Lazy Trading

Learn Computer and Data Science through Algorithmic Trading

23 July 2021

The big idea about Lazy Trading

In my opinion financial trading performed with a final aim to multiply funds is just a non-productive activity linked with big risks. It is, in principle, bad for society as there is no value added simply because no new goods or services are created. The Lazy Trading motivates everyone to only use various technologies and data developed within Algorithmic Trading Ecosystem to learn Computer and Data Science.

By the way, This is not a trading advice! so just relax and have a fun reading for the next 5 minutes!

Google that: “Hot to get rich?”

To start with, I would ask you to open any of your favorite search engines. Please try to type something like:

  • “How to get rich”,
  • “How to make money”…

I am almost sure that top search result will not be about how to develop the great idea, working hard, risking your own capital, start your own business, fail, resist, start again… Not! The top search will probably be about some quick and risky ways to make money. Most likely around trading, perhaps something linked to Crypto. And for sure one topic found will be about Algorithmic Trading

Why people believe in Algorithmic Trading?

They believe that their winning expectancy will be dominating the loosing expectancy. These people would strive to create systems that will generate lot’s of trades. These trading systems would be ‘trained’ on the past data and typically tested on the independent data to verify the result. Some people will also suggest to find long-term financial inefficiency and leverage this in combination with an Algorithmic Trading

Still, why it’s bad for society!

Typical situation: One person is risking 1 dollar, getting 99 dollars from the broker, instruct broker to buy or sell the asset, close the position after pre-defined sub-cent price move called ‘pips’, return 99 dollar, commission and get the few dollar profit or loss, repeat this many time during the day in an automated way…

Now, think about it:

  • What is produced?
  • What is the added value?
  • What are the risks?

How to use it and getting value?

It’s probably the best thing to learn Computer and Data Science!

Just a few comments why I believe that data and infrastructure can be used to scale up your skills and apply them in a real world situations:

  • Perfect data to play with
  • Free software
  • Does not require expensive infrastructure
  • Possible to play with it, iterate, experiment with different ideas
  • See the result
  • Risk free using Demo accounts
  • Use free basic education resources

What is there exactly?

In fact software and data that exists out there is available for free with a download click. Data is stored in the servers in the structured way, base functions and entire programming languages are created to manage all that! A lot of forums with information and often free articles and tutorials. More over, it’s possible to try all that in a very risk free environment using Demo accounts using available broker…

Brilliant! It’s just important not to loose your patience and to convert that “gold” into useful things

Why do I call it Lazy Trading?

Well, there would always be people who want to try Algorithmic Trading. Unfortunately this is not simple, could be quite time consuming as well. The idea here is to provide ideas for those people on how they can do algorithmic trading more efficiently. The idea is to use top level of supervision allowing to replace trader activities that should be done manually otherwise. The goal is to automate what can be automated leaving to the trader just possibility to supervise and maintain such trading ecosystem.

That should provide some psychological relaxation from the fact that Artificial Intelligence will take care about the situation… but also should help to reduce the longterm effort in maintaining the system.

Decision Support System

The idea is to use building blocks and to create what I call “Decision Support System”.

Conceptually decisions are required to:

  • Predict the future price change
  • Evaluate strategy
  • Deside which system is working well which not
  • Check for other important factors like macro-economic news releases

Lazy trading is the concept that would help anyone to set up the direction, build this Decision Support Ecosystem, improve it while keeping everything under Version Control

Why am I creating this series?

First of all this series was created to bring together series of tools that I created while researching the Algorithmic Trading in the first place. I wanted to keep this in the structured form to eventually bring that as a complete project one can reproduce with a minimum effort. In fact, while creating a course Instructor is almost obliged to follow predefined structure of the course. Well as reader may understand, this helping to the Author to be more disciplined and accurate - things that are so difficult to keep in mind!

Second reason is about the possibility to learn, practice and obviously share the concepts and methods with students in the transparent way.

Third reason is that concepts used in the course will be valuable for real value-added projects in the industry. Concepts that students can take and apply for the real world applications or at least being able to demonstrate competence to get a good job

What only benefit I can guarantee?

Even though no specific trading strategy or market inefficiency is being promoted author believes that these courses are bringing the entire framework trader can use to perform his/her own research. This framework can be expanded to suit more specific needs. On top of that valuable learning would appear naturally thought replication of proposed methods. These general purpose methods could be applied elsewhere to bring real value to society.

This is the only benefit I can guarantee - is to learn Computer and Data Science through Trading.

To Support this journey

Should you wish to donate some coins to support this project [please optionally indicate your Udemy name]:

BTC:

speakom

32UTZmNZPm7S1oJbMMnxtnnEAEudADa3hs

ETH:

speakom

0xf17ba25C018EaB2A1D19f5Db12E1f3C0DB1Ebf3d

DOGE:

speakom

DC72x5FzcKAhC2rHs96V9hRsQGC7D9jQeE

Conclusion

Hopefully this little article has answered question about the idea of Lazy Trading. How to start with that? Make sure to read specific article about each course of the series.

Thank you for reading!!!


Interests: industry, teaching, science, history, travels. I also like to travel with family and watch/play ice hockey