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 2
Financial Data Extraction and Cleaning
Content Locked
Section 2
Extracting Data from the Web
Not all the datasets are available for download in CSV, text, or Excel formats. In this video, you will learn to scrape online data, which can be used to detect trends, perform analysis, or generate a database. - Understand the HTML tags and CSS styles to select relevant data - Read HTML in R and use the rvestfunctions to extract relevant information using HTML and CSS tags - Import information stored in tables on webpages and convert them to data frames for analysis