Machine Learning analysis and forecasting on the SPDR® S&P 500® ETF Trust using Python
Recently I graduated from the Data Science Intensive at Flatiron School — it’s a program colloquially referred to as a bootcamp (or is it boot camp?). This is my first article since graduation and much has happened since then, especially on the job search front. But that’s for another post, this post is a summary of my final project.
Interviewing tips and resources
In Part 1 we looked at networking, networking, and networking. And searching for and applying to jobs. In this installment, we look at what to do when you’ve secured an interview. How do you sell yourself and live to tell the tale?
Interviewing skills aren’t constant. At my best a few years back, my interviewers congratulated me on deftly handling their questions designed to “shake” me, and I got the job. At other times, I was stumped by relatively simple questions that I wasn’t ready for; in one case I got the job, because the rest…
Job search progress, tips, and resources
In my last article I described the process before the Job Search Start Date (JSSD) — the date at which the job search officially starts post graduation from the Flatiron School Data Science immersive program. Now that all the preparatory work has been completed, it’s time to delve into things for real. My official job search start date — June 28, 2021.
Multitasking while finding gainful employment
After graduating from the Flatiron Data Science immersive program, we were encouraged to take some time off from coding to relax and celebrate our achievement. I took advantage of that for… a few hours? I then went right back to my project — I had to fix a few things I noticed during the presentation, adjust some models using updated data, and create another projection for EOY — all while it was still fresh.
But even before graduation, each of us had already connected with our individual Career Coach. With our weekly meetings coming up…
A foray into Time Series Analysis using SARIMAX to predict GameStop stock price using EOD data
As mentioned in Part 1 and Part 2 of my series on GameStop, this is no ordinary stock. The highest short interest in history led to the first great squeeze, rising some 2000% from last year’s prices, before settling back down around $40. Then, because there was still structural short interest that could not be fully covered, the stock “squoze” a second time (a smaller gamma squeeze), though not quite as high, and also has not fallen back down as low.
So you’re home because of the pandemic, or because you negotiated a sweet deal like in The 4-Hour Workweek, or possibly something in between.
You’ve got your MacBook Pro circa 2020, or perhaps 2015, but no one has to know. You’ve got not one but two external monitors, because you know it increases productivity by 35.5%. You’ve got your standing desk (or at least an ergonomic chair), favorite mason jar for water, perhaps a plate of sliced apples or mangoes, and you’re ready to get shit done.
How do large flows of capital in options trading impact stock price?
As discussed last time, the rapid and seismic price fluctuations in GameStop’s stock price have had significant ripple effects on the market at large, enough to cause massive deleveraging before stabilizing. In early February, when the turmoil died down and the stock settled in the $40–50 range, most people assumed the squeeze was over.
What effect does a short squeeze have on the broader market?
The understanding is that various institutions (“shorts”) were betting that GameStop’s stock (GameStock?) would decrease in value and perhaps that the company would go under. This embattled brick and mortar video game retailer has been suffering from the overall trend of digitalization. When the Covid pandemic hit in 2020 and the country entered a deep lockdown, the…
Finish of lip balm, rider of public transit, grower of collagen, maker of music, geeker of tech, and occasional sciencer of data.