I visited Paris several months ago before Christmas. I had been there many times. Despite that, I had never visited Notre-Dame. There was always some excuse why I hadn’t gone. Too far. Too near. Takes time. And so on. However, finally on this last trip I did take the time to visit. It was truly impressive to see it in person, and to marvel at the workmanship and skill of the medieval stonemasons who built it, as well as the later additions in the nineteenth century such as the spire by Eugène Viollet-le-Duc. It was very sad to see the fire at Notre-Dame break out this week. It was clearly lucky that there was no loss of life and furthermore that the firefighters bravely managed to save a large part of the building for future generations, a symbol for Paris and France.
The events of this week did make me think about the whole idea of delaying things. There will always be an excuse not to do something. I’m not purely talking about it from a personal perspective, in terms of travel, like in my example, but in terms of our professional lives. It can become easy to become lulled in the routine of it, and to (sorry to use such a tedious cliche) break outside of our comfort zone at work.
Finance is obviously no different as an industry, in that it continually develops. The difficulty is that whilst procrastination and doing exactly what you’ve done is the path of least resistance in the short term, the industry itself motors on. If I think about my own career, whilst it’s been centred around currency markets, the way that I look at them today has evolved significantly. I’ve forced myself to refresh my skillset over time.
At the start of my career I dabbled in Matlab and Excel (and Java too). The datasets I used were typically relatively small and were usually easy to use time series. Today, I’ve moved over in Python, and have been using it happily for nearly 5 years. I have to admit though I wish I had started using Python earlier, as it would have saved me a lot of wasted time before, playing with Excel.
In the past few years, I’ve ended up using a myriad of datasets which I don’t think I could have ever imagined 15 years ago, such as news and Twitter, which wasn’t even invented when I started working in currency markets (this is probably a good opportunity plug The Book of Alternative Data on this subject, which I’m co-authoring with Alexander Denev). I’ve also recently worked in the area of transaction cost analysis, which is a comparatively new area for me, and I’ve developed tcapy, a Python based library for transaction cost analysis. There is of course a lot still left to learn for me, and I want to get more into using machine learning more and also to get a better understanding of a lot of the other Python libraries out there.
If you’re currently working in finance, whether you’re in sales, trading or research, and want to learn new skills like Python or want to know how alternative data can help you, now is the time! There’s no point putting it off! I often get questions from folks in finance about how to learn Python and quant tools more broadly.. if that sounds like you, and you’ve got questions, feel free to drop me a message to ask me.