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AFL for Open Range BreakOut

AFL for Open Range BreakOut
That works great for me !!!


/* Intraday Open Range Breakout Exploration AFL by GMS
What's the open range breakout system ?
1. it identifies the highest price and lowest price reached since open upto the Start Time,
2. Enter long when Price cross above ORBH (Open Range Breakout High) with a stop loss at ORBL(open Range Breakout Low), once in trade adjust SL as per your risk tollarence level.
3. Enter Short when Price cross below ORBL (open Range Breakout Low) with a stop loss at ORBH((Open Range Breakout High),once in trade adjust SL as per your risk tollarence level.
What is in this AFL?
1) Draws regular Candle chart
2) Set ORB Time as per param
3) Marks "ORB High" Green dotted line, "ORB Low" Red dottend line and additional Black dotted line which is middle of ORBH & ORBL on chart
4) Possible to explore, Exploration results are sorted alphabatically and shows following columns
Column 1 = Script
Column 2 = Date
Column 3 = ORBH - Open Range Breakout High value, Green means already triggered.
Column 4 = ORBL - Open Range Breakout Low value, Red Mean already triggered.
Column 5 = ORB High Breakout gain, that is maximum gain if entered long as per ORBH
Column 6 = ORB Low Breakout gain, that is maiimum gain if short as per ORBL
How to trade?
Once ORBH & ORBL are values are set as per param time, place 2 orders
 1) BUY stop loss order if price crosses above ORBH price
 2) SELL stop loss order if price crosses below ORBL price.
Please strictly trade with stop loss, ideally for long stop loss = ORBL & for short stop loss = ORBH. Please feel free to adjust stop loss based on your risk tollarence level.
_SECTION_BEGIN("Intraday ORB Exploration");
SetChartOptions( 0, chartShowArrows chartShowDates );
BT = ParamTime ("Open Breakout Time""09:15");
afterbreakout0 = Cross(TimeNum(),BT);
afterbreakout1 = TimeNum()>=BT;
NewDay = Day()!= Ref(Day(), -1);
highestoftheday = HighestSince(newday,H,1);
Lowestoftheday =LowestSince(newday,L,1);
ORBH = ValueWhen(afterbreakout0,highestoftheday,1);
ORBL = ValueWhen(afterbreakout0,lowestoftheday,1);
Plot(ORBM, ""colorBlackstyleDots);
Plot C"Close"ParamColor("Color"colorBlack ), styleNoTitle ParamStyle("Style") |GetPriceStyle() );
Filter = ORBH OR ORBL;
AddColumn( ORBH, "C>ORBH", 1.2, colorDefault, IIf(Close>ORBH, colorGreenIIf(Close>ORBM,colorSeaGreen, colorDefault)));
AddColumn( ORBL, "C<ORBL", 1.2, colorDefault, IIf(Close<ORBL, colorRedIIf(Close<ORBM,colorOrange, colorDefault)));
AddColumn( ORBHG, "ORB High Breakout Gain", 1.2, colorDefault, IIf(ORBHG>0, colorGreen, colorDefault));
AddColumn( ORBLG, "ORB Low Breakout Gain", 1.2, colorDefault, IIf (ORBLG>0, colorRed, colorDefault));


1. The 20-day moving average commonly marks the short-term trend, The 50-day moving average the intermediate trend, and the 200-day Moving average the long-term trend of the market.

2. These three settings represent natural boundaries for price Pullbacks. Two forces empower those averages: First, they define Levels where profit- and loss-taking should ebb following strong price Movement. Second, their common recognition draws a crowd that Perpetrates a self-fulfilling event whenever price approaches.

3. Moving averages generate false signals during range-bound markets Because they’re trend-following indicators that measure upward or Downward momentum. They lose their power in any environment that Shows a slow rate of price change.

4. The characteristic of moving averages changes as they flatten and Roll over. The turn of an average toward horizontal signifies a loss of Momentum for that time frame. This increase the odds that price will Cross the average with relative ease. When a set of averages flat line And draw close to one another, price often swivels back and forth Across the axis in a noisy pattern.

5. Moving averages emit continuous signals because they’re plotted Right on top of price. Their relative correlation with price development Changes with each bar. They also exhibit active convergence divergence Relationships with all other forms of support and resistance.

6. Use exponential moving averages, or EMAs, for longer time frames But shift down to simple moving averages, or SMAs, for shorter ones.EMAs apply more weight to recent price change, while SMAs view each Data point equally.

7. Short-term SMAs let traders spy on other market participants. The Public uses simple moving average settings because they don’t Understand EMAs. Good intraday signals rely more on how the Competition thinks than the technicals of the moment.

8. Place five-, eight- and 13-bar SMAs on intraday charts to measure Short-term trend strength. In strong moves, the averages will line up And point in the same direction. But they flip over one at a time at highs And lows, until price finally surges through in the other direction.

9. Price location in relation to the 200-day moving average determines Long-term investor psychology. Bulls live above the 200-day moving Average, while bears live below it. Sellers eat up rallies below this line In the sand, while buyers come to the rescue above it.

10. When the 50-day moving average pierces the 200-day moving Average in either direction, it predicts a substantial shift in buying and Selling behavior. The 50-day moving average rising above the 200-day Moving average is called a Golden Cross, while the bearish piercing is Called a Death Cross.

11. It’s harder for price to break above a declining moving average than A rising moving average. Conversely, it’s harder for price to drop Through a rising moving average than a declining moving average.

12. Moving averages set to different time frames reveal trend velocity Through their relationships with each other. Measure this with a classic Moving Average-Convergence-Divergence (MACD) indicator, or apply Multiple averages to your charts and watch how they spread or contract Over different time.

13. Place a 60-day volume moving average across green and red Volume histograms in the lower chart pane to identify when specific Sessions draw unexpected interest. The slope of the average also Identifies hidden buying and selling pressure.

14. Don’t use long-term moving averages to make short-term Predictions because they force important data to lag current events. A Trend may already be mature and nearing its end by the time a specific Moving average issues a buy or sell signal.

15. Support and resistance mechanics develop between moving
Averages as they flip and roll. Look for one average to bounce on the Other average, rather than break through it immediately. After a Crossover finally takes place, that level becomes support or resistance For future price movement