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Introduction to Financial Portfolio Management with Python
Introduction to Financial Portfolio Management with Python
Challenge: Annualized Return and Risk
What is Annualization?
First, let’s define what is annualization in terms of return and risk.
Note that there is other term with similar name, but another meaning:
So, in terms of previous example, the main difference between them is that annual return/risk is exact return of an asset for a specific year/risk associated with this return, while annualized return/risk is return/risk over different time periods converted into equivalent annual return.
Another aspect, why annualization is important - is standartization.
Let's define it:
Annualized Returns
Let's assume next notation:
N
- length of time period we are working with in years;R
- return over entire period of time;R_a
- annualized return.
Then we can compute annualized return using the following expression:
Alternatively, we can assume that N
represents the number of months in our period, which will give us the following expression:
Coming back to the previous example with stocks of Nvidia and AMD, here is a code, which will help us compute annualized returns for them, using corresponding formulas:
# Computing annualized return for Nvidia Nvidia_annualized = (1 + 0.27) ** (12/6) - 1 print('Nvidia: \n') print(Nvidia_annualized) # Computing annualized return for AMD AMD_annualized = (1 + 3.93) ** (1/5) - 1 print('AMD: \n') print(AMD_annualized)
Annualized Risk
In terms of risk, which is measured by standard deviation, the annualized value can be calculated using the following expression:
Here:
σ
- basic risk;σ_a
- annualized risk;T
- time period, used for computing risk.
So, for example, if σ
denotes monthly risk - then T = 12
and annualized risk could be computed using the next expression:
Or, in case of daily risk σ
, to annualize we use T = 252
, since it is an approximate number of trading days in a year (excluding weekends and holidays), and the following expression is used for computing:
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.
¿Todo estuvo claro?
Challenge: Annualized Return and Risk
What is Annualization?
First, let’s define what is annualization in terms of return and risk.
Note that there is other term with similar name, but another meaning:
So, in terms of previous example, the main difference between them is that annual return/risk is exact return of an asset for a specific year/risk associated with this return, while annualized return/risk is return/risk over different time periods converted into equivalent annual return.
Another aspect, why annualization is important - is standartization.
Let's define it:
Annualized Returns
Let's assume next notation:
N
- length of time period we are working with in years;R
- return over entire period of time;R_a
- annualized return.
Then we can compute annualized return using the following expression:
Alternatively, we can assume that N
represents the number of months in our period, which will give us the following expression:
Coming back to the previous example with stocks of Nvidia and AMD, here is a code, which will help us compute annualized returns for them, using corresponding formulas:
# Computing annualized return for Nvidia Nvidia_annualized = (1 + 0.27) ** (12/6) - 1 print('Nvidia: \n') print(Nvidia_annualized) # Computing annualized return for AMD AMD_annualized = (1 + 3.93) ** (1/5) - 1 print('AMD: \n') print(AMD_annualized)
Annualized Risk
In terms of risk, which is measured by standard deviation, the annualized value can be calculated using the following expression:
Here:
σ
- basic risk;σ_a
- annualized risk;T
- time period, used for computing risk.
So, for example, if σ
denotes monthly risk - then T = 12
and annualized risk could be computed using the next expression:
Or, in case of daily risk σ
, to annualize we use T = 252
, since it is an approximate number of trading days in a year (excluding weekends and holidays), and the following expression is used for computing:
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.
¿Todo estuvo claro?
Challenge: Annualized Return and Risk
What is Annualization?
First, let’s define what is annualization in terms of return and risk.
Note that there is other term with similar name, but another meaning:
So, in terms of previous example, the main difference between them is that annual return/risk is exact return of an asset for a specific year/risk associated with this return, while annualized return/risk is return/risk over different time periods converted into equivalent annual return.
Another aspect, why annualization is important - is standartization.
Let's define it:
Annualized Returns
Let's assume next notation:
N
- length of time period we are working with in years;R
- return over entire period of time;R_a
- annualized return.
Then we can compute annualized return using the following expression:
Alternatively, we can assume that N
represents the number of months in our period, which will give us the following expression:
Coming back to the previous example with stocks of Nvidia and AMD, here is a code, which will help us compute annualized returns for them, using corresponding formulas:
# Computing annualized return for Nvidia Nvidia_annualized = (1 + 0.27) ** (12/6) - 1 print('Nvidia: \n') print(Nvidia_annualized) # Computing annualized return for AMD AMD_annualized = (1 + 3.93) ** (1/5) - 1 print('AMD: \n') print(AMD_annualized)
Annualized Risk
In terms of risk, which is measured by standard deviation, the annualized value can be calculated using the following expression:
Here:
σ
- basic risk;σ_a
- annualized risk;T
- time period, used for computing risk.
So, for example, if σ
denotes monthly risk - then T = 12
and annualized risk could be computed using the next expression:
Or, in case of daily risk σ
, to annualize we use T = 252
, since it is an approximate number of trading days in a year (excluding weekends and holidays), and the following expression is used for computing:
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.
¿Todo estuvo claro?
What is Annualization?
First, let’s define what is annualization in terms of return and risk.
Note that there is other term with similar name, but another meaning:
So, in terms of previous example, the main difference between them is that annual return/risk is exact return of an asset for a specific year/risk associated with this return, while annualized return/risk is return/risk over different time periods converted into equivalent annual return.
Another aspect, why annualization is important - is standartization.
Let's define it:
Annualized Returns
Let's assume next notation:
N
- length of time period we are working with in years;R
- return over entire period of time;R_a
- annualized return.
Then we can compute annualized return using the following expression:
Alternatively, we can assume that N
represents the number of months in our period, which will give us the following expression:
Coming back to the previous example with stocks of Nvidia and AMD, here is a code, which will help us compute annualized returns for them, using corresponding formulas:
# Computing annualized return for Nvidia Nvidia_annualized = (1 + 0.27) ** (12/6) - 1 print('Nvidia: \n') print(Nvidia_annualized) # Computing annualized return for AMD AMD_annualized = (1 + 3.93) ** (1/5) - 1 print('AMD: \n') print(AMD_annualized)
Annualized Risk
In terms of risk, which is measured by standard deviation, the annualized value can be calculated using the following expression:
Here:
σ
- basic risk;σ_a
- annualized risk;T
- time period, used for computing risk.
So, for example, if σ
denotes monthly risk - then T = 12
and annualized risk could be computed using the next expression:
Or, in case of daily risk σ
, to annualize we use T = 252
, since it is an approximate number of trading days in a year (excluding weekends and holidays), and the following expression is used for computing:
Tarea
In this task you need to:
- Compute annualized return
R_annualized
with a given returnR
for a 7 month, by specifying necessary power into formulap
. - Compute annualized risk
σ_annualized
with a given riskσ
for a 5 month, by specifying necessary time periodT
.