In the coming weeks, we’ll focus on some super-fun time-series data, including accessing and working with time-indexed data and building analyses, models, and visualizations.
Before that, let’s light that time-series candle with a quick, simple simulation of Netflix stock prices and returns (ticker: NFLX). A lot can be gleaned from assessing underlying fundamentals and growth / momentum to value a company in the medium and long term. However, day-to-day stock price movements are notoriously difficult to predict, adopting the path of a random walk, similar to that of genetic drift, an animal foraging, electron transport through a metal, bacterial movement, firing neurons, and particle diffusion through a liquid or gas.
Today, we’ll simulate NFLX price and returns using historical closing price data to approximate NFLX day-to-day movement. Here, we’ll use the IEX API, which is an excellent source of financial data. You can sign up for a free individual account, though there are tiered priced individual and business offerings with increasingly high API call allowances. We’ll also work with the Yahoo Finance API (free) in a future post.
Table of Contents
- Introduction
- Install and Import Packages
- Access Data using IEX API Call
- Pre-processing
- Exploratory Data Analysis
- Random Price Walk Using a Normal Distribution
- Simulate NFLX Equity Price and Returns
Stay tuned for some fun time-series explorations, analysis, models, and visualizations.
If there’s something you’d like to explore, give us a shout!
Till next time,
Rish
