Quantitative methods you have to know for Macro Econ analysis (Time Series series — ep 1)

Time series is the most common data type in the financial market, and if you are reading this article chances are you are aware how over the past four years the financial markets have been moving quite actively in response to the Fed policies. It gives me more reason to research Macro Econ regimes and dig deeper how policies are formulated based on which numbers and how different financial asset classes respond differently to the same policy. These “stuff” fascinates me so much so that I’m enrolling in another post-grad degree at Columbia University to further the cause.

As the first article of this time series series, I’m going to show you:

1. really comprehensive Macro data source that's readily available in Python.

2. decompose time series into its separate components for better forecasting capability.

Step 1 — Data Preparation

If you are interested in quantitative investment, pandas_datareader is THE data source you have to know about and it allows easy call through a Python function. And I’d suggest you spend sometime playing around with this package to explore its massive power.

pip install pandas_datareader
import pandas_datareader.data as web

In this article, I’m going to introduce you to my favorite Macro guy, Fred, and hopefully you’d find him just as useful.