![]() ![]() However, if people think that Python is as good as R as far as finance goes, well…so far, the going isn’t going to be easy. So, I’m hoping that his courses on Python will actually get my Python skills to the point that they get me more job opportunities (hopefully quickly). Everyone that praises any line of code on this blog…you have Vijay to thank for that. Basically, I view that time in my career as akin to a second master’s degree. In fact, I started this blog shortly after I left Optimal. I worked for Vijay in 20, and essentially, he made my R coding (I didn’t use any spaces or style in my code.) into, well, what allow you, the readers, to follow along with my ideas in code. It’s taught by Lionel Martellini of the EDHEC school as far as concepts go, but the lion’s share of it–the programming, is taught by the CEO of Optimal Asset Management, Vijay Vaidyanathan. However, rather than take multiple Python courses not particularly focused on quant finance, I’d rather redirect any reader to just *one*, that covers all the concepts found in, well, just about all of the DataCamp finance courses–and more–in its first two (of four) chapters that I’m self-pacing right now. The most interesting python for finance course I found there, was actually Dakota Wixom’s (a former colleague of mine, when I consulted for Yewno) on financial concepts, which covers things like time value of money, payback periods, and a lot of other really relevant concepts which deal with longer-term capital project investments (I know that because I distinctly remember an engineering finance course covering things such as IRR, WACC, and so on, with a bunch of real-life examples written by Lehigh’s former chair of the Industrial and Systems Engineering Department). concepts that so many reading this blog are familiar with. There are also a couple of courses on the usual risk management/covariance/VaR/drawdown/etc. There’s another course that tries to apply machine learning methodology to finance by measuring the performance of prediction algorithms with R-squareds, and saying it’s good when the R-squared values go from negative to zero, without saying anything of more reasonable financial measures, such as Sharpe Ratio, drawdown, and so on and so forth. While a course in basic time series manipulation is alright, I suppose, there is one course that just uses finance as an intro to numpy. In contrast, DataCamp’s Python for Finance courses have not particularly impressed me. I know for a fact that I’ve used Ross Bennett’s PortfolioAnalytics course teachings in a professional consulting manner before, quantstrat is used in industry, and I was explicitly told that my course is now used as a University of Washington Master’s in Computational Finance prerequisite. The R/Finance courses ( of which I teach one, on quantstrat, which is just my Nuts and Bolts series of blog posts with coding exercises) are of…reasonable quality, actually. ![]() ![]() However, for those that think Python is all that and a bag of chips, I hope to be able to disabuse people of that.įirst and foremost, as far as actual accessible coursework goes on using Python, just a quick review of courses I’ve seen so far (at least as far as DataCamp goes): ![]() (If you know of an opportunity, here’s my resume.) So, I’m trying to get my Python skills going, hopefully sooner rather than later. This post will be a quickie detailing a rather annoying…finding about the pandas package in Python.įor those not in the know, I’ve been taking some Python courses, trying to port my R finance skills into Python, because Python is more popular as far as employers go. ![]()
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