🌎 Full Course: Check out the full beginner course on Forex trading on this Finxter page (5 video lessons).
As a Python beginner, or anything else new that we dive into, everything is fresh and exciting for a while and we have no problem staying motivated to do the work and move ahead.
It’s no wonder you can stay fired up when you are learning the most popular language, in a field that looks promising for years to come, and its innovations will shape the future. That’s exciting!
There’s a book that summarizes the next step in your journey, whether it be Python, Forex, business, freelancing, or anything else. It deals with what most people call, “being at the intermediate level.”
It’s called “The Dip”, by Seth Godin. Like most “self-help” type books, even though this one is only around 100 pages, it could have been done in 10 or 15. In this case though, the author gets an “A+” for the concept.
The idea that after the honeymoon, there will be a period of uncertain struggle on where to go next. Python has the mother of all dips.
To wrap up this beginner’s guide, I want to help you find your way through the dip and come out the other side a success. That “way” is in the title – “Practical Projects.”
Doing a project for someone who doesn’t know how, or have the time to do it themselves, is a great way to put your Python skills to the test.
The great thing about freelancing your skills, is you never know what someone is going to need, and this can give you a great variety of projects.
PRO TIP: Don’t wait until you “feel” ready. You will never feel ready – what you need is confidence – by doing some real work, learning from your mistakes, and not making them again.
Getting started on a platform like Upwork is simple and you will know which projects you can handle, and which ones you can’t – besides, it’s good for you to take a couple that will push your skills and require you to learn how to complete them.
Here are a few more Ideas for some real-world projects:
We went through some simple examples of what you can do with data earlier in the series. Let’s break down a sample in detail:
- Think about a subject that interests you, and where you can find data collections for that topic.
- Do a search and find some downloadable files from their collections.
- Pick a file that suits your project, download the CSV, (I hope you’re using Anaconda and Jupyter), clean it up and organize it, then see what types of patterns, if any, you can identify. I grabbed historical data on interest rates from the Fed’s website for my last analysis. There is so much information out there for free that we will never be able to cover a tiny percentage of it. So narrow it down to your specific needs.
- Form a hypothesis – “Is there a correlation between the EUR/USD and WTI?” In light of recent global events, one would be safe in questioning crude oil’s affect on the entire world.
- Do a comparison – Do you remember in a previous lesson when I demonstrated how to overlay one instrument with another on your charts? This is a simple way to look for correlation. Remember, correlation can be positive or negative.
- Look to see if one or the other seems to “lead” its partner. This can be a great way to see into the future – so to speak.
- If your theory looks promising, question if there is a way to quantify and automate the information using Python. This would also be a good time to start digging into machine learning. Use Python to streamline the process and set alerts.
This is a hypothetical situation I created as an example. Do not trade any theory from anyone without thoroughly testing it yourself.
Sources for Datasets
- Governments collect data and make it available to the public on their websites. Records of everything from NFP to GDP, and weather events can be found with a little effort.
- Central banks, the IMF, and the World Bank also issue reports and data on a variety of economic indicators and predictions created by their own experts.
- Be wary of “advice” sites that are trying to sell you something – look for facts gleaned from statistics and research instead.
We have already discussed how to choose a broker, and did some analysis together on the subject. With the regulations in place these days, it’s really easy to find one that is legit. It will boil down to personal preference in the end. Make sure you feel comfortable with your choice, and that they have responsive customer service so you can communicate easily.
As a beginner, just like with Python, it’s important to start getting some experience while you’re learning to code your own bots. Using a ready-made bot on a demo account is the best way to get going and see if automated trading is right for you.
REMEMBER: Don’t make it all about the money just yet – the knowledge you’re getting in the process is the real value. If you have followed the steps in this series, you should already be on your way to safely making money with Python.
For all of you who have stuck it out until the end of our beginner series, I’m going to give you some analysis that will demonstrate the many different ways to go about your trade planning – they’re endless, which is what makes Forex so interesting. No matter your style, you can find a system that fits.
In the accompanying video, I’m going to give some high-level tips and analysis on the EUR/USD pair that we have been using in the series, and explain what actually makes currency values change.
Check out the video, and it has been a pleasure sharing this information with you.
Here’s to good trading and good luck!