Data Science for Investing and Trading

Name: Data Science for Investing and Trading
Rating: 4.0 (15 reviews)

Introduction to free APIs, data analytics and powerful visualizations using python - Jupyter Notebooks included

Created byQuant- Trading

Last updated 11/2024

English

What you'll learn

Download data from APIs that have public information such as Yahoo Finance, Federal Reserve FRED,SEC Edgar, OECD, FDIC, The World Bank, etc
Perform basic analytic calculations such as mean and median return, volatility, correlation, maximum drawdown, etc
Visualize the information in powerful and impacful charts.
Put all the information together to be able to analyze how a stock or any financial asset has performed in the past and give a view about it.

Course content

5 sections • 33 lectures • 4h 58m total length

Quick Introduction2:50
Introduction4:29

Yahoo Finance API10:45
In this lecture we will learn how to download data from the Yahoo Finance API.
Federal Reserve - Fred API5:36
In this lecture we will learn how to download data from the Federal Reserve - FRED API.
World Bank API11:33
In this lecture we will learn how to download data from the World Bank API.
OECD API12:52
In this lecture we will learn how to download data from the OECD API.
EUROSTAT API11:13
In this lecture we will learn how to download data from the EUROSTAT API.
EDGAR API12:07
In this lecture we will learn how to download data from the EDGAR API.
FINRA API7:03
In this lecture we will learn how to download data from the FINRA API.
FDIC API9:10
In this lecture we will learn how to download data from the FDIC API.
CHARLES SCHWAB API10:26
In this lecture we will learn how to download data from the Charles Schwab API.
APIs assignment

Mean and Median Returns21:58
In this lecture we will learn how to calculate mean and median returns. You will also learn how to transform a dataset from daily data to weekly or monthly data. You will learn how to make a groupby or pivot table using pandas. You will about calendar effects when calculating returns. You will learn how to assign categories using a novel method.
Cumulative Return6:12
In this lecture we will learn how to calculate cumulative returns. We will learn how to create a dictionary of DataFrames and store information for different assets.
Volatility7:20
In this lecture we will learn how to calculate the volatility of stocks' returns.
Correlation9:19
In this lecture we will learn how to calculate correlation for pairs of stocks' returns.
Portfolio Return and Volatility10:12
Maximum Drawdown4:28
In this lecture we will learn how to calculate maximum drawdown. This means, the return from previous peak. People use this metric a lot for trading and investing.
Basic analytics assignment

Cumulative Return Chart19:31
In this lecture we will learn how to plot cumulative returns using matplotlib library.
Heatmap Return Chart13:42
In this lecture we will learn how to make a heatmap using the returns per year from different assets.
Heatmap - Holding periods returns
Treemap Chart9:21
In this lecture we will learn how to make a treemap chart.
Candlestick Chart6:25
In this lecture we will learn how to make a candlestick chart like those you find on tradingview or tradingeconomics.
Disperssion Chart5:29
In this lecture we will learn how to make a disperssion chart. It is very usefull to show how volatile a stock has been throught the years.
Bar Chart10:27
In this lecture we will learn how to make a bar chart to plot returns and describe them.
Histogram9:58
In this lecture we will learn how to make a histogram for returns.
Boxplot7:54
In this lecture we will learn how to make a boxplot.
Historical Simulation5:59
In this lecture we will learn how to make a historical simulation chart. We will apply the same concepts to plot a cumulative return chart as we learnt in the first lecture of this topic, but now we will take cumulative returns per year.
Treemap - Market Cap
Two Axis Chart9:53
In this lecture we will learn how to make a chart with two axis. It is useful to plot different quantities, such as earnings and stock's price.
Geographical Chart15:44
In this lecture we will learn how to make a geographical chart. You can plot data into a map of different countries.
Wordcloud6:33
In this lecture we will learn how to make a Wordcloud. This is a chart to visualize words in a text.
Dynamic Chart15:24
In this lecture we will learn how to make a dynamic chart. This is kind of a movie. Here we will show the evolution of the returns of 3 stocks.
Visualizations assignment

Example 1 - Tesla Stock in July 20241:38
Here you can watch what happened to Tesla stock during July 2024 and some analysis around that event.
Example 2 - Dollar General Stock in August 20241:24
Here you can watch what happened to Dollar GEneral stock during August 2024 and some analysis around that event.
Example 3 - JP Morgan Stock since 2009 until 20241:17
In this lectura you can watch the total return of JP Morgan stock compared to some of its peers. You can also watch the evolution of earnings and earnings per share, and the weight of the stock on the financials index.

Requirements

Basic python knowledge like installing the program and its main libraries.
Basic financial concepts like what is a stock.

Description

This Introductory Data Science for Investing and Trading course is designed to teach you 3 main things using python:

1) Download data from public APIs such as Yahoo Finance, The World Bank, EUROSTAT, SEC Edgar, FINRA, etc.

2) Perfom some basic analytics using python, like calculating mean and median returns, volatility, correlation or maximum drawdown. Along the way you will learn basic commands for pandas, numpy and other libraries.

3) Make powerful and nice visualization for your data and calculations using libraries such as Matplotlib, Plotly or Seaborn.

We have organized the course in those 3 main topics. In each of them you will have complementary exercises that will help you better understand the concepts. For each lecture we provide a jupyter notebook, so you can reproduce the examples in your computer as well.

If you are a financial analyst this course will help you a lot, since you will leverage your financial skills with useful python scripts. This course can also help traders, portfolio managers, financial advisors and other financial professionals who want to increase their productivity, process data better and make more impactful presentations using powerful charts.

You just need very basic python knowledge. If you know how to install python and its basic libraries you can follow this course. So, don't hesitate to jump in and start learning with us.

Who this course is for:

Financial analyst who want to learn useful python applications.
Financial advisor who wish to better comunicate with their customers showing powerful visualizations.
Independent traders and portfolio managers who would like to know how to download information from public APIs for free.

Data Science for Investing and Trading

What you'll learn

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Course content

Introduction2 lectures • 7min

Download Data from APIs9 lectures • 1hr 31min

Basic analytics6 lectures • 59min

Data Visualization13 lectures • 2hr 16min

Examples of financial analysis3 lectures • 4min

Requirements

Description

Who this course is for: