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EMA IN PYTHON - TECHNICAL ANALISYS LIBRARY
EMA EN PYTHON - TECHNICAL ANALISYS LIBRARY
The instructor demonstrates how to load the exponential moving average indicator in Python using pre-loaded data. The first step is to obtain the data from MetaTrader 5, which can be done by selecting the desired market and dates and then exporting the data. Once the data is obtained, it needs to be converted into candles using a function. The instructor then installs the necessary library and imports the EMA indicator class from the library. To compute the EMA, a data frame column, such as the close data, is passed to the constructor. The window parameter specifies the number of periods to use for the EMA. Finally, the EMA values are obtained using the ema_indicator method, which creates a data frame with the values.
SMA IN PYTHON - TECHNICAL ANALYSIS LIBRARY
SMA EN PYTHON!! - TECHNICAL ANALYSIS LIBRARY
The video talks about the Simple Moving Average (SMA) and how it can be used in Python. The presenter explains that SMA is easy to use with past data, which can be obtained through MetaTrader5. The video goes on to demonstrate how to create candles from tick data and compute the SMA value using the AlgoTraderTrends library. The presenter provides a step-by-step guide on how to import and use the library to compute the SMA value from a specific column of the data frame. The video concludes with a call to action for viewers to like, subscribe, and share the video if they found it helpful.
How to import stock price data from MetaTrader 5 into Python?
How to import stock price data from MetaTrader 5 into Python?
In this YouTube video, different methods to import stock price data from MetaTrader 5 into Python are explained. The methods include importing necessary libraries, setting the desired time frame and time zone, defining a function called "get data," manipulating the resulting data frame, using the tqtndm package, creating a rates frame, and utilizing two data frames to retrieve prices and date/time information. The speaker suggests putting the loops into a function to make the code cleaner, and using these methods, users can easily import data for numerous symbols without much difficulty.
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RSI TRADING BOT IN PYTHON!!- GETTING DATA FROM METATRADER 5
RSI BOT DE TRADING EN PYTHON!! - COGIENDO DATOS DE MT5
The video provides an in-depth tutorial on creating a Python bot using the RS index on MetaTrader 5 (MT5) for algorithmic trading. The process involves configuring MT5 for algorithmic trading and web requests, creating a bot file using the Mt5 library, and importing the RS trading class, with a constructor that receives parameters such as the time period, lot size, and market string. To activate the bot, the presenter uses the "set" function to initiate an event, and the "join" function to end the process correctly. The video also covers the creation of a server module to receive data from MT5 and the definition of a function to open and close bot trades. The presenter tests the bot by loading it onto a chart and analyzing its behavior. Overall, the video provides an extensive guide on how to set up and test the RSI bot for automated trading.
How to download data from the Stock Market with MetaTrader 5 and Python
Como baixar dados da Bolsa de Valores com MetaTrader 5 e Python
The video tutorial "Como baixar dados da Bolsa de Valores com MetaTrader5 e Python" explains how to download stock market data using MetaTrader5 and Python. The tutorial demonstrates how to create a Python script to access desired assets and export the data to a CSV file. The video covers topics such as securely storing login credentials, manipulating data with Pandas, and extracting data from candles using cop rates. The high-quality and free data available is a valuable resource for developing tools to attract more people to the stock market. The video concludes with a call to visit the Develop Academy website for further learning and connecting via Instagram.
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Online Trading by Python in MetaTrader 5 + Get Data from MQL5
Get the code at GitHub: https://github.com/Hesamtps/online-trading-by-python-in-MetaTrader5-get-data-from-mql5
Online Trading by Python in MetaTrader 5 + Get Data from MQL5
The tutorial demonstrates how to download a dataset from MetaTrader and conduct online trading deals using Python. The instructor imports the MetaTrader5, pandas, and datetime libraries, specifies the asset and timeframe for the dataset, and downloads the last hundred data points. They explain how to manage a position in MetaTrader5 by setting stop loss, take profit, and using the GTC command for a specified duration. While the section provides a basic understanding of the different commands required to manage a position, it's unclear what the overall trading strategy being employed is.
Trading with Python - How to execute orders on the stock market?
Trading con Python - ¿Cómo ejecutar órdenes en bolsa?
In this video I show you how to execute stock orders with Python. For those who want to apply their knowledge in data analysis and economics, in the stock market.
Part 2: TRADING with Python - How to do automated INVESTMENTS?
Parte2: TRADING con Python - ¿Cómo hacer INVERSIONES automatizadas?
This is part two, on how to trade with Python. In the first part I explained how to launch orders. In this part I teach to launch orders based on the price of stocks and their relationships between them, automatically, with data from web scraping and apply algorithmic Trading.
Algorithmic Trading with Python (MACD Indicator)
Trading Algorítmico con Python (Indicador MACD)
In this video on "Trading Algorítmico con Python (Indicador MACD)," the instructor provides a detailed explanation of how the MACD indicator can be used to create trading algorithms in Python. The video covers the three parameters used by the MACD indicator, and how they dictate buying and selling decisions. Libraries like Pandas, NumPy, and Yahoo Finance are used to obtain and analyze stock data, while data cleaning techniques and dictionaries are used to retrieve key information. Overall, the video provides a practical overview of building trading algorithms with Python and the MACD indicator.
Algorithmic Trading with Python (Bollinger Bands Indicator)
Trading Algorítmico con Python (Indicador Bandas de Bollinger)
In this video, the speaker discusses Bollinger Bands, how they measure market volatility, and how to create an automated order system based on them using Python. The speaker explains the main libraries used, such as Yahoo Finance and Pandas, and emphasizes the importance of specifying parameters to customize the system for each stock analyzed. They also demonstrate adding data to the buy and sell columns and how to compare the last sale date with the current date and initiate a sale if they match. Finally, the speaker reminds viewers that technical analysis is not always accurate and suggests combining various indicators and using artificial intelligence to make informed trading decisions.