【Basic】Operation of MATLAB Financial Modeling Toolbox

# 2.1 Data Import and Export

### 2.1.1 Importing Data from Text Files

MATLAB offers various functions to import data from text files, including `importdata`, `textscan`, and `dlmread`. The `importdata` function can automatically detect the delimiter in the text file and convert it into a matrix or a struct. The `textscan` function allows for more flexible control over the import process, including specifying data types and rounding rules. The `dlmread` function is specifically designed for importing data from delimited text files and supports various delimiters.

% Importing data from a text file
data = importdata('data.txt');

% Using textscan to specify data types
data = textscan('data.txt', '%s %f %d', 'Delimiter', ',');

% Using dlmread to import delimited data
data = dlmread('data.txt', ',');

# 2. MATLAB Financial Modeling Toolbox Basic Operations

### 2.1 Data Import and Export

#### 2.1.1 Importing Data from Text Files

MATLAB provides the `importdata` function for importing data from text files. This function supports various file formats, including `.txt`, `.csv`, and `.xls`.

% Importing data from a text file
data = importdata('data.txt');

% Displaying the imported data
disp(data);

**Logical Analysis:**

* The `importdata` function reads the text file and stores its content in the `data` variable.
* The `disp` function displays the imported data.

**Parameter Explanation:**

* `'data.txt'`: The path to the text file to be imported.
* `data`: The variable that stores the imported data.

#### 2.1.2 Importing Data from a Database

MATLAB can import data from a database using the `database` toolbox. This toolbox provides functions for connecting to and querying various databases, such as MySQL, Oracle, and SQL Server.

% Connecting to a database
conn = database('my_database', 'username', 'password');

% Executing a query and obtaining results
sqlquery = 'SELECT * FROM my_table';
results = fetch(conn, sqlquery);

% Closing the database connection
close(conn);

**Logical Analysis:**

* The `database` function establishes a connection to the database and returns a `conn` object.
* The `fetch` function executes the specified SQL query and returns the results.
* The `close` function closes the database connection.

**Parameter Explanation:**

* `'my_database'`: The name of the database.
* `'username'`: The username for the database.
* `'password'`: The password for the database.
* `sqlquery`: The SQL query to be executed.
* `results`: The variable that stores the query results.

### 2.2 Data Analysis and Visualization

#### 2.2.1 Data Statistical Analysis

MATLAB provides a wealth of functions for performing data statistical analysis, including `mean` (average), `median` (median), `std` (standard deviation), and `corrcoef` (correlation coefficient).

% Calculating data statistics
mean_value = mean(data);
median_value = median(data);
std_value = std(data);
corr_matrix = corrcoef(data);

**Logical Analysis:**

* The `mean` function calculates the average value of the data.
* The `median` function calculates the middle value of the data.
* The `std` function calculates the standard deviation of the data.
* The `corrcoef` function calculates the correlation coefficients between the data.

**Parameter Explanation:**

* `data`: The data to be analyzed.
* `mean_value`: The variable that stores the average value.
* `median_value`: The variable that stores the median value.
* `std_value`: The variable that stores the standard deviation.
* `corr_matrix`: The variable that stores the correlation coefficient matrix.

#### 2.2.2 Data Visualization

MATLAB offers various functions for data visualization, including `plot` (line graph), `bar` (bar chart), and `scatter` (scatter plot).

% Plotting a line graph
figure;
plot(data);
title('Data Plot');
xlabel('Index');
ylabel('Value');

% Plotting a bar chart
figure;
bar(data);
title('Data Bar Chart');
xlabel('Index');
ylabel('Value');

% Plotting a scatter plot
figure;
scatter(data(:,1), data(:,2));
title('Data Scatter Plot');
xlabel('X-Axis');
ylabel('Y-Axis');

**Logical Analysis:**

* The `plot` function creates a line graph of the data.
* The `bar` function creates a bar chart of the data.
* The `scatter` function creates a scatter plot of the data.

**Parameter Explanation:**

* `data`: The data to be visualized.
* `figure`: Creates a new graphic window.
* `title`: Sets the title of the graph.
* `xlabel`: Sets the label for the X-axis.
* `ylabel`: Sets the label for the Y-axis.

# 3.1 Time Series Analysis

#### 3.1.1 Acquisition and Processing of Time Series Data

**Data Acquisition**

***Importing from Text Files:** The `load` function can import time series data from text files, specifying the delimiter and date format.

data = load('time_series.txt', '-ascii');
dates = load('time_series.txt', '-ascii', 1);   % Loads the first line as dates

***Importing from a Database:** The `database` function can connect to a database and extract time series data.

conn = database('my_db', 'username', 'password');
data = fetch(conn, 'SELECT * FROM tim