Qv2 MA

QV2 MA is an indicator that displays the results of two smoothed moving averages applied to Candles.

Item 01 - Buy signal: Candle show color Aqua when the 4-period smoothed moving average is expanding and above the 24-period smoothed moving average.

Item 02 - Sell Signal: Candle show color HotPink color when a 4-period smoothed moving average is expanding and below the 24-period smoothed moving average.

Item 03 - The gray candle is an undefined region.


When the candle is gray, there are two recommendations:

1-) When you have an open position, the recommendation is to close.

2-) When in a closed position, the recommendation is to wait for some of the signals described in items 01 and 02.


Important note: Histogram in blue and red colors is displayed to improve the trader's analysis. But the buy and sell signals are described in items 01 and 02.


Can be used on all deadlines.

Can be used on all pairs.

I use in H1




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The Qv² Histogram - Indicator developed for traders with advanced experience. This indicator has two purposes: 1-) Identify price normality patterns (green color) 2-) Identify abnormal price patterns “outliers” (red color) ====================================================================================================================================== Interpretation for trades in start trend: Histogram (Green color) crossing the zero line upside - uptrend. Histogram (Green color) crossing th
The Qv² Trend is an indicator that aims to identify trends. Buying trend signals are indicated by arrows pointing up. Selling trend signals are indicated by arrows pointing down. It can be used in all deadlines. It can be used in all pairs. I use it on the H1 with a period of 24. Important Recommendation: Make sure you trade in trend market. Good Trades, in trend market
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Joao Marcilio
BEHOLDER – THE INDICATOR THAT REVEALS HIDDEN PATTERNS IN TIME THE REAL TRADER’S PROBLEM: TEMPORAL BLINDNESS Every week, thousands of traders face the same dilemma: A flood of economic events (NFP, CPI, Interest Rates, Retail Sales…) Very little time to analyze correlations Decisions made on “gut feeling,” without reliable historical context Trying to do this manually is insane: Scrolling back through dozens of weeks on the calendar Comparing event by event Trying to calculate patt
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