August 2024
Intermediate to advanced
374 pages
8h 44m
English
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Predicting Stock Prices
Perhaps one of the most obvious applications of time-series analysis is forecasting the direction of markets. Given enough historical data, you should be able to predict the future performance of a given equity or market, right? As you’ll find out later in this chapter, the problem of forecasting markets is exceptionally difficult. If it were as easy as throwing a neural network at the problem, everybody would be doing it. Despite the challenges, attempting to forecast stock prices is a good exercise in time-series analysis and a good demonstration of the pitfalls of putting too much faith in a model.
In this example, you’ll be working with the historical stock data for 30 companies in the Dow Jones Industrial Average ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.