Python in algorithmic trading - page 9

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HOW TO AUTOMATE THE ORDERS PLACEMENT ON THE STOCK EXCHANGE USING PYTHON

AUTOMATIZAR O ENVIO DE ORDENS NA BOLSA DE VALORES USANDO PYTHON

In the video "COMO AUTOMATIZAR O ENVIO DE ORDENS NA BOLSA DE VALORES USANDO PYTHON", the instructor demonstrates how to use Python language to create a robot trader for executing orders in MetaTrader 5.

They use IRBR33F as an example and show how to input the symbol, deviation, order type, volume, and execution price in just a few minutes.

The instructor also offers a course on Python and algorithm development for those interested in learning more.

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Python and MetaTrader 5 Algotrading Demo 03.26.2021

ALGOTRADING - PYTHON E METATRADER 5 - DEMONSTRAÇÃO 26.03.2021

In this video I show how to collect intraday data from stock exchange assets, based on timeframes, using Python.

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LONG AND SHORT TRADES WITH PYTHON - ALGORITHMIC TRADING

OPERAÇÃO LONG AND SHORT COM PYTHON - ALGORITHMIC TRADING

The video shows a demonstration of using Python and MetaTrader to perform long and short operations.

The presenter executes a trade for Petro 4 and Petro 3 and sets a condition that automatically closes the trade if it reaches a profit of 20 Brazilian reals.

Although the demonstration is not done step-by-step, it showcases the possibility of using Python to execute trades using condition statements and order functions in a straightforward manner.

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MetaTrader 5 + Python : Creating indicator #1

MetaTrader 5 + Python делаем индикатор #1

This YouTube video serves as an introduction to using Python with MetaTrader 5 for creating trading indicators. The video covers topics such as installing libraries, initializing MetaTrader 5, and testing scripts. Additionally, the video explains how to analyze price and volume data using Python and how to retrieve data from different assets. The importance of testing scripts and sharing code is emphasized, and the video concludes with a call for viewers to share their own codes and resources on social media.

• 00:00:00 In this section, the YouTube video presenter discusses creating indicators using trading and Python. The presenter first checks the sound quality and asks viewers to alert him if they experience any issues with sound. He then showcases a feature that allows users to analyze and pull data from stock scenes, write their own codes, and use those codes for indicators. Additionally, the presenter explains how users can use a wizard to choose either Python script or a generated library before highlighting some of the errors that might occur when trying to use the script. Finally, he reveals the code generated and discusses resolution issues.
  
  
• 00:05:00 In this section, the author explains how to create an indicator using Python and MetaTrader 5. They start by showing how to install the required library for working with MetaTrader5 in Python and then demonstrate how to locate the Python path. The YouTuber proceeds to show how to initialize MetaTrader 5 and test a script. They also make reference to the MetaTrader 5 documentation, which they say is critical to the entire process. Overall, the YouTuber's video serves as an introduction to creating an indicator with Python and MetaTrader5.
  
  
• 00:10:00 In this section of the video, the speaker demonstrates how to calculate the volume and analyze the prices from the price ladder using Python. He includes the full Python code and the output result, which can be further analyzed using different libraries. The speaker emphasizes the importance of testing the script before executing it to avoid any unnecessary trades. He also shows various symbols, such as the Euro, and how they are named in the code while demonstrating a trading platform.
  
  
• 00:15:00 In this section, the author talks about using MetaTrader 5 and Python to create indicators. They go through some code and explain how to fix errors, and then show how to connect to the market and retrieve data on different assets. However, they note that because it is a weekend the market is closed, so they cannot retrieve much data. They emphasize the importance of sharing code with others and encourage viewers to do so. They also mention the need for volume data for indicators, which is not available for many assets during weekends or holidays.
  
  
• 00:20:00 In this section, the video creator explores additional features that can be added to the indicator, including symbols, and discusses testing for errors by creating a function that returns a blank list if no volumes are available. The creator also demonstrates how to use the MetaTrader5 terminal to check the code and obtain information about orders, positions, and profits, as well as analyze data for possible trading strategies. The video concludes with a call for viewers to share their own codes and links to the video on social media to provide more learning resources for others.

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Python with MetaTrader 5 : creating indicator (part 2)

MetaTrader5 + Python делаем индикатор #2

This tutorial focuses on using Python to obtain historical data and display it in an understandable format using MetaTrader 5. The video provides step-by-step guidance on how to import and initialize connections and retrieve data from MetaTrader 5. The presenter also demonstrates how to generate and compile data, visualize results on a chart, and create candlestick charts using Python. The tutorial concludes with a discussion of how to output data in the form of an indicator for internal calculations and send trading signals. While the presenter notes some challenges and the need for caution when using indicators, she emphasizes the importance of continuing to upgrade programming skills.

• 00:00:00 In this section, the speaker discusses how to use historical data in Python to make indicators on MetaTrader 5. The Euro to Ruble instrument is used as an example, and the speaker explains how to gather and analyze the historical data, which will be displayed on separate web pages. The speaker also mentions that there have been some changes to the platform since the last video and demonstrates how to create a new file called t-44. Overall, the focus is on teaching viewers how to take historical data for an instrument and display it in an easily understandable format.
  
  
• 00:05:00 In this section of the video, the presenter discusses how to use the documentation provided in the MetaTrader 5 IPython integration to create graphs and indicators using Python. The documentation contains a large amount of sample code and integration examples to help developers get started with the integration. However, the presenter notes that there may be some challenges due to updates in the documentation and changes to how certain commands work. The presenter shows how to load and display price data for a particular currency using candlestick charts and outlines the steps involved in creating a new script in MetaEditor. The presenter also notes that if any viewers have information on how to improve the display of the code, she would appreciate hearing from them.
  
  
• 00:10:00 In this section, the focus is on how to obtain data on a financial instrument and display it on a chart using MetaTrader 5 and Python. The video discusses how to utilize updated commands for initialization and making the necessary code changes. The goal is to analyze the code line by line and make modifications to obtain data and display it in charts. The narrator notes that the level of education or experience is not as important as one's ability and willingness to upgrade their skills in programming.
  
  
• 00:15:00 In this section, the tutorial dives into the specifics of connecting to the MetaTrader 5 terminal and using the command "copy rates". The video provides a step-by-step guide to importing and initializing the connection, setting the time zone, and taking data from "copy rates" command. The tutorial also emphasizes that users can modify the code to suit their specific needs and instrument, and includes sample code to provide guidance. The video concludes with a demonstration of how to specify the date when calling the "copy rates" command to get the latest data.
  
  
• 00:20:00 In this section of the video, the presenter continues to work on building an indicator using MetaTrader 5 and Python. They start by taking the code from the documentation to ensure that everything is properly organized. Then, they set the trading instrument to Euro and select the appropriate timeframe and number of bars. The code is then used to generate data, which is then converted into a format that can be analyzed with the pandas library. Finally, the code is compiled to ensure that it is working properly.
  
  
• 00:25:00 In this section of the video, the presenter shows the code for retrieving data from MetaTrader5 and converting it into a format suitable for analysis using other tools like neural networks. Despite encountering an error in the code, they are able to successfully display the data and highlight the potential benefits of using real-time data from MetaTrader5. They also provide a hint for displaying the data on a graph or web page.
  
  
• 00:30:00 In this section of the video, the presenter continues the previous tutorial on creating an indicator with MetaTrader5 and Python. He begins by showing how to import the MetaTrader 5 library and establish a connection to a trading terminal. Then the code downloads historical prices for a chosen financial instrument, saves them to a pandas dataframe, and uses the Plotly library to create charts for the data. The presenter also demonstrates how to plot both line and candlestick charts and provides the necessary code for each. The charts are interactive, and the presenter shows how to zoom in and out on the data.
  
  
• 00:35:00 In this section, the speaker demonstrates how to create candlestick charts within MetaTrader 5 using Python. By changing the method from "candlestick" to "OHLС" and vice versa, users can change the type of chart they are working with. However, the speaker notes that indicators often lag behind the current market trends, so users should approach trading with MetaTrader5 with caution and constantly adjust their strategies. While it is possible to create indicators in Python, the speaker suggests that it may be more nativeto write them in C++.
  
  
• 00:40:00 In this section of the video, the presenter explains how to use the MetaTrader5 platform to formulate calculations and output data in the form of an indicator for internal calculations. Users can choose to output this data as a separate window or directly onto the graph, and the tool can be used to send trading signals. While it may not be clear how to display the created indicator using Python, experimenting and reviewing documentation may be helpful. The presenter also invites viewers to comment and share the video on social media, mentioning that supporting the channel by sponsoring would be appreciated.

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MetaTrader 5 + Python creating indicator #3 Market Depth

MetaTrader 5 + Python делаем индикатор #3 Стакан котировок

The video demonstrates the use of Python to extract data from order books in MetaTrader 5 to create an indicator. The speaker explains how to connect and import data from table orders, as well as discussing packages such as pandas or TensorFlow neural networks for analyzing the data. The video also highlights how Ta-Lib library can be used for calculating additional indicators or data, and the challenges of automating trading. The speaker encourages viewers to share their ideas and questions to create innovative trading solutions.

• 00:00:00 In this section, Oleg Shpagin checks the sound quality and tests a previously-written Python code on MetaTrader5 for creating an indicator using the data from order books. He shows viewers how to initialize the connection and import data from table orders and the order book to be analyzed by other codes using packages like pandas or tensor fob neural networks. Shpagin also demonstrates the program's output of information from each row in the data table for mass data processing.
  
  
• 00:05:00 In this section, the speaker demonstrates how to use Python to extract data from a quote board in MetaTrader5. The data is then used to develop a trading model using neural networks. The speaker explains that one can apply a firewall to control access to the trading application or use ratification to prohibit unauthorized access to the internet. The speaker is currently in the process of creating a trading system and welcomes ideas from traders on this platform.
  
  
• 00:10:00 In this section, the presenter continues his demonstration of how to use Python to create a price chart screen for trading in MetaTrader 5. He explains that he likes using the C++ code because he finds it easier to work with than Python, but he shows how to use a Python library called ' Ta-lib' to perform calculations for additional indicators or data. Ta-lib is a tool that allows the user to avoid writing code and comments in text formats and also provides an import function to bring data into the code. The presenter highlights the advantage that this app can be adjusted for various mobile devices in addition to PCs.
  
  
• 00:15:00 In this section, the speaker shows how to use the Ta-Lib library with Python to gather financial data and use that data to make trading decisions. The speaker demonstrates how to connect to a trading instrument and extract historical data from the market. He also shows how to rename columns in a data table in order to use the data with Ta-Lib library functions. The speaker suggests that viewers leave comments to indicate what they are most interested in seeing in future videos, such as practical applications of using neural networks for trading decisions.
  
  
• 00:20:00 In this section, the speaker discusses the need for Russia to adapt to the rapidly changing trading market and the challenge of automating trading to adjust for these changes. He notes the drawbacks of relying solely on robots and highlights the need to constantly relearn and adjust. The speaker also mentions that neural networks can be useful for predicting the direction of prices but still require constant relearning to remain effective. In conclusion, he encourages viewers to continue sharing their ideas and questions to learn and create innovative trading solutions.

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Connect Python to MetaTrader 5

Connect Python to MetaTrader 5

In this YouTube video, the creator provides a tutorial on how to use Python to connect to the MetaTrader 5 trading platform. They explain step-by-step how to install the necessary libraries, import the required packages, and retrieve data from the platform. The video also includes an example of how to retrieve daily bars and analyze the data using the Pandas library. By looping through the bars and comparing the close and open prices, the creator determines the number of bullish and bearish bars, providing insights into market trends and statistical patterns. This method can be useful for further analysis and decision-making in trading.

• 00:00:00 This section provides a guide on how to connect Python to the MetaTrader 5 trading platform. They outline the necessary steps to ensure a successful connection, including installing the MetaTrader5 library and importing relevant packages such as pandas and numpy. The YouTuber also includes an example of how to retrieve data from the trading platform using the mt5 initialize method and explains why defining time zone variables is important for handling data. The tutorial concludes with a demonstration of how to retrieve daily bars for a specific range using the mt5.copy_rates_range method and displaying it in a readable format.
  
  
• 00:05:00 In this section, the author demonstrates how to collect data from MetaTrader 5's daily bars and convert them into a readable time format using the Pandas library in Python. The YouTuber then shows how to determine the number of bullish and bearish bars by looping through the bars and comparing the close and open prices. The resulting data shows that there were 132 bullish bars and 125 bearish bars, proving that the market is a 50-50 game. This method can be used to further analyze market trends and gain insights into statistical patterns.

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ROBOT FOR MINI BOVESPA INDEX - CLASS 1 - CONNECTING PYTHON WITH METATRADER 5

ROBÔ PARA MINI ÍNDICE BOVESPA - AULA 1 - CONECTANDO PYTHON COM METATRADER 5

The video tutorial showcases the process of connecting Python with Meta Trader to develop a trading robot, highlighting the advantages of Python over other languages and providing step-by-step directions for downloading and importing libraries. Detailed explanations on data retrieval and creating a DataFrame are also included, and the speaker demonstrates how to plot a graph of a specific stock's closing prices while providing historical data for the Ibovespa index. Overall, this tutorial provides valuable insights for viewers interested in developing their own trading robots.

• 00:00:00 In this section of the video, the speaker explains how to connect Python with MetaTrader 5 and develop a trading robot, showcasing his own robot that is nearly ready for testing. The speaker explains the advantages of using Python over other languages, such as the ease of use, broad range of statistics tools, and smaller libraries. He then goes on to explain the steps necessary to connect Python with MetaTrader 5, with directions on downloading Anaconda and MetaTrader 5, installing the necessary packages, and importing the requisite libraries.
  
  
• 00:05:00 In this section, the video tutorial demonstrates how to connect Python with MetaTrader 5, and introduces libraries such as pandas, matplotlib, and datetime to be used for data storage, charting, and date management. The speaker establishes variables for data retrieval from MetaTrader 5, and highlights the importance of correct capitalization and market observation when defining variables for asset consultation. The tutorial includes detailed explanations of the steps required for data retrieval, and the creation of a DataFrame to display the information in a more friendly manner.
  
  
• 00:10:00 In this section, the speaker shows his portfolio's data, including the date, opening price, high, low, closing price, volume, and spread. He then transforms the time into a more friendly format and shows how to plot a graph of the closing prices of a specific stock. He also demonstrates how one can obtain historical data for the Brazilian stock market index, Ibovespa. He concludes by saying that viewers can use this code to connect Python with MetaTrader 5 and begin their own analysis of different assets.

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Creating Pivot Point trading robot in Python with MetaTrader 5 integration

Criando robô de negociação Pivot Point em Python com integração no MetaTrader 5

In this video, the creator demonstrates how to create a trading robot in Python using Pivot Point indicator and integrating it into MetaTrader 5. The video provides instructions on coding the conditions for buying and selling, setting up the robot's configuration for different time frames and trading instruments, and testing its effectiveness by executing and canceling live trades. Additionally, the video offers techniques for quick response to changes in the market when creating a trading robot. The video concludes by encouraging users to use the provided calculations and to reach out to the creator for assistance.

• 00:00:00 In this section, the video creator discusses creating a trading robot in Python using Pivot Points and integrating it with MetaTrader 5. The creator has already written the code and shares it with viewers for them to follow along. The code uses the Pivot Point indicator and sets up conditions for buying and selling. The creator also provides instructions on how to start the robot in real-time in MetaTrader 5 and how to gather information for trading decisions. The final code is available to viewers for reference.
  
  
• 00:05:00 In this section, the creators demonstrate how to integrate their pivot point trading robot into the MetaTrade5 software, allowing users to execute trades automatically according to the pivot point strategy. They explain the formula used to calculate pivot points and demonstrate how to configure the robot's settings for different time frames and trading instruments. They also show how to test and validate the robot's effectiveness by executing a live trade and canceling it afterward. Overall, this section provides a practical tutorial on how to turn a pivot point trading strategy into an automated trading robot.
  
  
• 00:10:00 In this section of the video, the speaker discusses the creation of a trading robot that uses the Pivot Point trading strategy in Python with integration into the MetaTrade5 platform. He explains the function of the code and how it extracts information from the platform's data to make trading decisions based on support and resistance levels. The code also checks for previous trades and decides if it should enter into a new position. The speaker emphasizes the importance of sensitivity in the code to respond quickly to changes in the market.
  
  
• 00:15:00 In this section, the speaker concludes the video by stating that by watching the demonstration, users should have sufficient knowledge to create their own robot trading program using Python and that if they encounter any issues, they can refer to the calculations shown in the video. Users can also observe the trading operations executed on the platform. The speaker suggests using a notebook to follow along with the demonstration and emphasizes the program's ease of use. Finally, the speaker invites users to leave comments and ask questions if they need any assistance with building their own trading program.

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MetaTrader 5 Depth of Market with Python

Realtime MetaTrader 5 DOM (orderbook) plot with Python, Pandas, PyQtGraph and RabbitMQ

This video demonstrates the use of Python, Pandas, PyQtGraph and RabbitMQ in order to display realtime orderbook (DOM).