def set_company_and_data(self, code: str):
"""
Set the company and the closing_prices for this buy and hold strategy
:param code: company code
:type code: str
"""
self.company = code
self.closing_prices = stock_price_data.get_stock_data(
self.company)[column_headings.ADJUSTED_CLOSING_PRICE]
def calculate_cumulative_returns(code: str) -> pd.DataFrame:
"""
:param code: code of the company
:type code: str
:return: cumulative returns
:rtype: pd.Dataframe
"""
data = get_stock_data(code)
data[RETURNS] = _calculate_percentage_change(data)
return (data[RETURNS] + 1).cumprod()
def calculate_returns_daily(code: str) -> pd.DataFrame:
"""
Calculate daily returns given a code
:param code: code of the company
:type code: str
:return: daily percentage change
:rtype: pd.Dataframe
"""
data = get_stock_data(code)
return _calculate_percentage_change(data)
def calculate_returns_monthly(code: str) -> pd.DataFrame:
"""
Calculate monthly return given a code
:param code: code of the company
:type code: str
:return: monthly percentage change
:rtype: pd.Dataframe
"""
data = get_stock_data(code)
return data[CLOSE].resample(MONTH).ffill().pct_change()
def calculate_percentage_change_based_on_adjusted_closing_price(
code: str) -> pd.DataFrame:
"""
Calculate percentage change of a company given a company code
:param code: company code
:type code: str
:return: percentage changes
:rtype: pd.Dataframe
"""
return get_stock_data(code)[ADJUSTED_CLOSING_PRICE].pct_change().dropna()