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Trixter scalper TI

199 USD

Demo downloaded: 6

Published: 16 October 2026

Current version: 1.1

Trixter scalper TI

Experts
Andrei Samokhin
Andrei Samokhin
Russia

861
Welcome to my seller page. I develop applications in the fields of AI and machine learning, and I am also passionate about trading systems. My products are based on various machine learning techniques. I research and apply state-of-the-art algorithms for time series analysis and am constantly
Version: 1.1
Activations: 10

AI-based scalping trading system - the latest development in the field of AI and trading.

This system differs from the previous one by increased historical profitability. It uses special learning algorithms for trading with a high profit factor.

Since I am immersed in the development process and write many trading systems for my clients on order, I do not have time to test them myself. I invite respected buyers to share their trading reports with me; I am always open to fruitful cooperation. If any of the trading systems sparks your interest - be sure to write to me so that there is feedback.

A special promo price of $199 applies to the new product, hurry up to test the new system on favorable terms.

Features and advantages of this trading system:

Trades XAUUSD on any timeframe from M1 to H1. When the chart period changes, the trades differ.
The smaller the period, the higher the frequency of trades. Therefore, this system is mainly for scalping.
You can change the chart period "on the fly" while the expert is running. It will rebuild its logic for the selected timeframe by itself.
Stop-loss and take-profit matter! You can trade with short stops and long takes, or vice versa.
The system parameters are already configured, but you can optimize them at your discretion.
Not a loss-holder and not a position-averager. Honest trading with one order or a grid of orders (your choice).
Market entry strictly with limit orders, and closing trades by system signals.

What you need to do before and after purchasing:

First test the demo version with your broker on different timeframes. Use M1 and H1 to see the difference.
Test over the last 2-3 years, since the distant past no longer plays any role.
Try changing the lot size and be sure to look at the drawdown in the strategy tester.
Change or optimize the stop-loss and take-profit to find the best option for yourself.
Important: choose trading hours based on the backtester results, this can provide more stable trading!
Decide on your deposit size, choose the trading lot and do a final test.
Then, when you have made sure that everything is configured and works as needed, proceed to purchasing the bot.

I always answer questions in private messages.

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Local Outlier Factor (LOF) Algorithm is a machine learning method for finding anomalies in data that cannot be detected using global thresholds. Unlike simple methods, LOF looks for local outliers by comparing the density of points in their immediate vicinity. How it works The main idea of LOF is simple: an anomaly is a point whose surrounding object density is significantly lower than the density around its neighbors . Selecting the neighborhood. For each point, the algorithm finds k

99 USD

Decision tree is a supervised machine learning algorithm that operates on the principle of sequential "Yes/No" questions. It is a tree-like structure where: Internal nodes — are checks of some feature (e.g., "Age > 18?"). Branches — are the results of the check (Yes/No). Leaves — are the final decision (answer). The construction process is that the algorithm automatically finds the most important feature at each step (using criteria such as Gini Index or Entropy ) and splits the data into more h

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Love high-frequency, high-speed trading with low risk? Then this bot is created specifically for you. Thanks to precise entries and high expected payoff, the bot trades with tight stops while capturing large point movements. The stop-loss to take-profit ratio can reach up to 1:10—meaning the stop-loss is 10 times smaller than the take-profit—while this scalping bot remains profitable and does not hold onto losing trades, according to test results. This is an excellent system for those who are u

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Do you love high-frequency, high-speed trading with low risks? Then Trixter Quantum was created specifically for you. Thanks to precise entries and high mathematical expectation, the bot trades with short stop-losses while capturing large movements in points. Its core algorithm is based on the analysis of local entanglement of adjacent states (patterns), allowing it to instantly detect hidden microstructural shifts in the market. The stop-loss to take-profit ratio can reach up to 1:10 (the sto

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Elliptic Envelope is a parametric machine learning algorithm designed to detect outliers and anomalies in multidimensional data. The method assumes that "normal" data (the main sample) follows a multidimensional normal (Gaussian) distribution. Operating Principle Ellipsoid Formation: In the feature space, the algorithm builds a hyperellipsoid around the central group of points. The boundary of this ellipsoid is determined by the covariance matrix and the mean values of the features. Use of Ma

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The robust covariance (mincovdet) method, or Minimum Covariance Determinant (MCD) , is a robust method for estimating the covariance matrix and mean vector that is resistant to outliers in the data. The idea of the method Classical sample covariance is very sensitive to "contamination." MCD solves this problem by finding a "clean" subset of observations that does not contain outliers and computing standard estimates (mean and covariance) only on it. What MCD (mincovdet) is used for 1. Detection

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SVM solves a binary classification problem: it separates two classes. But One-Class SVM is trained only on data from one class ("normal" examples) and builds a boundary around them (a hyperplane in the transformed space) that separates this region from everything else. Everything that falls inside the region is considered normal, everything outside is an anomaly. How it works Data is mapped into a feature space (via a kernel, e.g., RBF). The algorithm looks for a hyperplane maximally distant fro

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Artificial intelligence-based scalping trading system - the latest development in the field of AI and trading. Since I am immersed in the development process and write many trading systems for my clients on order, I do not have time to test them myself. I invite respected buyers to share their trading reports with me; I am always open to fruitful cooperation. If any of the trading systems sparks your interest - be sure to write to me so that there is feedback. There is a special promo price of $

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Andrei Samokhin