Ali Şahbaz
📧 Email: ali_sahbaz@outlook.com
Trader_Bot is a high-performance trade bot built with C++ and Qt Framework 6.7.1, specifically designed for cryptocurrency markets.
This bot leverages advanced algorithms, multithreading, and real-time data analysis to execute trades based on user-defined strategies. With its customizable parameters and robust risk management tools, it serves as a powerful tool for both backtesting and live trading.
This project requires expertise in the following areas:
- Quant Developer: Building high-performance algorithms for financial markets.
- HFT Algorithms: High-frequency trading strategies and systems.
- C++: Proficiency in C++ for developing performance-critical applications.
- Mathematics: Advanced mathematical models for financial data analysis and algorithmic trading.
- Finance: Understanding of financial markets, trading strategies, and risk management.
- Cryptocurrency Markets: Knowledge of cryptocurrency trading platforms and APIs.
- Multithreading: Efficient execution of concurrent tasks in high-performance applications.
- Technical Analysis: Use of indicators like Moving Averages, MACD, Bollinger Bands, etc.
- Backtesting: Designing and running tests for trading strategies using historical data.
Keywords:
Quantitative Finance, Algorithmic Trading, High-Frequency Trading (HFT), C++, Mathematical Models, Cryptocurrency, Real-Time Data, Trading Strategies, Backtesting, Risk Management, Trading Bots, Finance, Technical Analysis.
- Custom Graphics Processing: High-performance visualization tools for monitoring and analysis.
- Trade / HFT Algorithm Integration: Implements cutting-edge algorithms for high-frequency trading.
- Modern Software Patterns: Employs advanced design patterns for maintainable and scalable development.
- Simplified Strategy Management: Easily add and test new trading strategies with minimal effort.
- Custom Binance WebSocket Library: Built for efficient real-time data retrieval and communication.
- Custom Binance REST API Implementation: Provides seamless interaction with Binance endpoints.
- Real-Time Testing: Direct testing of strategies with live market data.
- Backtesting Support: Analyze historical data to optimize and validate strategies.
- Fake Account Testing: Test strategies without risking actual funds.
- Custom OHLC Structures & Math Models: Supports complex calculations and high-precision operations.
- 20+ Pre-Built Strategies: Includes templates (
template_strategy.h) for creating your own strategies. - Comprehensive Logging Support: Provides detailed logs for debugging, analysis, and auditing.
- User-Friendly GUI: Offers an intuitive interface for traders to easily manage and monitor their trading activities.
This page emulates a Binance account. It supports:
- Monitoring real-time coin data
- Placing buy/sell orders
- Integrating strategies
- Viewing open orders, wallet balance, and logs
Provides an interface to visualize and analyze RSI and real-time data graphics. Features include:
- Configurable visibility of data elements
- Adjustable display settings
Allows users to:
- Select a strategy and a time range for backtesting
- Start testing and monitor data flow
- Control data flow speed via the GUI
- Log activities and set custom parameters for strategies
- Select coins and specify candle types, supporting up to second-level granularity
Displays LONG and SHORT orders directly on the graph. Features include:
- Analyzing past wallet performance
- Evaluating the strength of strategies through logs and graphical representations
The Moving Average (MA) calculates the average price movement of an asset over time. It helps traders smooth out price data and identify trends.
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Simple Moving Average (SMA):
The arithmetic average of prices over a specific time period.
Example: A 50-day SMA would average the closing prices of an asset over the past 50 days. -
Exponential Moving Average (EMA):
EMA gives more weight to recent prices, making it more sensitive and faster to respond to price changes.
Example: The 12-period EMA gives more importance to the last 12 price points than to the earlier ones.
Application in Trading:
Moving Averages can act as support and resistance levels. When the price is above a moving average, it may be seen as a support level, while if the price is below, it can be seen as a resistance level.
-
Golden Cross: When a short-term moving average crosses above a long-term moving average, it's a potential buy signal.
Example: A 50-day SMA crossing above a 200-day SMA. -
Death Cross: When a short-term moving average crosses below a long-term moving average, it’s a potential sell signal.
Example: A 50-day SMA crossing below a 200-day SMA.
MACD is a momentum and trend-following indicator that shows the relationship between two moving averages of an asset's price.
- The MACD line is calculated by subtracting the 26-period EMA from the 12-period EMA.
- The signal line is the 9-period EMA of the MACD line.
Trading Signals:
- Bullish signal: When the MACD crosses above the signal line.
- Bearish signal: When the MACD crosses below the signal line.
Bollinger Bands are volatility indicators that consist of a middle band (SMA) and two outer bands that are standard deviations away from the middle band.
- Upper Band: Represents overbought conditions.
- Lower Band: Represents oversold conditions.
Usage in Trading:
- Price bouncing off the lower band may indicate a buy signal, and bouncing off the upper band may indicate a sell signal.
Fibonacci retracement is a tool used to identify potential levels of support and resistance. The key Fibonacci levels are 23.6%, 38.2%, 50%, 61.8%, and 100%.
Example:
- If the price rises from 100 to 200, traders may expect the price to retrace to levels such as 161.8% of the rise (161.8% of 100-200 move) before continuing the uptrend.
The Stochastic Oscillator measures the level of the closing price relative to the high-low range over a specific period.
- Overbought zone: Values above 80 indicate overbought conditions.
- Oversold zone: Values below 20 indicate oversold conditions.
Usage in Trading:
- A buy signal occurs when the oscillator crosses from below 20 to above 20.
- A sell signal occurs when it crosses from above 80 to below 80.
Divergence occurs when the price of an asset moves in the opposite direction of an indicator (such as MACD or RSI), potentially signaling a reversal.
Example:
- Bullish Divergence: When prices form lower lows, but the indicator forms higher lows, suggesting potential upward momentum.
- Bearish Divergence: When prices form higher highs, but the indicator forms lower highs, suggesting potential downward momentum.
The Parabolic SAR is a trend-following indicator that helps determine the potential reversal points in the market.
- When the SAR is below the price, the trend is bullish, and when it is above the price, the trend is bearish.
This is a Japanese technical analysis indicator that provides insights into the market’s trend, support and resistance levels, and potential future price movements. It consists of five lines:
- Tenkan-sen: A fast-moving average.
- Kijun-sen: A slower-moving average.
- Senkou Span A and B: Leading lines forming the cloud, which indicates support or resistance.
- Chikou Span: The lagging line, showing the current price in relation to the past.
The ATR measures volatility by calculating the average of true ranges (the difference between the high and low of an asset for a period). A higher ATR indicates higher volatility.
CMF is a volume-weighted average of accumulation and distribution over a specified period. It measures the money flow of an asset.
Interpretation:
- Positive CMF: Indicates accumulation (buying pressure).
- Negative CMF: Indicates distribution (selling pressure).
OBV is a cumulative indicator that adds volume on up days and subtracts volume on down days, helping to gauge the direction of the trend.
Williams %R is a momentum indicator that measures overbought and oversold conditions.
- Overbought: Values above -20.
- Oversold: Values below -80.
- CPI (Consumer Price Index): Measures the average change over time in the prices paid by consumers for goods and services.
- PPI (Producer Price Index): Measures the average change in selling prices received by domestic producers for their output.
- GDP (Gross Domestic Product): Represents the total value of goods and services produced by a country in a specific time period.
- BETA: Measures an asset’s sensitivity to market movements.
- Delta: Measures the rate of change of an option’s price relative to the underlying asset’s price.
- Gamma: Measures the rate of change in delta.
- Vega: Measures an option's sensitivity to volatility.
- Theta: Measures the time decay of options.
- Rho: Measures an option's sensitivity to interest rate changes.
- Spread: The difference between an asset’s buying price and selling price.
- Margin: The amount of capital required to open a position.
- Leverage: Allows you to control a larger position with a smaller amount of capital.
- Drawdown: The decline from the highest value to the lowest during a particular period.
- Clone the repository:
git clone https://github.com/Alishbz/Trader_Bot.git cd Trader_Bot
