Discussion of article "Building a Social Technology Startup, Part I: Tweet Your MetaTrader 5 Signals"
There are so many wonder articles, and MQL5 Platform has everything that one need to build amazing trading strategies and much more.
You see this as a way for FX trading I see it as a global market intelligence network the only thing lacking from the Platform is "Natural Language Programming Integration" and "Big Data" to speed up processing of written languages.
There are so many wonder articles, and MQL5 Platform has everything that one need to build amazing trading strategies and much more.
You see this as a way for FX trading I see it as a global market intelligence network the only thing lacking from the Platform is "Natural Language Programming Integration" and "Big Data" to speed up processing of written languages.
Thank you for your comment! The main idea of this article is that robotic trading may not completely satisfy some traders. If this is your case, then you can consider some other approaches (decision support tools).
For example, you can combine the power of MetaTrader 5 with a human audience of experts who can make decisions on trading signals, and then analyze the knowledge obtained. One solution is capturing experts' observations in a web ontology.
A recommended reading on this subject is Roger Penroe's book "The Emperor's_New_Mind" -> http://en.wikipedia.org/wiki/The_Emperor's_New_Mind
Thank you for your comment! The main idea of this article is that robotic trading may not completely satisfy some traders. If this is your case, then you can consider some other approaches (decision support tools).
For example, you can combine the power of MetaTrader 5 with a human audience of experts who can make decisions on trading signals, and then analyze the knowledge obtained. One solution is capturing experts' observations in a web ontology.
A recommended reading on this subject is Roger Penroe's book "The Emperor's_New_Mind" -> http://en.wikipedia.org/wiki/The_Emperor's_New_Mind
Using Support Vectors in conjunction with Natural Language to gauge a person who is speaking or even a SEC report and output data along with correlated Market movements updating to a non centralized or centralized location that could be used to interpret global movement around the world is plausible an what i see here is a movement in the right direction to achieve multiple models for test scenarios. Your on the right track keep up the good work and as for you business model I think it will work..
Good point! Well, I am not familiar with Support Vectors so right now I cannot understand very well how they could be used in this SDSS.
Regarding the "Natural Language Programming Integration" problem, it can be solved by first capturing knowledge into a web ontology (with RDFs or OWL) and then later publishing a SPARQL endpoint to perform "Natural Language" queries, such as Wikipedia's -> http://dbpedia.org/snorql/
By the way, there is another interesting resource on this topic entitled Predicting Crowd Behavior with Big Public Data
Good point! Well, I am not familiar with Support Vectors so right now I cannot understand very well how they could be used in this SDSS.
Regarding the "Natural Language Programming Integration" problem, it can be solved by first capturing knowledge into a web ontology (with RDFs or OWL) and then later publishing a SPARQL endpoint to perform "Natural Language" queries, such as Wikipedia's -> http://dbpedia.org/snorql/
By the way, there is another interesting resource on this topic entitled Predicting Crowd Behavior with Big Public Data
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New article Building a Social Technology Startup, Part I: Tweet Your MetaTrader 5 Signals has been published:
This article aims to illustrate, through a practical example, how you can communicate an MetaTrader 5 terminal with an external web service. We are tweeting the trading signals generated by an Expert Advisor.
This idea comes from a particular conception of automatic trading called computer-assisted trading. In a nutshell, the computers of the XXI century do not have cognitive abilities, but they are very good at processing information and executing data. So why do not we build computer systems using human brains as filters to make decisions? This approach is inspired on the Human-based computation (HBC) paradigm, hence focuses on building decision support tools, rather than coding decision maker algorithms.
I had initially thought about creating an RSS feed with the trading signals generated by my EAs (it is assumed that there is a medium or long term underlying trading system, this idea is not valid for automatic scalping systems). A human with access to the feed should validate my robotic signals according to the circumstances of the moment, just before putting them on the market. However, I soon realized that everything could be even more social, and thought to myself, 'Why not publish my trading signals on the Twitter?' This led me to develop this Social Decision Support System.
Figure 1. SDSS Architecture
By the way, if you plan to create a technology startup related to FX trading this article may help you to take some ideas. It can be seen as a technical guide to build a commercial SaaS (Software as a Service) based on an SDSS.
This text is long, so I've decided to split it into two parts. The first one focuses on the web service architecture, the communication protocol used between the MetaTrader 5 terminal and the Twitter app, and finally the web app's integration with Twitter. The second part will cover the MQL5 layer of the network diagram shown above, which is intended to consume our Social Decision Support System's RESTful web service. Specifically, we will code an MQL5-RESTful framework in the same way as explained in the article MQL5-RPC. Remote Procedure Calls from MQL5: Web Service Access and XML-RPC ATC Analyzer for Fun and Profit.
This article is also social, so I encourage you to write your comments to help to continue with the second part.
Author: Jordi Bassaganas