Stock Analysis: Create a Buy Signal Filter using R and the Quantmod Package

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En este proyecto guiado, tú:

How to pull down Stock Data using the R Quantmod Package

Ability to quickly calculate daily returns on stocks chosen

Ability to create Buy/Sell Signals based on RSI Index

Clock2 Hours
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

In this 1-hour long project-based course, you will learn how to pull down Stock Data using the R quantmod package. You will also learn how to perform analytics and pass financial risk functions to the data. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que desarrollarás

Stock ModellingQuantmodR ProgrammingData AnalysisCreating Buy Filters

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Task 1: In this task the Learner will be introduced to the Course Objectives, which is to how to pull Stock Data for analytics using the R quantmod Package and create a Buy Filter (Trading Rule). There will be a short discussion about the Interface and an Instructor Bio.

  2. Task 2: The Learners will learn how to pull Stock Data and construct an xts object using the getsymbols function in the quantmod package.

  3. Task 3: The Learner will explore the lag function in R and how it is used to calculate a percentage stock change for a specified period.

  4. Task 4: The Learner will build a histogram that will help in the threshold for the model Buy signal.

  5. Task 5: The Learner will create a new vector using a For Loop over the data passing the Buy signal parameters. This will return a binary.

  6. Task 6: The learner will tie the Buy Signals to the data. A graph will then be created that will show both the buy signals and how the Signal performed on the specified data.

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso




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