Trading strategy, resources, and advice from someone who has done it before.

Video of a trading robot

How to Build Your Own Robot

Photo by Nicolas Hoizey on Unsplash Having trouble thinking of a strategy? Not sure which APIs and packages to use? I built a stock day trading program github repo from scratch and wanted to share some helpful resources as well as some advice on how to get started. I know starting a new project, especially in a foreign domain, is challenging, and I hope this article can help flatten the learning how to determine the trend in binary options. There are video of a trading robot projects you can work on, so why work on this?

Disclaimer: this is not meant to represent financial advice. Any investments you make using the algorithm, strategy, or ideas below is at your own risk. I am not liable for any consequences related to or caused by the information contained in this article.

1. Incorporate technologies of interest

How to get started : I provide some example psuedocode to help you get started. Resources : a list of github repos, websites, other medium articles, youtube videos, books, and podcasts that helped me tremendously.

A backend developer wanting to provide end users an API to get signals from your algorithm of when to buy and sell?

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Hopefully you get the idea. Collaborative Easily collaborate with others by breaking your program into areas of interest. I guess any project can be collaborative, but given the complexity of this challenge, people can choose their interest and simply tackle those challenges.

Sometimes its hard to collaborate because people get lost in the details and forget the overall objective.

How to Build a Stock Trading Bot from Scratch

Whether you are building a data pipeline, creating dashboards, or building some machine learning model, the objective is clear. Frankly, from a learning standpoint, its a win-win. If you make money, think how you can make more money or lose less. If you are losing money, think how you can make more money or lose less.

Always room for improvement and all effort amounts to video of a trading robot same measure.

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Sometimes with other projects, its hard to know whether your changes are beneficial. Success may rely on user feedback or just a matter of opinion. This project, in contrast, is great because success and failure is clear. Nevertheless, its important to remember that markets are infinitely complex.

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Most everyone invests in the stock market. Its easy understanding the goal of buying low and selling high.

Potentially Lucrative but unlikely You can make money building a successful algorithm that trades for you.

И вдруг впереди словно зажглась заря. Темнота стала рассеиваться, сменяясь туманными сумерками. Стены туннеля начали обретать форму. И сразу же из-за поворота выехала миниатюрная машина, ослепившая ее фарами.

When I first started on this project a few months ago, I was convinced that building something lucrative is mostly luck and chance. I still mostly feel that way, but I believe it is possible to build something profitable. Making money should not be the goal of this project, but its a nice side-benefit and aspirational goal.

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Infinitely Complex This ties in with my earlier point about easily incorporating any technology. Infinite complexity means you will never be done. I am viewing this as glass half full. There will always be new strategies, technology, indicators, and metrics to incorporate and test. Interpret that how you will, but I find that interesting and exciting. How to get started? COM on Unsplash Develop a strategy that works.

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Fact is that you will iterate. Defining a strategy will help provide some framework that can be improved upon. This is an example strategy that I created for trading stocks: I explained this strategy in another article I wrote about the initial performance of my stock trading algorithm. Now iterate upon this strategy and provide more details.

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Once you feel like you have something you can easily implement, start thinking about how to implement. This might be more specific than is currently needed during the pseudocode phase. How will you implement your strategy?

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What APIs, packages, and other resources help or are necessary to implement this pseudocode? Is this even possible? For news stories, I am thinking about doing some web scraping using Python modules Beautiful Soup and Selenium and Scrapy. I wrote my initial program in Jupyter Notebook and used Github as my repo.

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Now at this point, you may be tempted to start delving into new technologies and platforms such as incorporating some cloud or using airflow or kubeflow, but I recommend focusing on implementing as quickly as possible. If are interested in incorporating other technology and are a bit more experienced, you can do Proof of Concepts POCs for the technologies you plan to use before incorporating the technology. If you are working in a group, some might focus on just doing POCs and seeing what works best.

What we will discuss here, the rules and the steps are valid on the MT5 as well.

Iterate: fail-fast Simply going through the process of implementing the psuedocode will teach you so much. You begin to understand where the bottlenecks are and improvements in design. And perhaps have learned about new APIs, packages, or frameworks that can be useful.

Keep in mind, nothing is like trading live. Read one of my earlier articles which describes some of the challenges I faced when building my algorithm. Resources Photo by Fikri Rasyid on Unsplash Below are some of the resources that helped me get started and might help you too.

Again, some might provide specific tangible advice while others provide you some domain knowledge and expertise. Note: I will continuously update the list below with useful resources. Github Repos.