Get startedGet started for free

Time series variation

1. Time series variation

In this scenario, I am a new investment analyst working for a financial firm. I’m working with a new client who does not have much of a background in investing. Being a data-driven individual, I plan to show the different kinds of variation and risk profiles of two potential securities. Here I have a Power BI workbook loaded with two datasets for the different securities. Both of these datasets will record different metrics about each stock on every trading day, including the final price for each day. Let’s first look at the data for Norwegian Cruise Lines (ticker: NCLH). If we plot the close price over each day, we can understand how much variation we see. Loading the data into a line chart, we can see a fairly seasonal behavior for the stock, where the price increases in winter and decreased in summer. This makes logical sense, as the cruise industry is seasonal based on weather and tourist demand. To quantify this, let’s calculate a quick column regarding the daily variation that the stock experiences. In DAX, this is: Daily Variation = (NCLH[High] - NCLH[Low]) / NCLH[Close] This will give us a high-level understanding of the risk for this seasonal dataset over time. We can see that, on average, the NCLH stock will vary by about 3% daily. If we can buy during the low season and sell during the high season, then this will work in our favor. Let’s contrast this with a security that is supposed to be much more stable. In particular, we will look at an ETF managed by Vanguard with the ticker VOO. This ETF represents the entire S&P 500 index, which means that we will be able to model the entire stock market at an aggregate level. Similarly, we will plot the close price of this ETF over each day. We can see that the overall upward trend of the close price is much more consistent and visually stable than the NCLH stock. We can confidently say that the VOO close price models a positive secular trend, meaning that it will generally increase over time. If we calculate the same daily variance metric for this fund, we get a daily variance of around 1%, indicating that this is a less risky investment.

2. Let's practice!