# Corporate Actions

# Adjusting prices for corporate actions

We can use built-in functions to adjust price and volume for corporate actions.

We follow an example of a 1:3 split for WMT on Feb 26, 2024.
First let's review the unadjusted data: there appears to be a price jump.

```ipython3
import onetick.py as otp

data = otp.DataSource('US_COMP_SAMPLE_DAILY', tick_type='DAY')
data = data[['CLOSE', 'VOLUME', 'EXCHANGE']]
data = data.where(data['EXCHANGE'] == '')
result = otp.run(data,
                 start=otp.dt(2024, 2, 10),
                 end=otp.dt(2024, 3, 10),
                 symbols='WMT')
result.plot(x='Time', y='CLOSE')
```

```myst-ansi
<Axes: xlabel='Time'>
```

```myst-ansi
<Figure size 640x480 with 1 Axes>
```

Adding adjustment for corporate actions fixes this.
The prices are adjusted to the level before or after the split depending on the value of the `adjustement_date` parameter.
The next example illustrates this:

```ipython3
data = otp.DataSource('US_COMP_SAMPLE_DAILY', tick_type='DAY')
data = data[['CLOSE', 'VOLUME', 'EXCHANGE']]
data = data.where(data['EXCHANGE'] == '')
data['ORG_CLOSE'] = data['CLOSE']
data = data.corp_actions(fields='CLOSE', adjust_rule='PRICE', apply_split=True)
result = otp.run(data,
                 start=otp.dt(2024, 2, 10),
                 end=otp.dt(2024, 3, 10),
                 timezone='America/New_York',
                 symbols='WMT',
                 symbol_date=otp.dt.now())

result.plot(x='Time', y='CLOSE')
```

```myst-ansi
<Axes: xlabel='Time'>
```

```myst-ansi
<Figure size 640x480 with 1 Axes>
```

Adjustment can be applied to sizes in a similar way:

```ipython3
data = otp.DataSource(db='US_COMP_SAMPLE_DAILY', tick_type='DAY')
data = data[['CLOSE', 'VOLUME', 'EXCHANGE']]
data = data.where(data['EXCHANGE'] == '')
result = otp.run(data,
                 start=otp.dt(2024, 2, 10),
                 end=otp.dt(2024, 3, 10),
                 timezone='America/New_York',
                 symbols='WMT',
                 symbol_date=otp.dt.now())
result.plot(x='Time', y='VOLUME')
```

```myst-ansi
<Axes: xlabel='Time'>
```

```myst-ansi
<Figure size 640x480 with 1 Axes>
```

```ipython3
data = otp.DataSource(db='US_COMP_SAMPLE_DAILY', tick_type='DAY')
data = data[['CLOSE', 'VOLUME', 'EXCHANGE']]
data = data.where(data['EXCHANGE'] == '')
data['ORG_VOLUME'] = data['VOLUME']
data = data.corp_actions(fields='VOLUME', adjust_rule='SIZE', apply_split=True)
result = otp.run(data,
                 start=otp.dt(2024, 2, 10),
                 end=otp.dt(2024, 3, 10),
                 timezone='America/New_York',
                 symbols='WMT',
                 symbol_date=otp.dt.now())
result.plot(x='Time', y='VOLUME')
```

```myst-ansi
<Axes: xlabel='Time'>
```

```myst-ansi
<Figure size 640x480 with 1 Axes>
```

# Retrieving Corporate actions for a symbol

We can retrieve all corporate actions for the symbols of interest:

```ipython3
db = otp.databases()['US_COMP_SAMPLE_DAILY']
db.ref_data(
    ref_data_type='corp_actions',
    start=otp.dt(2024, 2, 10),
    end=otp.dt(2024, 3, 10),
    timezone='America/New_York',
    symbol='WMT',
    symbol_date=otp.dt.now(),
)
```

```myst-ansi
        Time  MULTIPLICATIVE_ADJUSTMENT  ADDITIVE_ADJUSTMENT ADJUSTMENT_TYPE
0 2024-02-26                   0.333333                  0.0           SPLIT
```