fincore.core¶
AnalysisContext¶
fincore.core.context.AnalysisContext(returns, *, factor_returns=None, positions=None, transactions=None, period=DAILY)
¶
Lazy, cached container for performance analytics.
All metrics are computed on first access and cached via
:func:functools.cached_property. Call :meth:invalidate to
clear all cached values (e.g. after replacing the underlying data).
参数：
| 名称 | 类型 | 描述 | 默认 |
|---|---|---|---|
returns
|
Series
|
Non-cumulative simple returns with a DatetimeIndex. |
必需 |
factor_returns
|
Series
|
Benchmark / factor returns aligned to the same dates. |
None
|
positions
|
DataFrame
|
Daily net position values. |
None
|
transactions
|
DataFrame
|
Executed trades. |
None
|
period
|
str
|
Data frequency. Default |
DAILY
|
Initialize the analysis context.
参数：
| 名称 | 类型 | 描述 | 默认 |
|---|---|---|---|
returns
|
Series
|
Portfolio returns. |
必需 |
factor_returns
|
Series
|
Benchmark or factor returns. |
None
|
positions
|
DataFrame
|
Portfolio positions. |
None
|
transactions
|
DataFrame
|
Executed trades. |
None
|
period
|
str
|
Data frequency. |
DAILY
|
annual_return
cached
property
¶
Annualized return.
cumulative_returns
cached
property
¶
Total cumulative return.
annual_volatility
cached
property
¶
Annualized volatility.
sharpe_ratio
cached
property
¶
Sharpe ratio (annualized).
calmar_ratio
cached
property
¶
Calmar ratio (annual return / max drawdown).
stability
cached
property
¶
R-squared of linear fit to cumulative returns.
max_drawdown
cached
property
¶
Maximum drawdown.
omega_ratio
cached
property
¶
Omega ratio.
sortino_ratio
cached
property
¶
Sortino ratio (annualized).
skew
cached
property
¶
Return skewness.
kurtosis
cached
property
¶
Return kurtosis.
tail_ratio
cached
property
¶
Tail ratio (95th percentile / 5th percentile).
daily_value_at_risk
cached
property
¶
Daily Value at Risk.
alpha
cached
property
¶
Alpha (excess return over factor returns).
beta
cached
property
¶
Beta (sensitivity to factor returns).
perf_stats()
¶
Return a :class:pd.Series of key performance metrics.
This method assembles the cached sub-metrics so that repeated calls are essentially free after the first computation.
to_dict()
¶
Return metrics as a plain dict (JSON-friendly values).
to_json(**kwargs)
¶
Serialize metrics to a JSON string.
plot(backend='matplotlib', **kwargs)
¶
Plot key performance charts using the specified backend.
参数：
| 名称 | 类型 | 描述 | 默认 |
|---|---|---|---|
backend
|
str
|
Visualization backend name ( |
'matplotlib'
|
返回：
| 类型 | 描述 |
|---|---|
Depends on the backend (e.g. matplotlib Figure or HTML string).
|
|
to_html(path=None)
¶
Generate a self-contained HTML performance report.
参数：
| 名称 | 类型 | 描述 | 默认 |
|---|---|---|---|
path
|
str
|
If given, write the HTML to this file path. |
None
|
返回：
| 类型 | 描述 |
|---|---|
str
|
The HTML report as a string. |
invalidate()
¶
Clear all cached metric values.
RollingEngine¶
fincore.core.engine.RollingEngine(returns, *, factor_returns=None, window=252, period=DAILY)
¶
Batch rolling metric computation engine.
参数：
| 名称 | 类型 | 描述 | 默认 |
|---|---|---|---|
returns
|
Series
|
Non-cumulative simple returns with a DatetimeIndex. |
必需 |
factor_returns
|
Series
|
Benchmark returns (required for |
None
|
window
|
int
|
Rolling window size. Default 252 (approx. 1 year of daily data). |
252
|
period
|
str
|
Data frequency. Default |
DAILY
|
available_metrics
property
¶
Return the set of metric names supported by this engine.
compute(metrics='all')
¶
Compute the requested rolling metrics.
参数：
| 名称 | 类型 | 描述 | 默认 |
|---|---|---|---|
metrics
|
list of str or ``'all'``
|
Which metrics to compute. Pass |
'all'
|
返回：
| 类型 | 描述 |
|---|---|
dict[str, Series]
|
Mapping from metric name to rolling values. |