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Technical Analysis is a study of examining and predicting price movements by using historical price charts and statistics. Based on previous market chart patterns, a trader predicts future possible price trajectories. Traders use Technical Analysis for the Entry and Exit of their Short term, Long term as well as Intraday trades. Most used Chart type in Stock Market is Candlestick Charts. 

AI models can analyze the historical market data and volatility that could affect returns and adjust portfolios in real-time to align with changing market conditions. Besides this, AI-driven algorithms improve overall portfolio performance by suggesting diversification strategies to mitigate potential risk.

Python is a versatile programming language widely used in stock trading for various purposes. Here are some ways Python can be utilized in stock trading:

enable traders to analyze historical market data, calculate financial metrics, and visualize trends and patterns. This helps traders make informed decisions based on data-driven insights.

for developing and backtesting algorithmic trading strategies. Traders can automate trade execution, optimize strategies, and simulate performance using historical data.

allow traders to retrieve real-time market data from financial websites, APIs, and data providers. This data can be used for analysis, decision-making, and strategy development.

enable traders to build predictive models for forecasting stock prices, identifying trading signals, and optimizing investment strategies.

Python facilitates risk management and portfolio optimization

trading platforms to execute trades, manage orders, and monitor portfolio performance programmatically. This allows for customized trading workflows and streamlined execution processes.

Traders can evaluate the historical performance of their strategies, identify areas for improvement, and refine their approach.