Just imagine if everything in life were proprietary? You want to speak a language? Pay a licence fee to the company who owns the language. You want to walk through on a street? Pay a toll based on the number of steps you take. Want to see street art, like the above photo? That won't be free. Ludicrous? Yes. Human languages are a product of the work of many humans over millennia. It would be ridiculous for a company to claim to own a language. It would also stifle innovation of society more broadly.
Does this mean that everything should be open sourced in the same way? Well, maybe not. Let's take the example of software. If you spend many years creating software which let's others generate significant profits, should that time you spent always be given away free? It depends!
In recent years, we have seen the the open source movement expand in the software world. People are literally posting their code projects on the internet for free. If you are a businessman this might seem odd. Yet it can make business sense.
Indeed, I wrote about about the benefits of open sourcing your software in a blog post a while back, after I had gone to an open source in finance conference in Frankfurt organised by the ever enthusiastic Python expert Yves Hilpisch. Thomas Wiecki, from Quantopian, outlined the obvious benefits of open source, that the software you produce will end up being better - because you'll have a community of people working on it. Furthermore, you can use open source software to show what you can do, a powerful advert. He also noted that you do not have to open source all your software.
Several weeks later, I've followed up that blog article with some action (rather than just writing about it)! I've open sourced some of my PyThalesians Python financial analysis code library this week. It's taken me a year and hundreds of hours of my time to write my library, so it's certainly not been "free" for me to produce. Yet, I think it's still been beneficial to open up some of the more generic parts of the library. The feedback I have got back so far has been great, so I'm very glad to have done so.
Whilst, I've not included any of my proprietary trading algorithms and some of the more fiddly bits of financial analysis I've written (!), I have included a lot of my code for making it easy to download market data from a multitude of sources like Bloomberg. I've also included a lot of code for making great visualisations too (like below).
I'd encourage you to take a look at the code I've written and hopefully you'll like it. Furthermore, if you are interested in supporting the project through sponsorship, whether directly or indirectly, such as by using the Thalesians to consult for you or through purchasing our research on systematic trading, let me know.
here), mainly on Big Data in Finance and there'll also be an interactive demo of PyThalesians too. You can download PyThalesians code from the GitHub PyThalesians page here.
Like my writing? Have a look at my book Trading Thalesians - What the ancient world can teach us about trading today is on Palgrave Macmillan. You can order the book on Amazon. Drop me a message if you're interesting in me writing something for you or creating a systematic trading strategy for you! Please also come to our regular finance talks in London, New York, Budapest, Prague, Frankfurt & Zurich- join our Meetup.com group for more details here (Thalesians calendar below)
22 Jul - London - Paul Bilokon - Stochastic Filtering (title TBC)
07 Sep - Frankfurt - Saeed Amen/Yves Hilpisch/Thomas Wiecki/Jochen Papenbrock/Miguel Vaz/Adrian Zymolka - Quant Evening (Thalesians/Quant Finance Group Germany)
08 Sep - Zurich - Saeed Amen - How to build a CTA? / interactive Python demo