I write this as precautionary tale intended to Engineering undergraduate students interested in the areas of Data Science and Artificial Intelligence (initially given as a guest lecture at Mexico’s ITAM video-link in Spanish)
Data Science is supposed to be the intersection of Computer Science (hacking, understanding databases), Math and Statistics (advanced modelling) and Domain Knowledge (Finance, for this tale). Each discipline traditionally required its own career syllabus, and in real life is almost impossible to find someone who is proficient in all three fields.
In my experience, I have noticed that some people might be very strong in two out…
(2021–02–16: Update — I added a link to the Yahoo Financial charts on the First table; clicking it takes you to the price plot for the stock)
Using the code published in (Demystifying) Sentiment Analysis in Finance I developed an automatic script that reads the ‘hot’ posts in r/wallstreetbets, identifies the stock tickers, and then looks for SEC Form 13F that also mentions them. I do not include the sentiment score as it uses a movie review off-the-shelf analyser completely incompatible with Financial Sentiment.
The output of the code also highlights many caveats on automatic analysis: there are many ‘false…
This article is the second in a series co-authored by Gerardo Lemus from Quanto and Kumar Suppiah of Project Jarvis. Project Jarvis is a pre-incorporation stealth mode digital asset trading startup supported by Quanto.
Gerardo does the quantitative heavy lifting while Kumar tries to break it down into layman’s terms with a dash of dry humor. Our co-authored articles are published by each individual author and you may find it reproduced here.
It is a universally acknowledged truth that any serious article worth its salt should eventually contain a cat meme (How Cats took over the Internet), and as a…
What do wine snobs, and Chinese anti-corruption laws have to do with failed statistical arbitrage? Just by reading the previous line aloud I am sure most of the readers already have either fallen sleep or clicked out of this blog.
I have written in the past about the perils of finding spurious correlations in Finance, and particularly about the inability of machine learning algorithms (and some very smart people) to identify the causal model that drives the prices of financial assets. Below we can see a typical model-breaking example, but with tastier assets than subprime mortgage backed derivates.
This article is the first in a proposed series co-authored by Gerardo Lemus from Quanto and Kumar Suppiah of Project Jarvis. Project Jarvis is a pre-incorporation stealth mode digital asset trading startup supported by Quanto. Gerardo does the quantitative heavy lifting while Kumar tries to break it down into layman’s terms with a dash of dry humour. Our co-authored articles are published by each individual author and you may find it reproduced here.
Nassim Taleb popularized the idea of ‘black swans’ in Finance (Unfortunately, it has nothing to do with Natalie Portman’s movie). …
what am I going to do with a set of numbers that I cannot prove makes me an owner of anything?
Well, there is one possible answer:
That ‘set of numbers’ could be data (encrypted or public) that you want to store for an unlimited amount of time (at least as long as miners exists) — hey, think of all those pictures in your smartphone (“How can I store my digital photos for ever ?” pops up frequently)
I recently stumbled with the following blog: “You Don’t Need a Diversified Crypto Portfolio to Spread Risk: Here’s Why”. While the diversification premise is debatable, I found the history of the evolution of crypto markets very interesting, as it has compressed in type various regimes (quotes from the blog above):
In 2016, the correlation of prices between each currency was very loose. In fact, if I recall correctly, you couldn’t even purchase Ripple except through this sketchy website called Gatehub. And I think you had to use fiat to purchase, but because that would…