[See Description] Accessing Fundamental company Data - Programming for Finance with Python - Part4 | Summary and Q&A

37.7K views
June 29, 2015
by
sentdex
YouTube video player
[See Description] Accessing Fundamental company Data - Programming for Finance with Python - Part4

TL;DR

This tutorial discusses the inclusion of fundamental data in algorithmic trading and highlights the differences between fundamental data and quantitative data.

Install to Summarize YouTube Videos and Get Transcripts

Key Insights

  • ❓ Most algorithmic traders rely on quantitative data derived from historical prices, which is inherently biased.
  • ❓ Fundamental data provides valuable insights into a company's value and growth potential.
  • 👻 Quantopian allows access to a vast database of fundamental metrics for incorporation into trading strategies.
  • 🦔 Incorporating fundamental data can give traders an edge over those who rely solely on quantitative data.
  • ❓ Obtaining fundamental data programmatically has been challenging, but it can be done with platforms like Quantopian.
  • 🎰 Fundamental data can be used in machine learning algorithms to improve trading strategies.
  • 🥳 Price-to-book ratio and price-to-earnings ratio are two fundamental metrics commonly used in trading strategies.

Transcript

what is going on everybody Welcome to the fourth Finance with python using quantopian and zipline tutorial in this tutorial we're going to be talking about the inclusion of fundamental data so fundamental data is fundamentally different than what most people are doing any sort of uh algorithmic trading on for the most part so most people when they ... Read More

Questions & Answers

Q: How is fundamental data different from quantitative data in algorithmic trading?

Fundamental data pertains directly to a company's value, such as price-to-book ratio or historical growth, while quantitative data is derived from historical prices and patterns.

Q: Why is it important to incorporate fundamental data in trading strategies?

Fundamental data provides a more accurate measure of a company's value, allowing traders to make informed decisions based on the company's financial health and growth potential.

Q: How can fundamental data be obtained programmatically?

Platforms like Quantopian provide access to a database of fundamental metrics, like Morning Star, which can be queried using SQL Alchemy queries.

Q: Can fundamental data be used in machine learning algorithms?

Yes, fundamental data can be used to train classifiers and incorporate machine learning techniques into trading strategies.

Summary & Key Takeaways

  • Most algorithmic traders rely on quantitative data derived from historical prices, but fundamental data, which directly relates to a company's value, is a more accurate measure.

  • Obtaining fundamental data programmatically has been challenging, but platforms like Quantopian allow access to a vast database of fundamental metrics.

  • By incorporating fundamental data into trading strategies, traders can gain an edge over others who rely solely on quantitative data.

Share This Summary 📚

Summarize YouTube Videos and Get Video Transcripts with 1-Click

Download browser extensions on:

Explore More Summaries from sentdex 📚

Summarize YouTube Videos and Get Video Transcripts with 1-Click

Download browser extensions on: