Денис Нижегородов
AI Automation & Python Developer | Bots, APIs & Workflows
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Automated Trade Execution & Risk Management
n automated trade execution and risk management module built for a Python-based Telegram trading system.
The system monitors market signals, evaluates confidence levels, opens demo positions based on predefined trading rules, and automatically manages each position using Take Profit and Stop Loss levels.
The example shown demonstrates an automatically monitored BUY position successfully reaching its Take Profit target and being closed by the system with the final PnL recorded.
Key features:
Automated trade execution
BUY / SELL signal processing
Confidence-based entry rules
Automatic Take Profit & Stop Loss
Real-time position monitoring
Automatic position closing
PnL calculation and trade logging
Telegram notifications
PostgreSQL trade history
This module was developed as part of a larger automated market analysis and demo trading platform.
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Automated Trading Signal Analytics
A real-time analytics module for monitoring and evaluating automated cryptocurrency trading signals.
The system automatically stores and analyzes generated BUY, SELL, and HOLD signals, tracks confidence scores, records market prices, and provides performance statistics directly through a Telegram interface.
Key features:
Automated BUY / SELL / HOLD signal tracking
Real-time signal statistics
Confidence score monitoring
Historical signal logging
Trade performance and PnL analytics
Win rate tracking
PostgreSQL data storage
Telegram reporting interface
Automated background monitoring
This analytics module is part of a larger Python-based automated market analysis and demo trading system.
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Trading Analytics & Self-Learning System
A data-driven analytics and self-learning module built for an automated Telegram trading system.
The system continuously records trading signals and completed trades, analyzes historical performance, and provides real-time statistics directly through Telegram.
It tracks win rate, total and average PnL, best and worst trades, signal distribution, confidence scores, and trading performance over time.
Key features:
Automated trade history tracking
Real-time PnL calculation
Win rate monitoring
BUY / SELL / HOLD signal statistics
Confidence score analysis
Historical performance evaluation
PostgreSQL data storage
Telegram reporting interface
Automated signal logging
This module was developed as part of a larger Python-based automated market analysis and demo trading platform.
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AI-Powered Crypto Market Analysis
A real-time Telegram interface for automated BTC/USDT market analysis.
The system collects live market data and calculates multiple technical indicators, including RSI, EMA20, EMA50, MACD, MACD Signal, MACD Histogram, and ATR.
Based on these indicators, the bot generates a BUY/SELL/HOLD signal with a confidence score and automatically calculates Stop Loss, Take Profit, and position size using built-in risk management logic.
Key features shown:
Real-time BTC/USDT market data
RSI, EMA20 & EMA50 analysis
MACD, Signal & Histogram
ATR volatility measurement
Automated trading signals
Confidence scoring
Dynamic Stop Loss & Take Profit
Automatic position sizing
Telegram-based interface
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