cap Ratio" indicator calculates and visualizes the market capitalization ratio between 1000SATS and ORDI. This indicator allows traders and investors to analyze the relative market strength and valuation trends of 1000SATS compared to ORDI over time. By tracking this ratio, users can gain insights into market dynamics and potential trading opportunities between these two assets. ### Indicator Usage **Purpose**: - To compare the market capitalizations of 1000SATS and ORDI. - To identify potential undervaluation or overvaluation of 1000SATS relative to ORDI. - To assist in making informed trading and investment decisions based on market cap trends. **How to Use**: 1. **Add the Indicator to Your Chart**: - Open TradingView and navigate to your chart. - Click on the "Indicators" button at the top of the chart. - Select "Pine Editor" and paste the provided script. - Click "Add to Chart" to apply the indicator. 2. **Interpret the Ratio**: - The indicator will plot a line representing the ratio of the market capitalization of 1000SATS to ORDI. - A rising ratio indicates that the market cap of 1000SATS is increasing relative to ORDI, suggesting stronger market performance or higher valuation of 1000SATS. - A falling ratio indicates that the market cap of 1000SATS is decreasing relative to ORDI, suggesting weaker market performance or lower valuation of 1000SATS. 3. **Analyze Trends**: - Use the indicator to spot trends and potential reversal points in the market cap ratio. - Combine the ratio analysis with other technical indicators and chart patterns to enhance your trading strategy. 4. **Set Alerts**: - Set custom alerts on the ratio to notify you of significant changes or specific thresholds being reached, enabling timely decision-making. **Example**: - If the ratio is consistently rising, it may indicate a good opportunity to consider 1000SATS as a stronger investment relative to ORDI. - Conversely, if the ratio is falling, it may be a signal to reevaluate the strength of 1000SATS compared to ORDI. **Note**: Always conduct thorough analysis and consider other market factors before making trading decisions based on this indicator. ### Script ```pinescript //@version=4 study("1000SATS and ORDI Market Cap Ratio", shorttitle="1000SATS/ORDI Ratio", overlay=true) // Define the circulating supply for ORDI and 1000SATS ORDI_supply = 21000000 // Circulating supply of ORDI SATS_1000_supply = 2100000000000 // Circulating supply of 1000SATS // Fetch the price data for ORDI ordi_price = security("BINANCE:ORDIUSDT", timeframe.period, close) // Fetch the price data for 1000SATS sats_1000_price = security("BINANCE:1000SATSUSDT", timeframe.period, close) // Calculate the market capitalizations ordi_market_cap = ordi_price * ORDI_supply sats_1000_market_cap = sats_1000_price * SATS_1000_supply // Calculate the market cap ratio ratio = sats_1000_market_cap / ordi_market_cap // Plot the ratio plot(ratio, title="1000SATS/ORDI Market Cap Ratio", color=color.blue, linewidth=2) ``` This description and usage guide should help users understand the purpose and functionality of your indicator, as well as how to effectively apply it in their trading activities on TradingView.
Indicador Pine Script®
por Mingdwings
Ethereum ETF Tracker (EET)Get all the information you need about all the different Ethereum ETF. With the Ethereum ETF Tracker, you can observe all possible Ethereum ETF data: ETF name. Ticker. Price. Volume. Share of total ETF volume. Fees. Exchange. Custodian. At the bottom of the table, you'll find the ETHE Premium (and ETH per Share), and day's total volume. In addition, you can see the volume for the different Exchanges, as well as for the different Custodians. If you don't want to display these lines to save space, you can uncheck "Show Additional Data" in the indicator settings. The Idea The goal is to provide the community with a tool for tracking all Ethereum ETF data in a synthesized way, directly in your TradingView chart. How to Use Simply read the information in the table. You can hover above the Fees and Exchanges cells for more details. The table takes space on the chart, you can remove the extra lines by unchecking "Show Additional Data" in the indicator settings or reduce text size by changing the "Table Text Size" parameter. Aggregate volume can be displayed directly on the graph (this volume can be displayed on any asset, such as Ethereum itself). The display can be disabled in the settings.
Indicador Pine Script®
por Blockunity
Coinbase vs Binance Spot Premium for All coins🔶 Coinbase Premium This indicator allows you to track the premiums for various coins listed on Coinbase relative to Binance. The buying strength of US markets tend to be a good indicator for up trending markets. The moving average crosses shown as ribbons can be used to time entries and exits 🔶 Available Pairs Currently, the indicator includes 31 coins as listed below: BTC, ETH, SOL, BONK, DOGE, XRP, SHIB, ONDO, AVAX, LINK, ENS, LTC, RNDR, INJ, BCH, ARB, OP, ADA, DOT, TIA, ICP, MATIC, LDO, NEAR, CVX, AERO, ORCA, SEI, STX, MKR, SUI 🔶 Key Features Select Coin: You can select any of the 31 supported coins to track its premium. Show Ribbons: Option to enable or disable the display of ribbon trend lines between two moving averages. Adjust MA Lengths: Customizable lengths for the short and long moving averages to fine-tune the trend analysis. 🔶 Calculations The premium is a simple nominal difference between the Coinbase price and the Binance price. eg) Coinbase ETHUSD - Binance ETHUSDT = Premium 🔶 Disclaimer This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and due diligence before making any trading decisions. Past performance is not necessarily indicative of future results.
Indicador Pine Script®
por hansolar21
2
[SGM Markov Chain]Introduction A Markov chain is a mathematical model that describes a system evolving over time among a finite number of states. This model is based on the assumption that the future state of the system depends only on the current state and not on previous states, the so-called Markov property. In the context of financial markets, Markov chains can be used to model transitions between different market conditions, for example, the probability of a price going up after going up, or going down after going down. Script Description This script uses a Markov chain to calculate closing price transition probabilities across the entire accessible chart. It displays the probabilities of the following transitions: - Up after Up (HH): Probability that the price rises after going up. - Down after Down (BB): Probability that the price will go down after going down. - Up after Down (HB): Probability that the price goes up after going down. - Down after Up (BH): Probability that the price will go down after going up. Features - Color customization: Choose colors for each transition type. - Table Position: Select the position of the probability display table (top/left, top/right, bottom/left, bottom/right).
Indicador Pine Script®
por Sigaud
1
Position Size CalculatorThe Position Size Calculator (PSC) is a comprehensive tool designed to assist traders in managing their trades risk by accurately calculating the optimal position size based on account settings, trade levels, and risk management parameters. This indicator helps traders make informed decisions by providing critical information about potential profit and loss , risk-reward ratio (RRR) , and position size (PS) . █ Key Features • Customizable Account Settings: Define your account size , currency , risk tolerance , and commission structure to personalize the calculations. • Real-Time Trade Levels: Easily input your entry , stop loss , and take profit prices directly on the chart for immediate calculations. • Visual Indicators: Clearly see your entry, stop loss, and take profit levels with customizable colors and labels. • Comprehensive Position Information: View detailed information about your position, including potential profit and loss , risk-reward ratio , and position size . • Currency Conversion: Automatically convert prices to your account currency, making it easy to manage trades in different markets. • Hide Metrics : Choose which metrics to display to avoid emotional influence on your trading decisions (e.g., hiding PnL). █ Conclusion The Position Size Calculator is an essential tool for traders looking to optimize their trading strategies and manage risk effectively . By providing detailed calculations and visual indicators, this tool helps you make informed decisions, improving your overall trading performance. █ Important • Ensure that your stop loss and take profit levels are correctly set relative to your entry price to avoid errors. • The default commission setting considers both entry and exit commissions. Adjust accordingly if only one commission is applicable. Consider using this tool to manage every trade risk correctly and prevent significant drawdowns. Hope you like it. Happy trading!
Indicador Pine Script®
por ActiveQuants
14
[SGM Return Distribution]Code Description This Pine Script™ is designed to analyze the distribution of historical returns of a financial asset and project future confidence levels. It uses statistical techniques to estimate the probability of winning and losing as well as displaying confidence bands and distribution statistics. User Entries Length (252): The number of days used to calculate statistics. Offset (20): Offset used to project future values. Projection Days (10): Number of days projected into the future. Smoothing Confidence Levels (10): Smoothing confidence bands. Display Settings Plot Distribution: Shows the distribution of returns. Show Probabilities: Shows winning and losing probabilities. Show Distribution Stats: Shows distribution statistics. Show Confidence Bands: Shows confidence bands. Show Confidence Lines: Shows confidence lines. Calculations and Features Distribution of Yields: Calculates logarithmic returns and their statistics (average, volatility, skewness, kurtosis). Projects the average and volatility over the projected number of days. Displays the distribution of returns as a histogram. Confidence Interval: Uses the inv_norm function to calculate Z scores for different confidence levels. Calculates the upper and lower bounds of the confidence bands. Probability Display: Calculates and displays win and loss probabilities based on the distribution of returns. Statistics Display: Shows key statistics such as mean, volatility, skewness and kurtosis. Trust Bands and Lines: Shows confidence bands and lines based on calculated confidence levels. Mathematical Assumptions Used Logarithmic Returns: Returns are calculated using the logarithm of prices, which is common for financial time series because it makes returns independent of price level. Normal Distribution for Confidence Bands: Confidence interval calculations are based on the assumption that returns follow a normal distribution. Average and Volatility Projection: Average returns and volatility are projected over a future period assuming they remain constant. Skewness and Kurtosis: Although these measures are calculated for understanding the distribution of returns, they are not used in box projections but can provide additional information about the distribution of historical returns. Use in Trading Risk Estimation: Confidence bands can help estimate likely future price levels, which is crucial for determining strike levels and risk management. Risk Management: Use confidence bands to set stop-loss and take-profit levels. Probability Analysis: Win and loss probabilities can help assess a position's likelihood of success. Potential Problems Assumption of Normality for Confidence Bands: Financial returns do not always follow a normal distribution, especially in the presence of extreme events (fat tails). Stationarity: Assuming that return statistics (average, volatility) remain constant over time can be erroneous in volatile market periods. Limited Historical Data: Using a limited history (252 days) may not capture all possible behaviors of the asset. Input Parameters: Results can be sensitive to the input parameters chosen (length, offset, etc.).
Indicador Pine Script®
por Sigaud
2
Harmonic Patterns Library [TradingFinder]🔵 Introduction Harmonic patterns blend geometric shapes with Fibonacci numbers, making these numbers fundamental to understanding the patterns. One person who has done a lot of research on harmonic patterns is Scott Carney.Scott Carney's research on harmonic patterns in technical analysis focuses on precise price structures based on Fibonacci ratios to identify market reversals. Key patterns include the Gartley, Bat, Butterfly, and Crab, each with specific alignment criteria. These patterns help traders anticipate potential market turning points and make informed trading decisions, enhancing the predictability of technical analysis. 🟣 Understanding 5-Point Harmonic Patterns In the current library version, you can easily draw and customize most XABCD patterns. These patterns often form M or W shapes, or a combination of both. By calculating the Fibonacci ratios between key points, you can estimate potential price movements. All five-point patterns share a similar structure, differing only in line lengths and Fibonacci ratios. Learning one pattern simplifies understanding others. 🟣 Exploring the Gartley Pattern The Gartley pattern appears in both bullish (M shape) and bearish (W shape) forms. In the bullish Gartley, point X is below point D, and point A surpasses point C. Point D marks the start of a strong upward trend, making it an optimal point to place a buy order. The bearish Gartley mirrors the bullish pattern with inverted Fibonacci ratios. In this scenario, point D indicates the start of a significant price drop. Traders can place sell orders at this point and buy at lower prices for profit in two-way markets. 🟣 Analyzing the Butterfly Pattern The Butterfly pattern also manifests in bullish (M shape) and bearish (W shape) forms. It resembles the Gartley pattern but with point D lower than point X in the bullish version. The Butterfly pattern involves deeper price corrections than the Gartley, leading to more significant price fluctuations. Point D in the bullish Butterfly indicates the beginning of a sharp price rise, making it an entry point for buy orders. The bearish Butterfly has inverted Fibonacci ratios, with point D marking the start of a sharp price decline, ideal for sell orders followed by buying at lower prices in two-way markets. 🟣 Insights into the Bat Pattern The Bat pattern, appearing in bullish (M shape) and bearish (W shape) forms, is one of the most precise harmonic patterns. It closely resembles the Butterfly and Gartley patterns, differing mainly in Fibonacci levels. The bearish Bat pattern shares the Fibonacci ratios with the bullish Bat, with an inverted structure. Point D in the bearish Bat marks the start of a significant price drop, suitable for sell orders followed by buying at lower prices for profit. 🟣 The Crab Pattern Explained The Crab pattern, found in both bullish (M shape) and bearish (W shape) forms, is highly favored by analysts. Discovered in 2000, the Crab pattern features a larger final wave correction compared to other harmonic patterns. The bearish Crab shares Fibonacci ratios with the bullish version but in an inverted form. Point D in the bearish Crab signifies the start of a sharp price decline, making it an ideal point for sell orders followed by buying at lower prices for profitable trades. 🟣 Understanding the Shark Pattern The Shark pattern appears in bullish (M shape) and bearish (W shape) forms. It differs from previous patterns as point C in the bullish Shark surpasses point A, with unique level measurements. The bearish Shark pattern mirrors the Fibonacci ratios of the bullish Shark but is inverted. Point D in the bearish Shark indicates the start of a sharp price drop, ideal for placing sell orders and buying at lower prices to capitalize on the pattern. 🟣 The Cypher Pattern Overview The Cypher pattern is another that appears in both bullish (M shape) and bearish (W shape) forms. It resembles the Shark pattern, with point C in the bullish Cypher extending beyond point A, and point D forming within the XA line. The bearish Cypher shares the Fibonacci ratios with the bullish Cypher but in an inverted structure. Point D in the bearish Cypher marks the start of a significant price drop, perfect for sell orders followed by buying at lower prices. 🟣 Introducing the Nen-Star Pattern The Nen-Star pattern appears in both bullish (M shape) and bearish (W shape) forms. In the bullish Nen-Star, point C extends beyond point A, and point D, the final point, forms outside the XA line, making CD the longest wave. The bearish Nen-Star has inverted Fibonacci ratios, with point D indicating the start of a significant price drop. Traders can place sell orders at point D and buy at lower prices to profit from this pattern in two-way markets. The 5-point harmonic patterns, commonly referred to as XABCD patterns, are specific geometric price structures identified in financial markets. These patterns are used by traders to predict potential price movements based on historical price data and Fibonacci retracement levels. Here are the main 5-point harmonic patterns : Gartley Pattern Anti-Gartley Pattern Bat Pattern Anti-Bat Pattern Alternate Bat Pattern Butterfly Pattern Anti-Butterfly Pattern Crab Pattern Anti-Crab Pattern Deep Crab Pattern Shark Pattern Anti- Shark Pattern Anti Alternate Shark Pattern Cypher Pattern Anti-Cypher Pattern   🔵 How to Use To add "Order Block Refiner Library", you must first add the following code to your script. import TFlab/Harmonic_Chart_Pattern_Library_TradingFinder/1 as HP 🟣 Parameters XABCD(Name, Type, Show, Color, LineWidth, LabelSize, ShVF, FLPC, FLPCPeriod, Pivot, ABXAmin, ABXAmax, BCABmin, BCABmax, CDBCmin, CDBCmax, CDXAmin, CDXAmax) => Parameters: Name (string) Type (string) Show (bool) Color (color) LineWidth (int) LabelSize (string) ShVF (bool) FLPC (bool) FLPCPeriod (int) Pivot (int) ABXAmin (float) ABXAmax (float) BCABmin (float) BCABmax (float) CDBCmin (float) CDBCmax (float) CDXAmin (float) CDXAmax (float) 🟣 Genaral Parameters Name : The name of the pattern. Type: Enter "Bullish" to draw a Bullish pattern and "Bearish" to draw an Bearish pattern. Show : Enter "true" to display the template and "false" to not display the template. Color : Enter the desired color to draw the pattern in this parameter. LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness. LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries. 🟣 Logical Parameters ShVF : If this parameter is on "true" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "false" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern. FLPC : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the lateest pattern seeing and a sharp reduction in reward to risk. FLPCPeriod : Using this parameter you can determine that the last pivot is based on Pivot period. Pivot : You need to determine the period of the zigzag indicator. This factor is the most important parameter in pattern recognition. ABXAmin : Minimum retracement of "AB" line compared to "XA" line. ABXAmax : Maximum retracement of "AB" line compared to "XA" line. BCABmin : Minimum retracement of "BC" line compared to "AB" line. BCABmax : Maximum retracement of "BC" line compared to "AB" line. CDBCmin : Minimum retracement of "CD" line compared to "BC" line. CDBCmax : Maximum retracement of "CD" line compared to "BC" line. CDXAmin : Minimum retracement of "CD" line compared to "XA" line. CDXAmax : Maximum retracement of "CD" line compared to "XA" line. 🟣 Function Outputs This library has two outputs. The first output is related to the alert of the formation of a new pattern. And the second output is related to the formation of the candlestick pattern and you can draw it using the "plotshape" tool. Candle Confirmation Logic : Example : import TFlab/Harmonic_Chart_Pattern_Library_TradingFinder/1 as HP PP = input.int(3, 'ZigZag Pivot Period') ShowBull = input.bool(true, 'Show Bullish Pattern') ShowBear = input.bool(true, 'Show Bearish Pattern') ColorBull = input.color(#0609bb, 'Color Bullish Pattern') ColorBear = input.color(#0609bb, 'Color Bearish Pattern') LineWidth = input.int(1 , 'Width Line') LabelSize = input.string(size.small , 'Label size' , options = ) ShVF = input.bool(false , 'Show Valid Format') FLPC = input.bool(false , 'Show Formation Last Pivot Confirm') FLPCPeriod =input.int(2, 'Period of Formation Last Pivot') //Call function = HP.XABCD('Bullish Bat', 'Bullish', ShowBull, ColorBull , LineWidth, LabelSize ,ShVF, FLPC, FLPCPeriod, PP, 0.382, 0.50, 0.382, 0.886, 1.618, 2.618, 0.85, 0.9) = HP.XABCD('Bearish Bat', 'Bearish', ShowBear, ColorBear , LineWidth, LabelSize ,ShVF, FLPC, FLPCPeriod, PP, 0.382, 0.50, 0.382, 0.886, 1.618, 2.618, 0.85, 0.9) //Alert if BearAlert alert('Bearish Harmonic') if BullAlert alert('Bulish Harmonic') //CandleStick Confirm plotshape(BearCandleConfirm, style = shape.arrowdown, color = color.red) plotshape(BullCandleConfirm, style = shape.arrowup, color = color.green, location = location.belowbar )
Biblioteca Pine Script®
por TFlab
8
9:30 Opening Price MarkerIndicator Name: 9:30 Opening Price Marker Description: The "9:30 Opening Price Marker" is a custom indicator for TradingView that highlights the opening price at 9:30 AM in the UTC-4 time zone (Eastern Daylight Time) on the chart. It helps traders and analysts easily identify and track the price level at which the market opens each day. Features: Timezone Conversion: The indicator converts the current time to the UTC-4 timezone (Eastern Daylight Time) to accurately determine the 9:30 AM opening price. Visual Marker: It visually marks the opening price with a dotted line on the chart, making it prominent for quick reference. Label: Additionally, it includes a label next to the opening price line, indicating "9:30 Opening Price", enhancing clarity and usability. Overlay: The indicator is designed to overlay on the price chart, ensuring it doesn't clutter other technical analysis tools or indicators. Usage: Day-to-Day Analysis: Traders can use this indicator to quickly gauge market sentiment at the daily opening, which can influence intraday trading strategies. Reference Point: Acts as a reference point for identifying price movements and potential trading opportunities relative to the day's opening price. Time-Specific Insights: Provides insights into price action immediately following the market open, aiding in decision-making based on early trading activity. Installation: Copy the provided Pine Script code into TradingView's Pine Editor, save the script as an indicator, and apply it to your chart. Disclaimer : This indicator is intended for informational purposes only and should not be solely relied upon for trading decisions. Always consider multiple sources of information and perform thorough analysis before executing trades.
Indicador Pine Script®
por Gricar
Curved Smart Money Concepts Probability (Zeiierman)█ Overview The Curved Smart Money Concepts Probability indicator, developed by Zeiierman, is a sophisticated trading tool designed to leverage the principles of Smart Money trading. This indicator identifies key market structure points and adapts to changing market conditions, providing traders with actionable insights into market trends and potential reversals. The trading tool stands out due to its unique curved structure and advanced probability features, which enhance its effectiveness and usability for traders. █ How It Works The indicator operates by analyzing market data to identify pivotal moments where institutional investors might be influencing price movements. It employs a combination of adaptive trend lengths, multipliers for sensitivity adjustments, and pivot periods to accurately capture market structure shifts. The indicator calculates upper and lower bands based on adaptive sizes and identifies zones of overbought (premium) and oversold (discount) conditions. Key Features of Probability Calculations The Curved Smart Money Concepts Probability indicator integrates sophisticated probability calculations to enhance trading decision-making: Win/Loss Tracking: The indicator tracks the number of successful (win) and unsuccessful (loss) trades based on the identified market structure points (ChoCH, SMS, BMS). This provides a historical context of the indicator's performance. Probability Percentages: For each market structure point (ChoCH, SMS, BMS), the indicator calculates the probability of the next move being successful or not. This is presented as a percentage, giving traders a quantifiable measure of confidence in the signals. Dynamic Adaptation: The probability calculations adapt to market conditions by considering the frequency and success rate of the signals, allowing traders to adjust their strategies based on the indicator’s historical accuracy. Visual Representation: Probabilities are displayed on the chart, helping traders quickly assess the likelihood of future price movements based on past performance. Key benefits of the Curved Structure The Curved Smart Money Concepts Probability indicator features a unique curved structure that offers several advantages over traditional linear structures: Noise Reduction: The curved structure smooths out short-term market fluctuations, reducing the noise often seen in linear structures. This helps traders focus on the true trend direction rather than getting distracted by minor price movements. Adaptive Sensitivity: The curved structure adjusts its sensitivity based on market conditions. This means it can effectively capture both short-term and long-term trends by dynamically adapting to changes in market volatility, something linear structures struggle with. Enhanced Trend Detection: By providing a more gradual transition between market phases, the curved structure helps in identifying trends more accurately. This is particularly useful in volatile markets where linear structures might give false signals due to their rigid nature. Improved Market Structure Analysis: The curved structure's ability to adapt and smooth out irregularities provides a clearer picture of the overall market structure. This clarity is essential for identifying premium and discount zones, as well as mid-range support and resistance levels, which are crucial for effective ICT Smart Money Trading. █ Terminology ChoCH (Change of Character): Indicates a potential reversal in market direction. It is identified when the price breaks a significant high or low, suggesting a shift from a bullish to bearish trend or vice versa. SMS (Smart Money Shift): Represents the transition phase in market structure where smart money begins accumulating or distributing assets. It typically follows a BMS and indicates the start of a new trend. BMS (Bullish/Bearish Market Structure): Confirms the trend direction. Bullish Market Structure (BMS) confirms an uptrend, while Bearish Market Structure (BMS) confirms a downtrend. It is characterized by a series of higher highs and higher lows (bullish) or lower highs and lower lows (bearish). Premium: A zone where the price is considered overbought. It is calculated as the upper range of the current market structure and indicates a potential area for selling or shorting. Mid Range: The midpoint between the high and low of the market structure. It often acts as a support or resistance level, helping traders identify potential reversal or continuation points. Discount: A zone where the price is considered oversold. It is calculated as the lower range of the current market structure and indicates a potential area for buying or going long. █ How to Use Identifying Trends and Reversals: Traders can use the indicator to identify the overall market trend and potential reversal points. By observing the ChoCH, SMS, and BMS signals, traders can gauge whether the market is transitioning into a new trend or continuing the current trend. Example Strategies ⚪ Trend Following Strategy: Identify the current market trend using BMS signals. Enter a trade in the direction of the trend when the price retraces to the mid-range zone. Set a stop-loss just below the mid-range (for long trades) or above the mid-range (for short trades). Take profit in the premium/discount zone or when a ChoCH signal indicates a potential reversal. ⚪ Reversal Strategy: Wait for a ChoCH signal to identify a potential market reversal. Enter a trade in the direction of the new trend as indicated by the SMS signal. Set a stop-loss just beyond the recent high (for short trades) or low (for long trades). Take profit when the price reaches the premium or discount zone opposite to the entry. █ Settings Curved Trend Length: Determines the length of the trend used to calculate the adaptive size of the structure. Adjusting this length allows traders to capture either longer-term trends (for smoother curves) or short-term trends (for more reactive curves). Curved Multiplier: Scales the adjustment factors for the upper and lower bands. Increasing the multiplier widens the bands, reducing sensitivity to price changes. Decreasing it narrows the bands, making the structure more responsive. Pivot Period: Sets the period for capturing trends. A higher period captures broader trends, while a lower period focuses on short-term trends. Response Period: Adjusts the structure’s responsiveness. A low value focuses on short-term changes, while a high value smoothens the structure. Premium/Discount Range: Allows toggling between displaying the active range or previous range to analyze real-time or historical levels. Structure Candles: Enables the display of curved structure candles on the chart, providing a modified view of price action. ----------------- Disclaimer The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Indicador Pine Script®
por Zeiierman
31
Moving Average Z-Score Suite [BackQuant]Moving Average Z-Score Suite 1. What is this indicator The Moving Average Z-Score Suite is a versatile indicator designed to help traders identify and capitalize on market trends by utilizing a variety of moving averages. This indicator transforms selected moving averages into a Z-Score oscillator, providing clear signals for potential buy and sell opportunities. The indicator includes options to choose from eleven different moving average types, each offering unique benefits and characteristics. It also provides additional features such as standard deviation levels, extreme levels, and divergence detection, enhancing its utility in various market conditions. 2. What is a Z-Score A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values. It is measured in terms of standard deviations from the mean. For instance, a Z-Score of 1.0 means the value is one standard deviation above the mean, while a Z-Score of -1.0 indicates it is one standard deviation below the mean. In the context of financial markets, Z-Scores can be used to identify overbought or oversold conditions by determining how far a particular value (such as a moving average) deviates from its historical mean. 3. What moving averages can be used The Moving Average Z-Score Suite allows users to select from the following eleven moving averages: Simple Moving Average (SMA) Hull Moving Average (HMA) Exponential Moving Average (EMA) Weighted Moving Average (WMA) Double Exponential Moving Average (DEMA) Running Moving Average (RMA) Linear Regression Curve (LINREG) (This script can be found standalone ) Triple Exponential Moving Average (TEMA) Arnaud Legoux Moving Average (ALMA) Kalman Hull Moving Average (KHMA) T3 Moving Average Each of these moving averages has distinct properties and reacts differently to price changes, allowing traders to select the one that best fits their trading style and market conditions. 4. Why Turning a Moving Average into a Z-Score is Innovative and Its Benefits Transforming a moving average into a Z-Score is an innovative approach because it normalizes the moving average values, making them more comparable across different periods and instruments. This normalization process helps in identifying extreme price movements and mean-reversion opportunities more effectively. By converting the moving average into a Z-Score, traders can better gauge the relative strength or weakness of a trend and detect potential reversals. This method enhances the traditional moving average analysis by adding a statistical perspective, providing clearer and more objective trading signals. 5. How It Can Be Used in the Context of a Trading System In a trading system, it can be used to generate buy and sell signals based on the Z-Score values. When the Z-Score crosses above zero, it indicates a potential buying opportunity, suggesting that the price is above its mean and possibly trending upward. Conversely, a Z-Score crossing below zero signals a potential selling opportunity, indicating that the price is below its mean and might be trending downward. Additionally, the indicator's ability to show standard deviation levels and extreme levels helps traders set profit targets and stop-loss levels, improving risk management and trade planning. 6. How It Can Be Used for Trend Following For trend-following strategies, it can be particularly useful. The Z-Score oscillator helps traders identify the strength and direction of a trend. By monitoring the Z-Score and its rate of change, traders can confirm the persistence of a trend and make informed decisions to enter or exit trades. The indicator's divergence detection feature further enhances trend-following by identifying potential reversals before they occur, allowing traders to capitalize on trend shifts. By providing a clear and quantifiable measure of trend strength, this indicator supports disciplined and systematic trend-following strategies. No backtests for this indicator due to the many options and ways it can be used, Enjoy
Indicador Pine Script®
por BackQuant
6
Trend Forecasting - The Quant Science🌏 Trend Forecasting | ENG 🌏 This plug-in acts as a statistical filter, adding new information to your chart that will allow you to quickly verify the direction of a trend and the probability with which the price will be above or below the average in the future, helping you to uncover probable market inefficiencies. 🧠 Model calculation The model calculates the arithmetic mean in relation to positive and negative events within the available sample for the selected time series. Where a positive event is defined as a closing price greater than the average, and a negative event as a closing price less than the average. Once all events have been calculated, the probabilities are extrapolated by relating each event. Example Positive event A: 70 Negative event B: 30 Total events: 100 Probabilities A: (100 / 70) x 100 = 70% Probabilities B: (100 / 30) x 100 = 30% Event A has a 70% probability of occurring compared to Event B which has a 30% probability. 🔍 Information Filter The data on the graph show the future probabilities of prices being above average (default in green) and the probabilities of prices being below average (default in red). The information that can be quickly retrieved from this indicator is: 1. Trend: Above-average prices together with a constant of data in green greater than 50% + 1 indicate that the observed historical series shows a bullish trend. The probability is correlated proportionally to the value of the data; the higher and increasing the expected value, the greater the observed bullish trend. On the other hand, a below-average price together with a red-coloured data constant show quantitative data regarding the presence of a bearish trend. 2. Future Probability: By analysing the data, it is possible to find the probability with which the price will be above or below the average in the future. In green are classified the probabilities that the price will be higher than the average, in red are classified the probabilities that the price will be lower than the average. 🔫 Operational Filter . The indicator can be used operationally in the search for investment or trading opportunities given its ability to identify an inefficiency within the observed data sample. ⬆ Bullish forecast For bullish trades, the inefficiency will appear as a historical series with a bullish trend, with high probability of a bullish trend in the future that is currently below the average. ⬇ Bearish forecast For short trades, the inefficiency will appear as a historical series with a bearish trend, with a high probability of a bearish trend in the future that is currently above the average. 📚 Settings Input: via the Input user interface, it is possible to adjust the periods (1 to 500) with which the average is to be calculated. By default the periods are set to 200, which means that the average is calculated by taking the last 200 periods. Style: via the Style user interface it is possible to adjust the colour and switch a specific output on or off. 🇮🇹Previsione Della Tendenza Futura | ITA 🇮🇹 Questo plug-in funge da filtro statistico, aggiungendo nuove informazioni al tuo grafico che ti permetteranno di verificare rapidamente tendenza di un trend, probabilità con la quale il prezzo si troverà sopra o sotto la media in futuro aiutandoti a scovare probabili inefficienze di mercato. 🧠 Calcolo del modello Il modello calcola la media aritmetica in relazione con gli eventi positivi e negativi all'intero del campione disponibile per la serie storica selezionata. Dove per evento positivo si intende un prezzo alla chiusura maggiore della media, mentre per evento negativo si intende un prezzo alla chiusura minore della media. Calcolata la totalità degli eventi le probabilità vengono estrapolate rapportando ciascun evento. Esempio Evento positivo A: 70 Evento negativo B: 30 Totale eventi : 100 Formula A: (100 / 70) x 100 = 70% Formula B: (100 / 30) x 100 = 30% Evento A ha una probabilità del 70% di realizzarsi rispetto all' Evento B che ha una probabilità pari al 30%. 🔍 Filtro informativo I dati sul grafico mostrano le probabilità future che i prezzi siano sopra la media (di default in verde) e le probabilità che i prezzi siano sotto la media (di default in rosso). Le informazioni che si possono rapidamente reperire da questo indicatore sono: 1. Trend: I prezzi sopra la media insieme ad una costante di dati in verde maggiori al 50% + 1 indicano che la serie storica osservata presenta un trend rialzista. La probabilità è correlata proporzionalmente al valore del dato; tanto più sarà alto e crescente il valore atteso e maggiore sarà la tendenza rialzista osservata. Viceversa, un prezzo sotto la media insieme ad una costante di dati classificati in colore rosso mostrano dati quantitativi riguardo la presenza di una tendenza ribassista. 2. Probabilità future: analizzando i dati è possibile reperire la probabilità con cui il prezzo si troverà sopra o sotto la media in futuro. In verde vengono classificate le probabilità che il prezzo sarà maggiore alla media, in rosso vengono classificate le probabilità che il prezzo sarà minore della media. 🔫 Filtro operativo L' indicatore può essere utilizzato a livello operativo nella ricerca di opportunità di investimento o di trading vista la capacità di identificare un inefficienza all'interno del campione di dati osservato. ⬆ Previsione rialzista Per operatività di tipo rialzista l'inefficienza apparirà come una serie storica a tendenza rialzista, con alte probabilità di tendenza rialzista in futuro che attualmente si trova al di sotto della media. ⬇ Previsione ribassista Per operatività di tipo short l'inefficienza apparirà come una serie storica a tendenza ribassista, con alte probabilità di tendenza ribassista in futuro che si trova attualmente sopra la media. 📚 Impostazioni Input: tramite l'interfaccia utente Input è possibile regolare i periodi (da 1 a 500) con cui calcolare la media. Di default i periodi sono impostati sul valore di 200, questo significa che la media viene calcolata prendendo gli ultimi 200 periodi. Style: tramite l'interfaccia utente Style è possibile regolare il colore e attivare o disattivare un specifico output.
Indicador Pine Script®
por thequantscience