markowizard.data¶
data ¶
Convenience functions for fetching market data and computing returns.
Use these to quickly download prices from Yahoo Finance. The core analytical modules also accept a pre-computed returns DataFrame directly, so these helpers are optional in practice.
fetch_prices ¶
fetch_prices(
tickers: list[str],
period: str = "5y",
auto_adjust: bool = True,
) -> pd.DataFrame
Download historical adjusted close prices for a list of tickers.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tickers
|
list of str
|
Yahoo Finance ticker symbols (e.g., ['AAPL', 'MSFT', 'SPY']).
Each ticker must match |
required |
period
|
str
|
Data period (default '5y'). See yfinance for valid periods. |
'5y'
|
auto_adjust
|
bool
|
Whether to use auto-adjusted close prices (default True). |
True
|
Returns:
| Type | Description |
|---|---|
DataFrame
|
DataFrame of closing prices with DatetimeIndex and tickers as columns. |
compute_monthly_returns ¶
compute_monthly_returns(prices: DataFrame) -> pd.DataFrame
Convert daily close prices to monthly percentage returns.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
prices
|
DataFrame
|
Daily closing prices with DatetimeIndex and tickers as columns. |
required |
Returns:
| Type | Description |
|---|---|
DataFrame
|
DataFrame of monthly percentage returns. |