May 2024
Beginner to intermediate
496 pages
13h 15m
English
Content preview from Deep Learning Tools for Predicting Stock Market Movements
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
6Various Model Applications for Causality, Volatility, and Co-Integration in Stock Market
Swaty Sharma
Mittal School of Business, Lovely Professional University, Phagwara, Punjab, India
Abstract
Causality, volatility, and co-integration are fundamental concepts in econometrics and financial research, playing a crucial role in understanding the dynamics of financial markets. This chapter explores various models and their applications for analyzing causality, volatility, and co-integration. An overview of these concepts is provided and discusses how different models have been utilized to investigate their implications. This chapter covers a range of methodologies, including time series analysis, vector autoregression, GARCH models, and co-integration analysis. Additionally, this chapter examined real-world applications of these models in finance and economics, highlighting their contributions to risk management, portfolio optimization, and market efficiency. The findings presented in this chapter contribute to a deeper understanding of the dynamics of financial markets and provide valuable insights for practitioners and researchers.
Keywords: Stock market, econometric models, co-integration test, granger causality test, volatility test
6.1 Introduction
The study of financial markets and their complex dynamics has been a subject of great interest and significance in the field of finance. Financial econometrics provides valuable tools and methodologies to analyze and understand ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.