def get_volatility(symbol, start_date=dt(year=2013, month=1, day=1), end_date=dt.today(), index_symbol="^GSPC"):
"""
Standard deviation of returns
:param symbol:
:param start_date:
:param end_date:
:param index_symbol:
:return:
"""
symbol_returns = get_pct_returns(symbol, start_date, end_date)
index_returns = get_pct_returns(index_symbol, start_date, end_date)
cov_mat = np.cov(symbol_returns, index_returns)
volatility = np.sqrt(cov_mat[0, 0])
return volatility * 100
def get_beta(symbol, start_date=dt(year=2013, month=1, day=1), end_date=dt.today(), index_symbol="^GSPC"):
"""
:param symbol:
:param start_date:
:param end_date:
:param index_symbol:
:return:
"""
symbol_returns = get_pct_returns(symbol, start_date, end_date)
index_returns = get_pct_returns(index_symbol, start_date, end_date)
# TODO: if stock does not have data since start_date
cov_mat = np.cov(symbol_returns, index_returns)
beta = cov_mat[0, 1] / cov_mat[1, 1]
return beta
def get_volatility(symbol,
start_date=dt(year=2013, month=1, day=1),
end_date=dt.today(),
index_symbol='^GSPC'):
"""
Standard deviation of returns
:param symbol:
:param start_date:
:param end_date:
:param index_symbol:
:return:
"""
symbol_returns = get_pct_returns(symbol, start_date, end_date)
index_returns = get_pct_returns(index_symbol, start_date, end_date)
cov_mat = np.cov(symbol_returns, index_returns)
volatility = np.sqrt(cov_mat[0, 0])
return volatility * 100
def get_beta(symbol,
start_date=dt(year=2013, month=1, day=1),
end_date=dt.today(),
index_symbol='^GSPC'):
"""
:param symbol:
:param start_date:
:param end_date:
:param index_symbol:
:return:
"""
symbol_returns = get_pct_returns(symbol, start_date, end_date)
index_returns = get_pct_returns(index_symbol, start_date, end_date)
# TODO: if stock does not have data since start_date
cov_mat = np.cov(symbol_returns, index_returns)
beta = cov_mat[0, 1] / cov_mat[1, 1]
return beta
def get_alpha(symbol,
start_date=dt(year=2013, month=1, day=1),
end_date=dt.today(),
symbol_returns=None,
index_returns=None,
index_symbol='^GSPC'):
"""
Using Jensen's alpha (https://en.wikipedia.org/wiki/Jensen%27s_alpha)
:param symbol:
:param start_date:
:param end_date:
:param index_symbol:
:return:
"""
if symbol_returns is None:
symbol_returns = get_pct_returns(symbol, start_date, end_date)
if index_returns is None:
index_returns = get_pct_returns(index_symbol, start_date, end_date)
beta = get_beta(symbol, start_date, end_date, index_symbol)
alpha = np.mean(symbol_returns) - beta * np.mean(index_returns)
return alpha * 100
def get_alpha(
symbol,
start_date=dt(year=2013, month=1, day=1),
end_date=dt.today(),
symbol_returns=None,
index_returns=None,
index_symbol="^GSPC",
):
"""
Using Jensen's alpha (https://en.wikipedia.org/wiki/Jensen%27s_alpha)
:param symbol:
:param start_date:
:param end_date:
:param index_symbol:
:return:
"""
if symbol_returns is None:
symbol_returns = get_pct_returns(symbol, start_date, end_date)
if index_returns is None:
index_returns = get_pct_returns(index_symbol, start_date, end_date)
beta = get_beta(symbol, start_date, end_date, index_symbol)
alpha = np.mean(symbol_returns) - beta * np.mean(index_returns)
return alpha * 100
