Conteúdo do Curso
Introduction to Portfolio Management with Python
Introduction to Portfolio Management with Python
The 5-factor Model
In the previous two chapters, we discovered the Capital Asset Pricing Model, which uses a single factor, and then transitioned to the Fama-French Model, which incorporates three factors.
However, there is still potential to identify additional factors that could enhance predictions.
One suggestion is to expand the standard Fama-French Model with three factors, by introducing two new factors:
- Profitability factor (RMW or Robust Minus Weak) - which distinguishes between companies with strong profitability and those with weak profitability;
- Investment factor (CMA or Conservative Minus Aggressive) - which highlights the relationship between investment strategies and stock returns.
RMW is computed by taking the average return of robust companies (companies with high profitability) and subtracting the average return of weak companies (companies with low profitability).
CMA is computed by taking the average return of conservative companies (companies that less tend to invest in growth opportunities and focus more on stable projects with lower risk) and subtracting the average return of aggressive companies (companies that invest heavily in growth and expansion, usually taking on more risk in hopes of higher returns).
As well as before, all necessary data could be found by the following link.
Tarefa
- Define corresponding linear regression model with necessary data.
- Fit this model.
- Make forecast on the next two days.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
The 5-factor Model
In the previous two chapters, we discovered the Capital Asset Pricing Model, which uses a single factor, and then transitioned to the Fama-French Model, which incorporates three factors.
However, there is still potential to identify additional factors that could enhance predictions.
One suggestion is to expand the standard Fama-French Model with three factors, by introducing two new factors:
- Profitability factor (RMW or Robust Minus Weak) - which distinguishes between companies with strong profitability and those with weak profitability;
- Investment factor (CMA or Conservative Minus Aggressive) - which highlights the relationship between investment strategies and stock returns.
RMW is computed by taking the average return of robust companies (companies with high profitability) and subtracting the average return of weak companies (companies with low profitability).
CMA is computed by taking the average return of conservative companies (companies that less tend to invest in growth opportunities and focus more on stable projects with lower risk) and subtracting the average return of aggressive companies (companies that invest heavily in growth and expansion, usually taking on more risk in hopes of higher returns).
As well as before, all necessary data could be found by the following link.
Tarefa
- Define corresponding linear regression model with necessary data.
- Fit this model.
- Make forecast on the next two days.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
The 5-factor Model
In the previous two chapters, we discovered the Capital Asset Pricing Model, which uses a single factor, and then transitioned to the Fama-French Model, which incorporates three factors.
However, there is still potential to identify additional factors that could enhance predictions.
One suggestion is to expand the standard Fama-French Model with three factors, by introducing two new factors:
- Profitability factor (RMW or Robust Minus Weak) - which distinguishes between companies with strong profitability and those with weak profitability;
- Investment factor (CMA or Conservative Minus Aggressive) - which highlights the relationship between investment strategies and stock returns.
RMW is computed by taking the average return of robust companies (companies with high profitability) and subtracting the average return of weak companies (companies with low profitability).
CMA is computed by taking the average return of conservative companies (companies that less tend to invest in growth opportunities and focus more on stable projects with lower risk) and subtracting the average return of aggressive companies (companies that invest heavily in growth and expansion, usually taking on more risk in hopes of higher returns).
As well as before, all necessary data could be found by the following link.
Tarefa
- Define corresponding linear regression model with necessary data.
- Fit this model.
- Make forecast on the next two days.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
In the previous two chapters, we discovered the Capital Asset Pricing Model, which uses a single factor, and then transitioned to the Fama-French Model, which incorporates three factors.
However, there is still potential to identify additional factors that could enhance predictions.
One suggestion is to expand the standard Fama-French Model with three factors, by introducing two new factors:
- Profitability factor (RMW or Robust Minus Weak) - which distinguishes between companies with strong profitability and those with weak profitability;
- Investment factor (CMA or Conservative Minus Aggressive) - which highlights the relationship between investment strategies and stock returns.
RMW is computed by taking the average return of robust companies (companies with high profitability) and subtracting the average return of weak companies (companies with low profitability).
CMA is computed by taking the average return of conservative companies (companies that less tend to invest in growth opportunities and focus more on stable projects with lower risk) and subtracting the average return of aggressive companies (companies that invest heavily in growth and expansion, usually taking on more risk in hopes of higher returns).
As well as before, all necessary data could be found by the following link.
Tarefa
- Define corresponding linear regression model with necessary data.
- Fit this model.
- Make forecast on the next two days.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo