Something interesting, old thread - page 128

 

Interesting indicator -

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Sampler - indicator for MetaTrader 5

The indicator (i_Sampler.mq5) calculates perfect market entry signals, which can be used for neural network training.

 Sampler - indicator for MetaTrader 5

Sampler - indicator for MetaTrader 5

 Sampler - indicator for MetaTrader 5

The e_CheckSampler.mq5 Expert Advisor is created for checking of the indicator values.
The Expert Advisor uses the data from file, created by indicator.

Sampler
Sampler
  • www.mql5.com
The indicator calculates perfect market entry signals, which can be used for neural network training.
 

Forum on trading, automated trading systems and testing trading strategies

Metatrader 5 versions of indicators ...

Sergey Golubev, 2017.08.31 16:39

Something interesting on this thread:
  1. Stochastic RSI for MT5 - the post 
  2. Stochastic rsi (oma) colored or MT5 - the post:
    - RSI types: Cuttler's RSI; Ehlers' smoothed RSI; Harris' RSI; Rapid RSI; RSI; RSX; Slow RSI
    - levels: floating; quantile; fixed
  3. Round price DOC indicator for MT5 - the post: Added 2 parameters : price (so we can chose the price we would like to use - in the original it is Close) and T3Original (false for Fulks/Matulich calculation which is faster then the original Tim Tillson calculation).

 

Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram

Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram

This article will follow the course of integrating Telegram with MetaTrader 5. We intend to achieve this by crafting a custom Expert Advisor (EA) in the MetaQuotes Language 5 (MQL5) programming language. Our main task is to program a trading assistant that operates in real-time and keeps us in the loop via a chat on Telegram. The Telegram bot that we will build will act like an update server, sending us juicy morsels of information that help us make important trading decisions.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram
Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram
  • www.mql5.com
In this article, we create an Expert Advisor (EA) in MQL5 to send messages to Telegram using a bot. We set up the necessary parameters, including the bot's API token and chat ID, and then perform an HTTP POST request to deliver the messages. Later, we handle the response to ensure successful delivery and troubleshoot any issues that arise in case of failure. This ensures we send messages from MQL5 to Telegram via the created bot.
 

Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram

Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram

Having set the foundation in Part 1, we can now proceed to the next step: transmitting trading signals to Telegram using MQL5. Our newly enhanced Expert Advisor does something quite remarkable: It not only opens and closes trades based on preset conditions but also performs the equally impressive feat of transmitting a signal to a Telegram group chat to let us know a trade was executed. The trading signals themselves have gone through a bit of a makeover, ensuring that the information we send to Telegram is as clear and concise as possible. Our "Chatty Trader" does a better job of talking to the group in Telegram than our previous version, and it does so at the same or faster pace than our old "Chatty Trader" had, which means we can expect to receive signals nearly in real-time as trades are taken or closed.

We will generate signals based on the famous moving average crossover system and relay the generated signals. In addition, if you recall, in part 1 of the series, we had just a single message that could be pretty long, and if someone wanted to add segments to the message, it would result in an error. Thus, only a single message could be sent at a time, and if there were extra segments, they would have to be relayed in different individual messages. For example, sending “A buy signal has been generated.” and “Open a buy order.”, would be either a single long message or two short messages.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram
Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram
  • www.mql5.com
In this article, we create an MQL5-Telegram integrated Expert Advisor that sends moving average crossover signals to Telegram. We detail the process of generating trading signals from moving average crossovers, implementing the necessary code in MQL5, and ensuring the integration works seamlessly. The result is a system that provides real-time trading alerts directly to your Telegram group chat.
 

Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram

Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram

In the previous article, the second part of our series, we carefully examined the process of merging MetaQuotes Language 5 (MQL5) with Telegram for signal generation and relay. The outcome was clear; it allowed us to send trading signals to Telegram and, of course, the necessity to use the trading signals for the whole thing to be worthwhile. So, why must we take the next step in the integration process? What we do in this third part of the series is very much a "next step" in illustrating the potential of merging MQL5 with Telegram in terms of sending trading signals. However, instead of sending just the text portion of the trading signal, we send a screenshot of the chart of the trading signal. It is sometimes better to not only receive a signal that one can act upon but also see the signal setup like price action setups on the chart in a visual representation, in this case, the chart screenshot.

Thus, in this article, we will focus on the specifics of converting image data into a compatible format for embedding in HyperText Transfer Protocol Secure (HTTP) requests. This conversion must happen if we are to include images in our Telegram bot. We'll work through the details of the process that gets us from a chart in MQL5, through the MetaTrader 5 trading terminal to an artfully arranged bot-message with a caption and a chart image as the visually impressive part of our trading notification. This article will be organized into four parts.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram
Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram
  • www.mql5.com
In this article, we create an MQL5 Expert Advisor that encodes chart screenshots as image data and sends them to a Telegram chat via HTTP requests. By integrating photo encoding and transmission, we enhance the existing MQL5-Telegram system with visual trading insights directly within Telegram.
 

Creating an MQL5-Telegram Integrated Expert Advisor (Part 4): Modularizing Code Functions for Enhanced Reusability

Creating an MQL5-Telegram Integrated Expert Advisor (Part 4): Modularizing Code Functions for Enhanced Reusability

In the preceding article of this series, we delved into the process of sending chart snapshots with captions from MetaTrader 5 to Telegram. Our approach, while effective, was rather straightforward and somewhat inflexible. We chained together the components necessary to capture a screenshot, convert or encode it into a message-friendly form, and send it along to Telegram. Although this setup worked, it resulted in a fair bit of code that was repetitive and not all that manageable. So, what can we do to improve this implementation? Move to a more modular codebase! This is the first step toward both a more flexible and a more maintainable system.

In this fourth part of our series, we will focus on enhancing the reusability of our program through code modularization. We will undertake a detailed discussion on the principles of code modularization and, more specifically, how these principles apply to our project. Following that, we will present step-by-step instructions for reorganizing our existing mql5 script into separate, well-defined functions. In the end, you will have the choice of using the old, monolithic program or a new, modular Expert Advisor (EA) with the same output.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram
Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram
  • www.mql5.com
In this article, we create an MQL5 Expert Advisor that encodes chart screenshots as image data and sends them to a Telegram chat via HTTP requests. By integrating photo encoding and transmission, we enhance the existing MQL5-Telegram system with visual trading insights directly within Telegram.
 

Creating an MQL5-Telegram Integrated Expert Advisor (Part 5): Sending Commands from Telegram to MQL5 and Receiving Real-Time Responses

In this article, part 5 of our series, we continue integrating MetaQuotes Language 5 (MQL5) with Telegram, focusing on refining the interaction between MetaTrader 5 (MT5) and Telegram. Previously, in part 4 of the series, we laid the groundwork for sending complex messages and chart images from MQL5 to Telegram, establishing the communication bridge between these platforms. Now, we aim to expand on that foundation by enabling the Expert Advisor to receive and interpret commands directly from Telegram users. Instead of the Expert Advisor controlling itself by generating signals, opening market positions, and sending predefined messages to our Telegram chat, we will control it from the Telegram chat by relaying commands to the Advisor which will, in turn, decode the commands, interpret them, and send back intellectual and appropriate request replies and responses.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 5): Sending Commands from Telegram to MQL5 and Receiving Real-Time Responses
Creating an MQL5-Telegram Integrated Expert Advisor (Part 5): Sending Commands from Telegram to MQL5 and Receiving Real-Time Responses
  • www.mql5.com
In this article, we create several classes to facilitate real-time communication between MQL5 and Telegram. We focus on retrieving commands from Telegram, decoding and interpreting them, and sending appropriate responses back. By the end, we ensure that these interactions are effectively tested and operational within the trading environment
 

Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons

Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons

This article dives into making our MetaQuotes Language 5 (MQL5) Expert Advisor more responsive and interactive for users through Telegram. In the fifth installment of this series, we laid the groundwork for our bot by implementing the ability to respond to commands and messages from Telegram and by creating custom keyboard buttons. In this segment, we’re upping the interactivity of our bot by integrating inline buttons that trigger various actions and respond dynamically to user inputs.

The article is organized to address a few key components. First, we will introduce inline buttons in Telegram bots, including what they are, their usefulness, and the benefits they provide over other methods of creating a bot interface. Then, we will transition to discussing how to use these inline buttons in MQL5, so that they can be part of our Expert Advisor's user interface.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons
Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons
  • www.mql5.com
In this article, we integrate interactive inline buttons into an MQL5 Expert Advisor, allowing real-time control via Telegram. Each button press triggers specific actions and sends responses back to the user. We also modularize functions for handling Telegram messages and callback queries efficiently.