financial.sharpe_ratio

Sharpe Ratio for measuring risk-adjusted returns in investment portfolios.

The Sharpe Ratio is a measure of risk-adjusted return developed by Nobel laureate William F. Sharpe. It calculates the excess return per unit of risk (standard deviation) and is widely used to compare the performance of investment portfolios.

Wikipedia Reference: https://en.wikipedia.org/wiki/Sharpe_ratio Investopedia: https://www.investopedia.com/terms/s/sharperatio.asp

The Sharpe Ratio is used for: - Comparing performance of different investment strategies - Evaluating mutual funds and hedge funds - Portfolio optimization and risk management - Assessing risk-adjusted returns in trading strategies

Attributes

monthly_returns

Functions

annualized_sharpe_ratio(→ float)	Calculate the annualized Sharpe Ratio for a series of periodic returns.
sharpe_ratio(→ float)	Calculate the Sharpe Ratio for a series of returns.

Module Contents

financial.sharpe_ratio.annualized_sharpe_ratio(returns: list[float], risk_free_rate: float = 0.0, periods_per_year: int = 252) → float

Calculate the annualized Sharpe Ratio for a series of periodic returns.

The annualized Sharpe Ratio accounts for the time period of returns: S_annual = S_periodic * sqrt(periods_per_year)

Common periods_per_year values: - Daily returns: 252 (trading days) - Weekly returns: 52 - Monthly returns: 12 - Quarterly returns: 4

Parameters:

• returns – List of periodic returns

• risk_free_rate – Risk-free rate per period, default 0.0

• periods_per_year – Number of periods in a year, default 252 (daily)

Returns:

Annualized Sharpe Ratio

>>> round(annualized_sharpe_ratio(
...     [0.001, 0.002, 0.0015, 0.0005, 0.0012], 0.0, 252), 4)
35.1844
>>> round(annualized_sharpe_ratio([0.01, 0.02, 0.015, 0.005, 0.012], 0.0, 12), 4)
7.6779
>>> round(annualized_sharpe_ratio([0.05, 0.06, 0.055, 0.045, 0.052], 0.0, 4), 4)
18.7322
>>> round(annualized_sharpe_ratio([0.001, 0.002, 0.0015], 0.0001, 252), 4)
44.4486
>>> round(annualized_sharpe_ratio([0.001, 0.002], 0.0, 252), 4)
33.6749
>>> annualized_sharpe_ratio([0.001, 0.002, 0.0015], 0.0, 0)
Traceback (most recent call last):
    ...
ValueError: periods_per_year must be > 0
>>> annualized_sharpe_ratio([0.001, 0.002, 0.0015], 0.0, -252)
Traceback (most recent call last):
    ...
ValueError: periods_per_year must be > 0

financial.sharpe_ratio.sharpe_ratio(returns: list[float], risk_free_rate: float = 0.0) → float

Calculate the Sharpe Ratio for a series of returns.

The Sharpe Ratio formula: S = (R - Rf) / std_dev

Where: S = Sharpe Ratio R = Average return of the investment Rf = Risk-free rate of return std_dev = Standard deviation of returns (volatility)

Parameters:

• returns – List of periodic returns (e.g., daily, monthly)

• risk_free_rate – Risk-free rate of return per period, default 0.0

Returns:

Sharpe Ratio

>>> round(sharpe_ratio([0.1, 0.2, 0.15, 0.05, 0.12]), 4)
2.2164
>>> sharpe_ratio([0.05, 0.05, 0.05, 0.05, 0.05])
inf
>>> round(sharpe_ratio([0.1, 0.2, 0.15, 0.05, 0.12], 0.02), 4)
1.8589
>>> sharpe_ratio([0.0, 0.0, 0.0, 0.0, 0.0])
0.0
>>> round(sharpe_ratio([-0.05, -0.1, -0.08, -0.12, -0.15]), 4)
-2.6261
>>> sharpe_ratio([])
Traceback (most recent call last):
    ...
ValueError: returns list must not be empty
>>> sharpe_ratio([0.1])
Traceback (most recent call last):
    ...
ValueError: returns list must contain at least 2 values

financial.sharpe_ratio.monthly_returns