Book Image

Developing Financial Analysis Tools [Video]

By : Atmajitsinh Gohil
Book Image

Developing Financial Analysis Tools [Video]

By: Atmajitsinh Gohil

Overview of this book

<p><span id="description" class="sugar_field">As most of the data on the web or residing in a database is not structured in the right way, the course will assist viewers in developing skills to manipulate, transform, and evaluate raw input data. Through the concept of tidy data and visualization tools, viewers will be able to analyze trends and study the financial markets. </span></p> <p><span id="description" class="sugar_field">Once users have developed a good understanding of financial markets and financial data, the next three sections (3, 4, and 5) will introduces users to the concepts of basic statistics, time series analysis, and forecasting. Viewers will use a variety of basic R functions and forecast package to understand statistics and perform time series analysis.</span></p> <p><span id="description" class="sugar_field">By the end of this volume users will be able to use R, learn the use of Shiny apps, understand the concept of tidy data, and generate R markdown files for sharing information.</span></p> <h2><span class="sugar_field">Style and Approach</span></h2> <p><span class="sugar_field"><span id="trade_selling_points_c" class="sugar_field">This course is shows how to build finance models and helps analyst solve their quantitative finance problems.</span></span></p>
Table of Contents (5 chapters)
Chapter 4
Introduction to Time Series Modeling
Content Locked
Section 4
Stationarity and Autocorrelation in R (Continued)
The objective is to introduce the Box- Pierce test, Ljung-Box test and understand the concept of Partial Autocorrelation. - Explain the concept of Box-Pierce test and Ljung-Box test to test for autocorrelation in time series data - Understand Partial Autocorrelation function - Learn to perform Box-Pierce test, Ljung-Box test and calculate Partial Autocorrelation in R