Forecasting the Future: Predicting Stock Prices with ARIMA
Predicting the stock market is basically the Holy Grail of finance. Everyone wants to know what’s going to happen tomorrow. In Chapter 2, we look at a classic tool for this: the ARIMA model.
Predicting the stock market is basically the Holy Grail of finance. Everyone wants to know what’s going to happen tomorrow. In Chapter 2, we look at a classic tool for this: the ARIMA model.
Chapter 2 opens with a quote from Fred Brooks: “Conceptual integrity is the most important consideration in system design.” Written decades ago. Still true. Maybe more true now than ever.
Previous: Getting Started with Hadoop 3: What’s New and Why It Matters
In the last post, we talked about all the cool new features in Hadoop 3. Now, let’s actually build something. Sridhar Alla’s book gives a solid walkthrough on setting up a single-node cluster. If you’re on Linux, this is pretty straightforward.
In the first chapter of Data Analytics for Finance Using Python, we get into the nitty-gritty of portfolio management using something called K-Means clustering.
Diana starts Chapter 1 with a warning. Reading a book about systems thinking will not teach you systems thinking. Just like reading a book about tennis will not teach you tennis. You have to go outside and play. Fair enough. But you still need to know the rules before you step on the court.
Previous: Big Data for the Rest of Us
Hadoop has been around for a while, but version 3 is where things get really interesting. If you’ve worked with Hadoop 1 or 2, you know it was solid but had some pain points. Sridhar Alla’s book kicks off by looking straight at what’s changed.
So, I’ve been thinking about how the stock market works and why it feels like such a gatekept club. It turns out, if you know a bit of Python, you can actually peek behind the curtain.
I just finished reading “Learning Systems Thinking” by Diana Montalion (O’Reilly, 2024, ISBN: 978-1-098-15133-1) and I want to share what I got from it. Chapter by chapter. Like a retelling with my own thoughts mixed in.
So, you’ve heard about big data. It’s everywhere. But how do you actually handle it? If you’re looking for the OG of big data platforms, you’re looking at Hadoop. And honestly, it’s still the foundation for almost everything we do in data today.