Discussing the article: "Category Theory in MQL5 (Part 14): Functors with Linear-Orders"
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Check out the new article: Category Theory in MQL5 (Part 14): Functors with Linear-Orders.
This article which is part of a broader series on Category Theory implementation in MQL5, delves into Functors. We examine how a Linear Order can be mapped to a set, thanks to Functors; by considering two sets of data that one would typically dismiss as having any connection.
Ocean tide data is published and made available to the public by the National Oceanic and Atmospheric Administration (NOAA) through their website which can be viewed here. The data logs the height of ocean tide off of a datum, four times a day. The time and altitude of the tide at each time are all that gets recorded for each day all year round. Here is a preview:
All oceans are divided into 4 regions with tide values gathered from a host of measuring stations within each region. For the West Coast of North and South America for example, that spans from South America Chile all the way to Alaska, there are 33 stations. For our analysis we will pick data gathered from Monterey station in California for the year 2020.
The NASDAQ is a well-established stock exchange but we are looking at it here primarily as an index, that is composed of quite a few tech companies such as MSFT, AAPL, GOOG, and AMZN, that are all headquartered in California. This index can be traded from most brokers so its price feed will inform our category as we see if the market cap of these companies that have revolutionized industries and exemplify California’s innovation spirit are in any way linked to the ocean tide data gathered off of its coast.
Author: Stephen Njuki