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Our focus is building indicators, custom libraries, and trading utilities that reveal market patterns others miss.
Open to discussions with traders and developers interested in algorithmic trading solutions.
https://www.mql5.com/en/market/product/148032
FBS-Demo
Login 103414472
Investor Ykj]]tM0
Version 5.786
New Features
1. New UsePanel Input Param To Enable or Disable Panel.
2. Added X and Y Input Param to move panel around.
3. Improve Logic, Faster Performance.
4. Improved Calculation Logic.
Like all trend indicators whipsaw occur, one of best way to reduce that is to trade in higher trend direction, easiest way to do so is using the SAR of
Step
0.0022
Maximum
0.2
and trailing winning trades.
Tutorial coming up.
Available Here
https://www.mql5.com/en/market/product/148032
Account Reports Here
https://www.forexfactory.com/sunrisejan/262854
May It Never Falter!
Let’s Build Together
https://www.mql5.com/en/channels/socialgathering
With a $1299 balance
Available Here
https://www.mql5.com/en/market/product/148032
Account Reports Here
https://www.forexfactory.com/sunrisejan/262854
Hopefully Resume Next Week Monday, Have a wonderful weekend.
May It Never Falter!
https://www.mql5.com/en/market/product/148032
FBS-Demo
Login 103414472
Investor Ykj]]tM0
https://www.mql5.com/en/market/product/148032
Login 103414472
Password Ykj]]tM0
FBS Demo
September Trades So far: $102.12
May It Never Falter!
https://www.mql5.com/en/market/product/148032
Free Download: https://www.mql5.com/en/market/product/148880
The MOON SNIPER indicator is a breakout detection tool that combines price action analysis with Gaussian Distribution mathematics to identify high-probability entry points in forex trading. Core Mechanism: The indicator calculates support and resistance levels using statistical price distribution rather than traditional pivot points. It applies Gaussian Distribution principles to determine where price is most likely to find equilibrium and where significant deviations may occur. Key Features
1. GAUSSIAN (Fisher Transform):
- Normal distribution with thin tails
- Transform: artanh(x) = 0.5 * ln((1+x)/(1-x))
- Best for: Smooth trending markets
2. STUDENT_T:
- Fat tails, captures market crashes better
- Parameter: degrees of freedom (lower = fatter tails)
- Best for: Volatile markets with frequent extremes
3. LAPLACE:
- Sharp peak, exponential tails
- Transform: sign(x) * ln(2|x|) for quantile function
- Best for: Markets with sudden reversals
4. LOGISTIC:
- Similar to normal but heavier tails
- Transform: logit function = ln(p/(1-p))
- Best for: General purpose with better extreme handling
5. HYPERBOLIC:
- Moderate fat tails, smooth
- Transform: inverse of sech distribution
- Best for: Balanced approach between normal and fat-tailed
6. SKEWED_T:
- Asymmetric with fat tails
- Captures directional bias in markets
- Best for: Trending markets with directional preference
Usage Recommendations:
- Trending markets: DIST_GAUSSIAN or DIST_HYPERBOLIC
- Volatile/choppy markets: DIST_STUDENT_T or DIST_LAPLACE
- Balanced approach: DIST_LOGISTIC
- Directional bias: DIST_SKEWED_T with appropriate skew parameter
Other profitable programs https://www.mql5.com/en/users/ifyjava/seller The Solarwind No Repaint is a technical oscillator that applies the Fisher Transform to normalized price data, creating a histogram-based indicator that identifies potential market turning points. This indicator converts price movements into a Gaussian normal distribution, making cyclical patterns and momentum shifts more visible to traders. How It Works The indicator processes price data through several
The Solarwind No Repaint is a technical oscillator that applies the Fisher Transform to normalized price data, creating a histogram-based indicator that identifies potential market turning points. This indicator converts price movements into a Gaussian normal distribution, making cyclical patterns and momentum shifts more visible to traders. How It Works The indicator processes price data through several computational steps: High-Low Analysis : Calculates the highest high and lowest low over the