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Autor Tópico: Practical Financial Investment Analysis In R And Tidyquant  (Lida 52 vezes)

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Practical Financial Investment Analysis In R And Tidyquant
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.63 GB | Duration: 3h 3m

Conduct Financial Analysis and Portfolio Assessment With RStudio and tidyquant. Obtain & Work With Real Financial Data

What you'll learn
LEARN To Obtain Real World Financial Data FREE From Yahoo and Quandl
BE ABLE To Read In, Pre-process & Visualize Financial Data
LEARN How To Use Different R-based Packages For Financial Analysis (including tidyquant)
USE Common Financial Analytics Technique For Financial Analysis
Requirements
Prior Familiarity With The Interface Of RStudio and Package Installation
Be Able To Carry Out Data Reading And Pre-Processing Tasks Such As Data Cleaning In R
Interest In Working With Quantitative Financial Data
Description
THIS IS YOUR COMPLETE GUIDE TO FINANCIAL DATA ANALYSIS IN R!This course is your complete guide to analyzing real-world financial data using R All the main aspects of analyzing financial data- statistics, data visualization, time series analysis and machine learning will be covered in depth.If you take this course, you can do away with taking other courses or buying books on R-based data analysis. In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By proficiently analysing financial data in R, you can give your company a competitive edge and boost your career to the next level. LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE:Hey, my name is Minerva Singh, and I am an Oxford University MPhil (Geography and Environment), graduate. I recently finished a PhD at Cambridge University. I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and I have produced many publications for international peer-reviewed journals. Throughout my research, I realised almost all the R data science courses and books out there do not account for the multidimensional nature of the topic. So, unlike other instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science-related topics! With this course, in around 3 hours, you'll get familiar with some of the most common R packages for obtaining, cleaning, visualizing and analyzing financial data for making data-driven decisions (either for yourself or your company)Among other things:· Obtain long-term stock market data from platforms such as Yahoo and Quandl· Learn to visualize temporal financial data and produce clear graphs and visualizations · Implement standard analysis techniques, including moving averages and the Sharpe ratio.You'll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in the R Programming Language. My course will help you implement REAL DATA methods obtained from different sources. Many courses use made-up data that does not empower students to implement R-based data science in real-life.After taking this course, you'll easily use the common time series and financial analysis packages in RStudioYou'll understand the underlying concepts to understand what algorithms and methods best suit your data. We will work with real data and you will have access to all the code and data used in the course. JOIN MY COURSE NOW!
Overview
Section 1: Welcome To the Course:Practical Financial Analysis in R
Lecture 1 Introduction To Course
Lecture 2 Data and Code
Lecture 3 Install R and RStudio
Lecture 4 Different Data Types
Section 2: Preliminary Data Processing in R
Lecture 5 Read CSV and Excel Data
Lecture 6 Read in Data from Online HTML Tables-Part 1
Lecture 7 Read in Data from Online HTML Tables-Part 2
Lecture 8 Editing Data Within R
Lecture 9 Data Cleaning in R
Lecture 10 More Data Cleaning
Lecture 11 Introduction to dplyr for Data Summarizing-Part 1
Lecture 12 Introduction to dplyr for Data Summarizing-Part 2
Section 3: Obtaining Financial Data in R
Lecture 13 Let's Get the Tesla Stock Prices
Lecture 14 Obtaining More Stocks and Data
Lecture 15 Getting Started With Quandl
Lecture 16 Quandl Financial Data
Lecture 17 Get Cryptocurrency Data
Section 4: Basic Visualisations and Processing Financial Data With Tidyquant
Lecture 18 Data Visualisation:Conceptual Foundations
Lecture 19 Basic Visualisations For Financial Data
Lecture 20 Some More Basic Visualisations
Lecture 21 What Are the Returns?
Lecture 22 Visualise The Returns
Lecture 23 Stock Data At Different Time Scales
Section 5: Analysing Financial Performance
Lecture 24 Simple Moving Average (SMA)
Lecture 25 Moving average convergence/divergence (MACD)
Lecture 26 Lets Look At the Annual Returns
Lecture 27 Identify Most Frequent Large Positive Returns
Lecture 28 What Is the Sharpe Ratio?
Lecture 29 Identify Risk-Adjusted Returns With the Sharpe Ratio
Lecture 30 Compare To a Baseline
Lecture 31 Capital Asset Pricing Model (CAPM)
Anyone Who Wants To Become Proficient In Financial Data Analysis Working With Real Life Data,Anyone Who Wants Master Financial Data Analysis In RStudio,Anyone Who Wants To Become An Expert Financial Data Scientist


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